Thesis Paper on Performance Of Enhanced Solar Dryer Integrated with Heat Storage System for Fruits & Vegetables Drying

PERFORMANCE OF AN ENHANCED SOLAR DRIER INTEGRATED WITH HEAT STORAGE SYSTEM FOR FRUITS AND VEGETABLES DRYING

Atkilt Mulu Gebrekidan

Advisors: Ftwi Yohanness (Assistant Professor) Meseret Tesfay (M.Tech.)

M.Sc. Thesis in Energy Technology Mekelle University

Ethiopian Institute of Technology-Mekelle Department of Mechanical Engineering September 12, 2013

PERFORMANCE OF AN ENHANCED SOLAR DRIER INTEGRATED WITH HEAT STORAGE SYSTEM FOR FRUITS AND VEGETABLES DRYING

By

ATKILT MULU GEBREKIDAN

FOR A THESIS IN PARTIAL FULFILLMENT OF THE REQUIREMENTS OF THE DEGREE OF MASTER OF SCIENCE IN ENERGY TECHNOLOGY MEKELLE UNIVERSITY September 12, 2013

©2013 Atkilt Mulu. All Rights Reserved.

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CERTIFICATION The undersigned certify that they have read and hereby recommend for acceptance by Mekelle University a thesis entitled: Performance of an Enhanced Solar Drier Integrated with Heat Storage System for Fruits and Vegetables Drying, in fulfillment of the requirements for the degree of Master of Energy Technology of Mekelle University.

Ftwi Yohanness, Assistant Professor Advisor Date: …………………………… And Meseret Tesfay, M.Tech. Co-Advisor Date: ……………………………

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DECLARATION AND COPYRIGHT I, ATKILT MULU GEBREKIDAN, declare that this thesis is my own original work and that it has not been presented and will not be presented to any other University for a similar or any other degree award.

Signature…………………………………… This thesis is copyright material protected under the Berne Convention, the Copyright Act 1999 and other international and national enactments, in that behalf, on intellectual property. It may not be reproduced by any means, in full or in part, except for short extracts in fair dealings, for research or private study, critical scholarly review or discourse with an acknowledgement, without the written permission of the School of Graduate Studies, on behalf of both the author and the EiT – M.

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ACKNOWLEDGEMENT First and for most I would like to praise the Almighty God for the courage and endurance that He inhabits on me. And my countless admiration goes to my advisors Ato Ftwi Yohanness and Ato Meseret Tesfay for all of their supervision, understanding and guidance from the beginning to the end of the thesis work. Then deep from my heart I would like to appreciate Ato Solomon Tsegay, Civil engineering Deprtment Head, Ato Samuel Estifanos and Ato Birhane Gebremedhin from Geology Department and Ato Asfafaw From Mechanical Engineering Department for their support in providing materials and documents during the thesis work. I would also like to extend my gratefulness to my all family, especially to my dear brother Doctor Ing. Berhanu Mulu and my wife Lily Arega their continuous financial and moral encouragements are truly inspiring and remarkable. My appreciation also goes to NORAD Master’s Program within Energy and Petroleum sector (EnPe) project for sponsoring the Masters in Energy Technology hosted at the Department of Mechanical Engineering, Mekelle University. Finaly I would like thank you to all of those helped me during the experiment and construction of the dryer in workshop.

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ABSTRACT Fruits and vegetables play an essential role in human nutrition. Apart from providing flavor and variety to human diet, they serve as important sources of vitamins and minerals which will prevent diseases and promoting health. Most fruits and vegetables contain more water and therefore highly perishable. And water loss and decay account for most of their postharvest losses and short storage life. Therefore, preserving fruits and vegetables is necessary for keeping them for a long time without further deterioration in their quality in order to utilize their nutritional value efficiently. Drying is one of the best method of preserving fruits and vegetables. Natural convection indirect solar dryer is common drying method applied for drying fruits and vegetables. To improve the quality of the product and the performance of the natural convection indirect solar dryer designed at Mekelle university, the solar dryer is integrated with rock bed heat storage system and its thermal performance was experimentally analysed and compared with dryer without heat storage system. Sandston with a size of 2 - 4 cm is used as heat storage directly below the absorber plate. The solar dryer without heat storage system has maximum drying air temperature of 63-68 oC during peak solar radiation, and the maximum daily drying efficiency of 21 %. The solar dryer heat storage system can have a maximum drying air temperature up to 55-58 o C at peak solar radiation. The maximum daily drying efficiency of the system is 27 %. The heat storage system temperature gradually increases from ambient temperature and attains temperature of 38 oC. Since the temperature of the heat storage system decreases gradually, it can keep the minimum drying air temperature variation at high and low radiations. This helps to maintain the product quality as well. The quality of product dried without heat storage dryer has less quality than dried with heat storage dryer. In terms of color quality pre-treated dried fruits and vegetables have better quality, which is more close to the raw fruits and vegetables color.

Key words: Natural convection dryer; Fruits and Vegetables; Heat Storage; Pre-treatment

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1.

Table of Contents

INTRODUCTION .......................................................................................................... 1 1.1. BACKGROUND........................................................................................................ 1 1.2. PROBLEM STATEMENT ........................................................................................ 3 1.3. JUSTIFICATION....................................................................................................... 4 1.4. SCOPE OF THESIS................................................................................................... 4 1.5. OBJECTIVES ............................................................................................................ 4 1.5.1. General Objective .................................................................................................. 4 1.5.2. Specific Objectives ................................................................................................ 4 1.6. LIMITATION OF THE THESIS ............................................................................... 5

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LITERATURE REVIEW ............................................................................................... 6 2. 1. WORKING PRINCIPLE OF PASSIVE SOLAR DRYER ....................................... 6 2. 2. PREVIOUS WORK ON PASSIVE SOLAR DRYER .............................................. 6 2. 3. EFFECT OF HEAT STORAGE ON SOLAR DRYER PERFORMANCE .............. 7

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METHODS AND MATERIALS.................................................................................... 9 3. 1. HEAT STORAGE SYSTEM DESIGN ..................................................................... 9 3.1.1 Heat storage rock selection.................................................................................... 9 3.1.2 Heat storage volume and thickness calculations ................................................... 9 3. 2. EVALUATION OF DEHYDRATED PRODUCTS QUALITY ............................. 10 3. 3. MATHEMATICAL MODELING ........................................................................... 10 3.3.1 Dryer cabinet ....................................................................................................... 10 3.3.2 Energy storage solar collector component .......................................................... 13 3.3.3 Weather data preparation..................................................................................... 14 3. 4. EXPERIMENTAL SETUP ...................................................................................... 15 3.4.1 Description of the solar dryer .............................................................................. 15 3.4.2 Setup without heat storage .................................................................................. 15 3.4.3 Setup with heat storage........................................................................................ 16 3.4.4 Experimental procedure ...................................................................................... 17 3.4.5 Instrumentations .................................................................................................. 18

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RESULTS AND DISCUSSION ................................................................................... 21 4.1 RESULTS OF HEAT STORAGE DESIGN............................................................ 21 4.1.1 Heat storage rock selection.................................................................................. 21 vi

4.1.2 Heat storage volume and thickness calculations ................................................. 21 4.2 RESULTS OF MATHEMATICAL MODELINGS ................................................ 22 4.2.1 Component creating and FORTRAN programing flow chart ............................. 22 4.2.2 FORTRAN programing of the mathematical modeling ...................................... 23 4.3 TRNSYS SIMULATION AND RESULTS............................................................. 24 4.4 EXPERIMENTAL RESULTS AND DISCUSSION............................................... 26 4.4.1 Drying with dryer without heat storage ............................................................... 26 4.4.2 Drying with heat storage integrated dryer ........................................................... 34 4.5 COMPARING THE DRYER PERFORMANCE AND PRODUCT QUALITY .... 45 4.3.1. Dryer performance comparison ........................................................................... 45 4.3.2. Product quality comparison ................................................................................. 45 4.6 SUMMARY ............................................................................................................. 47 5.

CONCLUSION AND RECOMMENDATIONS ......................................................... 48 5.1. CONCLUSION ................................................................................................... 48 5.2. RECOMMENDATIONS .................................................................................... 48

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REFERENCES ............................................................................................................. 49

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APPENDIXES .............................................................................................................. 51 A.

APPENDIX 1: .......................................................................................................... 51

B.

APPENDIX 2: .......................................................................................................... 59

C.

APPENDIX 3: .......................................................................................................... 60

D.

APPENDIX 4: .......................................................................................................... 63

E.

APPENDIX 5: .......................................................................................................... 65

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LISTS OF FIGURES Figure 3-1: Sectional view of the dryer cabinet ..................................................................... 11 Figure 3-2: Sectional view of the solar collector and heat storage system ............................ 14 Figure 3-3: Schematic view of Solar dryer without heat storage ........................................... 16 Figure 3-4: Schematic view of solar dryer with rock storage ................................................ 17 Figure 3-5: K-type thermocouples .......................................................................................... 18 Figure 3-6: METEON Pyranometer ....................................................................................... 19 Figure 3-7: National Instrument data logger ......................................................................... 19 Figure 3-8: Thermometer ....................................................................................................... 20 Figure 3-9: Moisture balance ................................................................................................. 20 Figure 4-1: New component proforma creating flow chart.................................................... 22 Figure 4-2: Flow chart of FORTRAN programing................................................................. 23 Figure 4-3: Creating TRNSYS project for simulation ............................................................ 24 Figure 4-4 Moisture content and weight loss of tomato with time ......................................... 25 Figure 4-5 Heat gain and drying air predictions ................................................................... 25 Figure 4-6: Day 1 drying air temperature and solar radiation distribution .......................... 27 Figure 4-7: Day 2 dryinf air temperature and solar radiation distribution ........................... 27 Figure 4-8: Day 3 drying air temperature and solar radiation distribution .......................... 28 Figure 4-9: Instantaneous weight loss of mangoe slices for three drying days .................... 28 Figure 4-10: Useful heat gain of the solar collector .............................................................. 29 Figure 4-11: Daily mango drying efficiency of the system ..................................................... 30 Figure 4-12: Day 1 tomato drying air temperature and solar radiation distribution ............ 31 Figure 4-13: Day 2 tomato drying air temperature and solar radiation distribution ............ 31 Figure 4-14: Day 3 tomato drying air temperature and solar radiation distribution ............ 32 Figure 4-15: Instantaneous weight loss of tomato slices for the three drying days ............... 33 Figure 4-16: Useful heat gain of the solar collector .............................................................. 33 Figure 4-17: Daily drying efficiency of the solar dryer system .............................................. 34 Figure 4-18: Day 1 tomato drying air temperature and solar radiation distribution ............ 35 Figure 4-19: Day 2 tomato drying air temperature and solar radiation distribution ............ 36 Figure 4-20: Day 1 heat storage and collector temperatures distribution ............................ 36 Figure 4-21: Day 2 heat storage and collector temperatures distribution ............................ 37 Figure 4-22: Instantaneous weight loss of tomatoes’ slices for two days drying ................... 37 Figure 4-23: Useful heat gain of the collector at the first drying day .................................... 38 Figure 4-24: Useful heat gain of the collector for the second drying day ............................. 38 Figure 4-25: Day 1 mango drying air temperature and solar radiation distributions .......... 39 Figure 4-26: Day 2 mango drying air temperature and solar radiation distributions .......... 40 Figure 4-27: Day 3 mango drying air temperature and solar radiation distributions .......... 40 Figure 4-28: Day 1 heat storage and collector temperatures distribution ............................ 41 Figure 4-29: Day 2 heat storage and collector temperatures distribution ............................ 41 viii

Figure 4-30: Day 3 heat storage and collector temperatures distribution ............................ 42 Figure 4-31: Instantaneous weight loss of mangoes slices on the first day ........................... 42 Figure 4-32: Instantaneous weight loss of mangoes slices on day 2 and 3 ............................ 43 Figure 4-33: Useful heat gain of the collector during the first day........................................ 43 Figure 4-34: Useful heat gain of the collector for the 2nd and 3rd days ................................. 44 Figure 4-35: Daily drying efficiency of the solar dryer system .............................................. 45 Figure 4-36: Dried mangoes slices by dryer with heat storage system. ................................. 46 Figure 4-37: Dried mangoes slices by dryer without heat storage system............................. 46 Figure 4-38: Dried tomatoes slices by dryer with heat storage system ................................. 46 Figure 4-39: Dried tomatoes slices by dryer without heat storage system ............................ 46 Figure A 1: Samples slices preparation.................................................................................. 59 Figure A 2: Samples distribution on trays and drying cabinet ............................................... 59 Figure A 3: Experimental setup .............................................................................................. 59 Figure A 4: Construction of dryer with heat storage rock ..................................................... 60 Figure A 5: Creating new component proforma..................................................................... 60 Figure A 6: Generating FORTRAN code skeleton and a compiler project ............................ 61 Figure A 7:Writing Mathematical equations on microsoft visual stidio ................................ 61 Figure A 8: Component selection from TRNSYS studio ......................................................... 62 Figure A 9: Connecting components inputs and outputs ........................................................ 62 Figure A 10: Configuring connections for simulation ............................................................ 62 Figure A 11: Typical meteorological year format weather data of Mekelle .......................... 63 Figure A 12: Graphical representations of the prepared data ............................................... 64

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LIST OF TABLES Table 4-1: Thermo-Physical properties of Rocks for sensible heat storage[25] .................... 21 Table A 1: Drying without heat storage on 16/06/13 ............................................................. 65 Table A 2: Drying without heat storage on 17/06/13 ............................................................. 65 Table A 3: Drying without heat storage on 18/06/13 ............................................................. 65 Table A 4: Drying with heat storage on 03/07/13 .................................................................. 65 Table A 5: Drying with heat storage on 04/07/13 .................................................................. 66 Table A 6: Drying with heat storage on 05/07/13 .................................................................. 66 Table A 7: Drying without heat storage on 20/06/13 ............................................................. 66 Table A 8: Drying without heat storage on 21/06/13 ............................................................. 67 Table A 9: Drying without heat storage on 22/06/13 ............................................................. 67 Table A 10: Drying without heat storage on 28/06/13 ........................................................... 68 Table A 11: Drying without heat storage on 29/06/13 ........................................................... 68

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NOMENCLATURES Surface area of solar collector (m2) Surface area of drying tray (m2) Solar intensity on horizontal surface (W/m2) Drying constant (s-1) Latent heat of vaporization (KJ/kg. k) 𝐾_𝑖𝑛𝑠 Thermal conductivity of insulation (W/m. K) 𝑚𝑤𝑓 Total water content to be removed (kg) 𝑚𝑤𝑡 Instantaneous mass of water (kg) 𝑀𝑒 Equilibrium moisture content (%) 𝑀𝑓 Final moisture content (%) 𝑀𝑜 Initial moisture content (%) Instantaneous moisture content on dry basis (%) 𝑀𝑡 𝑀𝑠𝑟 Moisture content at sunrise (%) Moisture content at sunset (%) 𝑀𝑠𝑠 𝑅𝐻𝑡 The estimated relative humidity at time (%) 𝑅𝐻𝑚𝑎𝑥 Daily maximum humidity (%) 𝑅𝐻𝑚𝑖𝑛 Daily minimum humidity (%) 𝑅𝑛 Nocturnal moisture re-absorption or losses (%) Temperature drying air (oC) 𝑇𝑎 𝑇𝑐 Temperature crop to dried (oC) Dry bulb temperature at time (oC) 𝑇𝑡 𝑇𝑚𝑎𝑥 Daily mean maximum temperature (oC) 𝑇𝑚𝑖𝑛 Daily mean minimum temperature (oC) 𝑡 Desired time period (s) 𝑊𝑑 Weight of dried product (kg) 𝑊𝑜 Initial weight of dried product (kg) 𝑍𝑖𝑛𝑠_𝑏𝑜𝑡 Thickness of the bottom insulation (m) 𝑍𝑖𝑛𝑠_𝑠𝑖𝑑 Thickness of the side insulation (m) 𝐴coll 𝐴𝑡𝑟𝑎𝑦 𝐼 𝑘 ℎfg

GREEK LETTERS

ɳd ɳn ɳ𝑟𝑜𝑐𝑘

𝜌𝑟𝑜𝑐𝑘

Daily drying efficiency (%) Normalized daily drying efficiency (%) Efficiency of limestone (%) Limestone density

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1. INTRODUCTION 1.1. BACKGROUND Fruits and vegetables play an essential role in human nutrition. Apart from providing flavor and variety to human diet, they serve as important sources of vitamins and minerals which will prevent diseases and promoting health. Most fruits and vegetables contain more water and therefore highly perishable. And water loss and decay account for most of their postharvest losses and short storage life. But, serious losses will arise in the availability of the essential nutrients, vitamins and minerals constituted in them. Therefore, preserving fruits and vegetables is necessary for keeping them for a long time without further deterioration in their quality in order to utilize their nutritional value efficiently [1]. The post-harvest losses of fruits and vegetables are estimated to be more than 30% in the developing countries due to their perishable nature, poor storage facility, poor marketing conditions and shortage of low-cost and appropriate post-harvest technologies [1]. The problems related to short storage life of fruits and vegetables in developing countries like Ethiopia are blown up more by the poor transportation and marketing system [2]. The development of agro-industries and food processing sectors can play a vital role in reducing the post-harvest losses by processing and value addition of fruits and vegetables which will ensure better remuneration to the growers. Therefore, to enhance the shelf life of fruits and vegetables and minimizes post-harvest loss much effort have to be done in developing efficient and low-cost local post-harvest technologies. Drying is one of such preservation methods of fruits and vegetables that can enhance their shelf life [2, 3]. Drying using solar energy is one of oldest and world widely known method of agricultural products preservation practiced by humankind. Drying will help fruits and vegetables to extending their shelf life by reducing the moisture content to optimum level below which deterioration does not occur. Apart from extending the shelf life, it can also improve quality of dehydrated products, to sustain constant price, lower storage and transportation costs and reduces post-harvest losses highly, since most of the water is taken out during the drying process [3, 4]. Open sun drying is the oldest and widely known traditional method for drying crops in developing countries. Open sun drying is the simplest and cheapest method of drying agricultural products such as fruits, vegetables, cereals, grains, tobacco, timber, etc. by spreading on the ground and turned regularly until sufficiently dried so that they can be stored safely. In Ethiopia the traditional open sun drying methods have also commonly used for drying crops, but little attempts have been made for drying of fruits and vegetables. Even if, open sun drying requires little capital and work force, it also associated with many problems and short comings. Open sun drying requires large drying space and long drying period. The short comings of open sun drying are; crops damaged because of the hostile weather conditions, contamination of crops from the foreign materials, degradation by overheating, and infestation by insect, rodents, birds and other animals. It may result in 1

physical and structural changes in the product such as shrinkage, case hardening, loss of nutrient and volatiles components and lower water reabsorption during rehydration. And there is no control on the drying process of open sun drying, and this could lead to slow drying rate, poor quality and contamination of dried products, and losses in production [3, 4]. To overcome the drawbacks of open sun drying various types of drying devices like solar dryer, electric dryers, wood-fuel driers and oil-burned driers are adopted and used widely. However, the high cost of oil and electricity and their scarcity in the rural areas of most developing countries have made these driers to be unattractive and expensive. Therefore, interest has been focused mainly on the development of driers using solar energy as heat source [2, 3 and 5]. Solar assisted drying system is one of the most attractive and promising applications of solar energy systems. For drying applications solar energy can easily provide low heating temperature required for fruits and vegetables drying [6]. Solar energy is inexhaustible and abundantly found renewable energy sources. And its intensity is relatively high near the equator. The introduction of dryers powered by solar energy for drying fruits and vegetables will be feasible to countries located near the equator like Ethiopia since they are endowed to high solar radiation intensity and long sunshine duration. Now a day, due to atmospheric pollution related issues and increasing price of fossil fuels the application of solar thermal technologies have gaining rapid acceptance in agriculture application as an energy saving mechanism. Since the solar intensity varies from region to region the type and method of solar energy conversion technologies also varies. Solar drying can be considered as an elaboration of sun drying and is an efficient system of utilizing solar energy. The purpose of a solar dryer is to supply the product with heat by conduction and convection from the surrounding air more than that available under ambient conditions at temperatures above that of the product, or conduction from heated surfaces in contact with the product [7]. The introduction of solar drying system seems to be one of the most promising alternatives to reduce post-harvest losses. As compared to open sun dried products, solar dried products have much better color and texture. The justification for solar dryers is that they dry products rapidly, uniformly and hygienically, the traits inevitable for industrial food drying processes. Since, they are more effective than open sun drying method [3]. According to the method of drying, Duffle and Beckman [8] classified solar dryers in to three namely; 1. Direct solar dryer 2. Indirect solar dryer 3. Mixed solar dryer Direct solar dryer, the crop is placing on top of the absorber plate dried using both direct solar radiation and air which enters by natural convection to collector through the opening between absorber and glass cover. The construction of direct solar dryer is simple and lowcost compare to the other types of solar dryers. Since the product have direct contact with 2

sunlight drying of fruits and vegetables with this type of dryer will expose them to ultraviolet radiation which accounts for color change and losses of some minerals and vitamins of fruits and vegetables. An indirect solar dryer uses pre-heated air in the solar collector to dry the product in the drying chamber. Here it is possible to control the temperature in the dryer. Since the products have no direct contact with sunlight they are not exposed to ultraviolet radiation which accounts for the damage of color and nutrients of the dehydrated product [5]. According to the mode of air flow indirect solar dryers are further classified into natural convection and forced convection solar dryers [8]. Natural convection indirect solar dryers do not require a fan to pump the air through the dryer. However, it’s low air flow rate and longer drying time result in low drying capacity and restricts its application to small scale level. Forced convection solar dryer are used for commercial production of agricultural products. Forced convection solar dryer provides a better control of drying air and require additional energy for drying operation. Natural convection solar dryer is highly preferred for drying food products especially when a thin layer drying is considered [3]. And also due to its zero electricity consumption, natural convection solar dryers are widely used in rural areas to dry agricultural products where electricity is not accessible. For commercial applications, the ability of the drier to process continuously throughout the day is very important to dry the fruits and vegetables to their safe storage level and to maintain the quality. Thermal storage systems are employed with the dryer to store thermal energy, which includes sensible heat and latent heat storage. The most commonly known sensible heat storage materials used to store the sensible heat are water, gravel bed, sand, clay and concrete [9]. Therefore in this study the performance of indirect natural convection solar dryer will be improved by designing heat storage system to using the sensible heat storage material to integrate with it. The performance of the solar dryer will be evaluated and compared with other types of solar dryer without heat storage system. 1.2. PROBLEM STATEMENT To prevent the post-harvest losses of agricultural products “Natural Convection Indirect Solar Dryer” was designed and manufactured at Mekelle University, Mechanical Engineering Department. However, continuous operation of the dryers is limited due to absence of heat storage mechanism and intermittent energy supply due to climatic conditions variation (like solar intensity, sunshine hour, and cloud cover) and this makes the dryers unsuitable to dry fruits and vegetables. If drying of fruits and vegetables continues with these solar dryers the quality of dehydrated product will be degraded, sometimes beyond edibility, and also due to limited drying capacity incompetent for commercial applications. Therefore, it is critically important to integrating thermal storage system with the solar collector to improve the dryer performance and also maintain the desired quality of dehydrated product. In this study, the 3

design and construction of improved solar dryer integrated with heat storage system for drying fruits and vegetables will be the major emphasis. Besides, performance test will be conducted using simulation softwares and models encountered in literatures to determine the drying characteristics of the products by considering the gaps identified from previous study. 1.3. JUSTIFICATION Natural convection indirect solar dryer for crop drying was designed in Mekelle University, Mechanical Engineering Department, and this research is continuation to that. These types of dryer are the most appropriate for drying agricultural products especially for third world countries. But the drying air temperature of these dryers is not constant due to variation of solar intensity and cloud cover. The drying air temperature is the most important parameter need to be controlled in drying of fruits and vegetables since its variation can affect the quality of dehydrated product. Therefore, to use these types of dryers to dry fruits and vegetables, it is necessary to store the surplus solar energy appearing at the radiation peaks using locally available heat storage materials to control this temperature and to avoid local over drying. Storing of the solar energy also reduces drying time and moisture re-absorption of the product from the surrounding air during night and improves the dryer efficiency by extending the drying period. These all circumstances can justify the importance of integrating heat storage system with solar dryer to dry fruits and vegetables in order to have better quality of dehydrated product and dryer efficiency. 1.4. SCOPE OF THESIS The scopes of the thesis was analyzing the performance of the existing solar dryer to optimize and upgrade, designing the thermal storage system to integrate with it and selecting the heat storage material. The experiment has been conducted at Mekelle University, main campus. The thermal performance of the dryer with heat storage system has been evaluated for selected fruits and vegetables drying in relation to weather parameters. These highly variable environmental conditions make the characterization of the drying process difficult because parameters such as air temperature and airflow are constantly varying. Therefore, this study does not attempt to derive a drying model for the particular dryer design. The study experimentally compares the differences in dryer performance and product quality between natural convection solar dryer with and without heat storage system. 1.5. OBJECTIVES 1.5.1. General Objective To design, construct and analyze the thermal performance of natural convection indirect solar dryer integrated with heat storage system for fruits and vegetables drying. 1.5.2. Specific Objectives 1. To design a solar dryer with rock as heat storage material. 2. To simulate the solar dryer to optimize and upgrade the design for better performance.

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3. To analyze the drying kinetics of natural convection solar drying of mangoes and tomatoes slices in relation to weather parameters, and to evaluate quality of dehydrated products. 4. To compare the dryer performance and product quality with natural convection indirect solar drier for drying mangoes and tomatoes slices.

1.6. LIMITATION OF THE THESIS To create the new component for simulation TRNSYS require compiler to write and synchronize the mathematical modeling with the new component. Simulation part of the thesis was delayed for long time due to lack of the FORTRAN compiler software. Since the FORTRAN compiler used for this thesis was the second option for TRNSYS, compiling with this software requires good FORTRAN programing language. These all things and the time constraint were the major limitation of the thesis.

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2. LITERATURE REVIEW To preserve fruits and vegetables for a longer time without any deterioration in their quality and nutritional value the moisture content should be reduced to the optimum level. Generally, many fruits and vegetables have large quantity moisture, usually above 70% on wet basis. In order to lower this large quantity of moisture to optimum level of 7–15% requires large amount of energy [10]. Normally fruits and vegetables are very sensitive at high temperature, which might affect their composition and damage the quality. So to have good quality of dried fruits and vegetables the drying temperature should be kept between the recommended ranges of 35–63oC [10]. Drying of fruits and vegetables using different types of solar dryers have been conducted by a number of researchers to reduce the moisture content, and which can be prepared further to value added products [11]. Among the vast types of dryers passive dryers become most appropriate for drying these products to minimize damage (decolonization and surface cracking) when exposed to direct solar radiation [11]. Hence, natural convection indirect solar dryers are best suitable for drying of fruits and vegetables, and only these types of dryers with and without heat storage system performance are reviewed in this study. 2. 1. WORKING PRINCIPLE OF PASSIVE SOLAR DRYER Heat and mass transfer are the two fundamental processes which govern the drying process. The indirect type solar dryer basically consists of solar collector and drying chamber. The air which dries the product first heated by absorbing heat from the heated absorber plate in the collector and this absorbed heat will transfer to moist product in the drying chamber when the hot air flows from the collector to drying chamber and then moisture will be removed from the product to attain the required moisture level [12]. 2. 2. PREVIOUS WORK ON PASSIVE SOLAR DRYER The natural convection indirect solar crop dryer without heat storage system was designed, manufactured and tested its performance by Dawit [13] at Mekelle University, Mechanical Engineering Department. The solar dryer was designed basically by considering fixed drying time from the sunshine hour data to dry 10kg of tomato. During design of the chimney only its height was considered but its position has needed to be considered. For the performance test it was not clearly stated whether thin or thick layer drying was used. The thermal performance of the dryer was tested for drying a single type of crop by determining the drying rate. The moisture re-absorption or loss of the product during off sunshine from the surrounding air and the quality of dehydrated crop were not considered during the test. The study concluded that, since it dried high moisture content tomato it could also dry other types of crops efficiently. Forced convection solar dryer with heat storage system was designed and constructed by Anteneh and Assab [14] at Mekelle University, Mechanical Engineering Department for final year project of undergraduate program. The dryer was designed to dry 5kg of maize in 11hrs 6

using the drying temperature of 70oC to lower the moisture content from 65% to 3%. For the heat storage material black stone was selected by considering its thermal conductivity and it was integrated with drying chamber. In this dryer type the air was first heated by the collector and pumped to the storage material using fan and then the air out from the storage system was passed through the drying chamber to dry the product. In this project work the performance of the dryer was not evaluated but some performance parameters were calculated with some assumptions and were used as input for the design process. 2. 3. EFFECT OF HEAT STORAGE ON SOLAR DRYER PERFORMANCE The effects of size and types of different thermal energy storage materials on the thermal performance of natural convection indirect solar dryers have been studied by researchers and they are able to achieve some critical results. Passive type solar crop dryer integrated with heat storage and with shallow bed and reflector on chimney was designed and tested its performance analytically by Tiwari et al [15]. During analysis the reflector effect on the collector and the effect of thermal storage and crop properties on outlet air temperature of the collector were considered. The energy balance equations were analytically expressed in terms of the design and climatic parameters. The analytical result showed increased collector and heat storage efficiency due to the reflector effect which in turn increases the drying period and significantly reduces drying time. A solar air heater with tube as solar energy absorber and energy storage was designed and experimentally studied its performance. The tube was used to replace the corrugated absorber plate in conventional solar air heaters and to create turbulence near the collector surface which increased the heat transfer coefficient. The sensible and latent heat storage materials used for test were sand, paraffin wax and Glauber's salt. From the experimental results it was observed that the system heat losses were reduced because of reduced absorber temperature due to incorporated thermal energy storage materials. The temperature of outlet air from the collector also increased due to increased heat transfer coefficient. The effective heat gain and overall efficiency also improved due to introduction of thermal storage materials. The daily average efficiency obtained with paraffin wax was higher as compared to sand as the storage material. The effective heat transfer rate increased with air flow rate for a shorter effective period [16]. The performance and heat transfer characteristics of flat plate solar air heater with and without thermal storage material was studied theoretically and experimentally by Saravana Kumar [17]. Mathematical model was developed based on convective heat transfer correlations and some assumptions to predict the thermal conductivity effect of heat storage material on the collector. The implicit method of finite difference scheme was employed to solve the model. The model predicted higher collector efficiency for solar air heater with thermal storage than without thermal storage material, and the thermal conductivity of the storage material had significant effect on the thermal performance of the solar air heater. The model was validated by comparing with the experimental data.

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The effect of thermal energy storage materials on the performance of air collector was studied by Goyal [18] for Delhi climatic conditions. The air collector constructed on the ground and consisted of two regions, the top region was the absorber made of the energy storage material itself and covered with glass, the second region is was the ground filled with soil, and the air was heated up when it flowed between the two regions. Energy storage materials used for the study were concrete, brick, sand, and ground and phase change material. The energy balance equations were developed by considering different assumptions. Ambient temperature and solar intensity were expressed periodically to analyze the temperature of the storage at different depth and flowing air temperature. The energy balance equations were computed numerically to study optimum length and thickness of storage material and the effect of air flow rate on collector thermal performance. From the results better performance was observed when using brick and concrete as energy storage materials compared to the others. Due to its simplicity in preparation concrete was chosen to investigate further to get optimum thickness. The solar air heater with and without storage materials for drying application was investigated experimentally. Transient analytical model was developed by assuming the flowing air temperature to vary with time and space coordinates, the effects of design parameters of the air heater such as length, width, spacing between the absorber plate and glass cover, mass flow rate and the storage material (sand, granite and water) type and thickness on the outlet and average temperatures of the flowing air were studied. Increased heater performance with storage system were achieved at the optimum thickness (0.12 m) of the storage material that enabled continues drying process during night, to prevent products from re-absorption of moisture from the surrounding air, and this makes the air heater promising heat source for drying fruits and vegetables [19]. From the literatures reviewed above the thermal performance of the solar dryers can be greatly improved simply by integrating the thermal storage system with it. In this research modeling and simulation of the existing work and integrating it with a heat storage system to optimize and upgrade the design will be the major priority. Evaluating the performance of the dryer by considering the major evaluation parameters drying time, drying rate and drying efficiency and also effect of the moisture re-absorption or loss of the product during night for thin layer drying of fruits and vegetables.

8

3. METHODS AND MATERIALS 3. 1. HEAT STORAGE SYSTEM DESIGN 3.1.1 Heat storage rock selection The data for available types of rocks around Mekelle would be collected and identified from the geological map of Mekelle prepared by Mekelle University, Geology Department. The heat storage rock bed which integrated with the solar collector would be selected based on their thermo-physical properties, availabilities and accessibilities. For better temperature distribution along the storage volume the rock bed would be prepared with the dimension of 2 – 4 cm [20]. 3.1.2 Heat storage volume and thickness calculations To design the heat storage size the following assumptions were considered.  For design purpose the dryer was expected to dry tomatoes because of its high moisture content.  Maximum initial moisture content of tomato (Mo) was taken as 92%.  Final moisture content in the dried tomatoes (Mf) was 15%.  10kg of sliced tomatoes would be dry per batch.  The initial temperature of crop (𝑇𝑐_𝑖𝑛 ) equal to ambient temperature  The tomatoes are dried at night by the stored energy  The efficiency of the storage material to release the stored energy to absorber was assumed to be 70% due to good thermal conductivities of sandstone. i.

The amount of water need to be removed from tomato would be calculated as follow; 𝑚𝑤𝑓 =

𝑊𝑜 (𝑀𝑜 −𝑀𝑓 )

(3.1)

1−𝑀𝑓

ii. The total energy required by the air to evaporate the water from the tomatoes would be calculated from the following relations; 𝑚𝑎 ∗ 𝐶𝑃𝑎 ∆𝑇 = 𝑚𝑤𝑓 ∗ ℎ𝑓𝑔 (3.2) iii. Heat content of water vapor would be calculated from the initial temperature of the crop. ℎ𝑓𝑔 = 2501 + 1.84𝑇𝑐_𝑖𝑛 (3.3) iv. The total heat loss (UL ) is calculated as follow; (3.4)

𝑈𝐿 = 𝑈𝑏 + 𝑈𝑒

Where; 𝑈𝑏 =

𝐾𝑖𝑛𝑠

𝑍𝑖𝑛𝑠_𝑏𝑜𝑡

and 𝑈𝑒 =

𝐾𝑖𝑛𝑠

𝑍𝑖𝑛𝑠_𝑠𝑖𝑑

v. The volume of the storage material would be calculated from the total energy required by the storage material to heat up the flowing air. 𝑚𝑟𝑜𝑐𝑘 ∗ 𝐶𝑃𝑟𝑜𝑐𝑘 ∆𝑇 =

𝑚𝑎 ∗𝐶𝑃𝑎 ∆𝑇+𝑈𝐿

9

ɳ𝑠

(3.5)

And,

Where; 𝑚𝑟𝑜𝑐𝑘 = 𝜌𝑟𝑜𝑐𝑘 ∗ 𝑉𝑠

𝜌𝑟𝑜𝑐𝑘 ∗ 𝑉𝑠 ∗ 𝐶𝑃𝑟𝑜𝑐𝑘 ∆𝑇 =

𝑚𝑎 ∗𝐶𝑃𝑎 ∆𝑇+𝑈𝐿

𝑉𝑠 =

ɳ𝑟𝑜𝑐𝑘

𝑚𝑎 ∗𝐶𝑃𝑎 ∆𝑇+𝑈𝐿

ɳ𝑠 ∗𝐶𝑃𝑟𝑜𝑐𝑘 ∆𝑇∗𝜌𝑟𝑜𝑐𝑘

(3.6)

vi. The thickness of the rock storage material could be calculated from the collector area and volume of the rock; 𝑉 𝑍𝑠𝑚 = 𝑠 (3.7) 𝐴𝑐𝑜𝑙𝑙

3. 2. EVALUATION OF DEHYDRATED PRODUCTS QUALITY

Drying processes might affect the color and texture of fruits and vegetables. Fast drying leads to surface cracking, resulting in final rigid products with more volume and a crust on the surface. On the other hand, uniform and denser products with reduced re-hydration rate and capacity can be achieved with slow drying rates [23]. The quality of dehydrated product would be evaluated based on the sensory attributes of fruits and vegetables like color, texture and flavor. Texture can be considered an external reflection of micro and macro-structural characteristics of a food product that directly influences its sensory perceived features. Sensations as hardness, softness, crispness, juiciness, and toughness are considered as texture. Mechanical tests can be applied to quantify textural attributes of dried foods; dynamic tests, such as compression, relaxation and creep are the most used ones [23]. The visual appearance of raw, dry and rehydrated fruits and vegetables slices would be evaluated by eye inspection. 3. 3. MATHEMATICAL MODELING 3.3.1 Dryer cabinet To simulate the complete process of the drying, the whole components of the drying system should necessarily be modeled. Therefore, new dryer component is created using FORTRAN programing language to formulate the mathematical models. To develop the new component it is necessary to identify the parameters, inputs and outputs of the simulation, and their mathematical relationships are also described. Figure 3-1 shows the sectional view of the dryer component and the position of thermocouples.

10

Figure 3-1: Sectional view of the dryer cabinet

The energy balance equations for the drying chamber were written based on the following assumptions;      

Constant thermal properties of the products within the operating temperature Uniform thickness of the drying product Negligible volume shrinkage of the dried product No temperature gradient in the individual drying particle No variation of temperature and moisture along the thickness of the product The inner and outer wall temperatures of the dryer are assumed to be equal to the drying air and ambient temperature respectively.

The mathematical equations that are used to estimate the outputs of the simulation are described below. i. Drying air temperature (𝑇𝑎 ) The TOUT is the collector outlet temperature which is equal to air temperature entering the tray 1. The other drying air temperatures are calculated from the energy balance equations on each tray. Energy balance on tray 1 𝑚𝑎 ∗ 𝐶𝑃𝑎 (𝑇𝑂𝑈𝑇 − 𝑇𝐼𝑁 ) = 𝑚𝑎 ∗ 𝐶𝑃𝑎 (𝑇𝑎1 − 𝑇𝑎2 ) + ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑎1 − 𝑇𝑐1 )

(3.8)

Energy balance on tray 2 𝑚𝑎 ∗ 𝐶𝑃𝑎 (𝑇𝑎1 − 𝑇𝑎2 ) = 𝑚𝑎 ∗ 𝐶𝑃𝑎 (𝑇𝑎2 − 𝑇𝑎3 ) + ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑎2 − 𝑇𝑐2 )

(3.10)

𝑇𝑎2 = 𝑇𝐼𝑁 +

ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑎 ∗𝐶𝑃𝑎

𝑇𝑎3 = 𝑇𝑎2 �2 +

(𝑇𝑎1 − 𝑇𝑐1 )

ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑎 ∗𝐶𝑃𝑎

� − 𝑇𝑎1 −

ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑎 ∗𝐶𝑃𝑎

𝑇𝑐2

Energy balance on tray 3 𝑚𝑎 ∗ 𝐶𝑃𝑎 (𝑇𝑎2 − 𝑇𝑎3 ) = 𝑚𝑎 ∗ 𝐶𝑃𝑎 (𝑇𝑎3 − 𝑇𝑎4 ) + ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑎3 − 𝑇𝑐3 ) 𝑇𝑎4 = 𝑇𝑎3 �2 +

ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑎 ∗𝐶𝑃𝑎

� − 𝑇𝑎2 −

ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑎 ∗𝐶𝑃𝑎

𝑇𝑐3

11

(3.9)

(3.11) (3.12) (3.13)

ii. Crop temperature ((𝑇𝑐 ) The crop temperatures are also calculated from the energy balance equation on each tray as follow; Energy balance on tray 1 𝑑𝑇 ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑎1 − 𝑇𝑐1 ) = 𝑚𝑐 ∗ 𝐶𝑃𝑐 ∗ 𝑐1 + ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑐1 − 𝑇𝑎2 ) (3.14) 𝑑𝑡 Equating Eqn. (3.9) in to (3-14) and rearranging it to get the differential equation 𝑑𝑇𝑐1 + 𝐴1 𝑇𝑐 = 𝐹1 (𝑡) (3.15) 𝑑𝑡

Where; A1 =

𝐹1 (t) =

ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦

𝑚𝑐 ∗𝐶𝑃𝑐 ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑐 ∗𝐶𝑃𝑐

(2 +

ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦

)

𝑚𝑎 ∗𝐶𝑃𝑎 ℎ𝑐𝑓𝑐1 ∗ 𝐴𝑡𝑟𝑎𝑦

(𝑇𝑎1 �1 +

𝑚𝑎 ∗𝐶𝑃𝑎

� + 𝑇𝐼𝑁 )

Energy balance on tray 2 𝑑𝑇 ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑎2 − 𝑇𝑐2 ) = 𝑚𝑐 ∗ 𝐶𝑃𝑐 ∗ 𝑐2 + ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑐2 − 𝑇𝑎3 ) 𝑑𝑡 Equating Eqn. (3.11) in to (3-16) and rearranging it to get the differential equation dTc2 + A2 Tc = F2 (t) dt

Where; A2 = 𝐹2 (t) =

ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦

𝑚𝑐 ∗𝐶𝑃𝑐 ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑐 ∗𝐶𝑃𝑐

(2 +

ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦

)

𝑚𝑎 ∗𝐶𝑃𝑎 ℎ𝑐𝑓𝑐2 ∗ 𝐴𝑡𝑟𝑎𝑦

(𝑇𝑎2 �3 +

𝑚𝑎 ∗𝐶𝑃𝑎

Where; A3 =

𝐹3 (t) =

ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦

𝑚𝑐 ∗𝐶𝑃𝑐 ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦 𝑚𝑐 ∗𝐶𝑃𝑐

(2 +

ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦

)

𝑚𝑎 ∗𝐶𝑃𝑎 ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦

(𝑇𝑎3 �3 +

𝑚𝑎 ∗𝐶𝑃𝑎

(3.17)

� − 𝑇𝑎1 )

Energy balance on tray 3 𝑑𝑇 ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑎3 − 𝑇𝑐3 ) = 𝑚𝑐 ∗ 𝐶𝑃𝑐 ∗ 𝑐3 + ℎ𝑐𝑓𝑐3 ∗ 𝐴𝑡𝑟𝑎𝑦 (𝑇𝑐3 − 𝑇𝑎4 ) 𝑑𝑡 Equating Eqn. (3-13) in to (3-18) and rearranging it to get the differential equation 𝑑𝑇𝑐𝑟𝑜𝑝3 + 𝐴3 𝑇𝑐 = 𝐹3 (𝑡) 𝑑𝑡

(3.16)

(3.18) (3.19)

� − 𝑇𝑎2 )

iii. Moisture removed from the crop  The drying rate can be expressed as the thin layer drying equation; 𝑑𝑀 = −𝑘(𝑀𝑡 − 𝑀𝑒 ) (3.20) 𝑑𝑡  The moisture content on the dry basis (Mo) is the weight of moisture present in the product per unit weight of the dry matter in the product. 𝑊 −𝑊 𝑀𝑜 = 𝑜 𝑑 (3.21) 𝑊𝑑

 The instantaneous moisture content (Mt) at any time can be calculated from the following equation; (𝑀 +1)𝑊𝑡 𝑀𝑡 = � 𝑜 �−1 (3.22) 𝑊𝑜

 The instantaneous weight of crop (𝑊𝑡 ) could be calculated from the following equation; 𝑊𝑡 = 𝑊𝑜 − 𝑚𝑤𝑡 (3.23) 12

 The instantaneous mass of water (𝑚𝑤𝑡 ) would be calculated from the energy balance equation; 𝑚𝑐 ∗ 𝐶𝑃𝑐 ∆𝑇𝑐 = 𝑚𝑤𝑡 ∗ ℎ𝑓𝑔 (3.24) 𝑚𝑤𝑡 =

𝑚𝑐 ∗𝐶𝑃𝑐 ∆𝑇𝑐

(3.25)

ℎ𝑓𝑔

 The total mass of water to be removed from the crop (𝑚𝑤𝑓 ); 𝑀𝑜 −𝑀𝑓

𝑚𝑤𝑓 = 𝑊𝑜 (

1−𝑀𝑓

)

(3.26)

 The nocturnal moisture re-absorption or loss (Rn) is defined as the ratio of the rise in moisture content over the night period to the moisture content value at sunset of the preceding day, and expressed as a percentage. 𝑀 −𝑀 𝑅𝑛 = � 𝑠𝑟 𝑠𝑠 � 𝑥100% (3.27) 𝑀𝑠𝑠

 The daily drying efficiency (ɳd) is the ratio of the energy required to evaporate the moisture from the crop to the insolation received over the area of the air heater’s horizontal projection. (𝑊𝑜 ∗ℎ𝑓𝑔 )

�𝑀 +1 ⎡�𝑀𝑡−𝑀𝑓�∗ 𝑜 ⎤ ⎢ ⎥ ɳ𝑑 = ⎢ (3.28) ⎥ 𝑥100% 𝐼𝐴𝑡 ⎢ ⎥ ⎣ ⎦  Drying efficiencies (ɳn) to isolate the effect of the initial crop mass, the drying efficiencies are normalized against the total weight to obtain the corresponding ‘‘normalized’’ drying efficiencies.

ɳ𝑛 =

ɳ𝑑

𝑊𝑜

(%𝑘 −1 )

(3.29)

3.3.2 Energy storage solar collector component To simulate the existing solar dryer which was integrated with heat storage system using the pre-defined components in TRNSYS library may lead to error, because in the pre-defined components the energy from the collector to storage is transferred by convection from the flowing air. Whereas in this dryer, since both collector and storage components are stationary and there is no moving part in between, heat is transferred by conduction from the collector to the storage and vice versa. Therefore it was necessary to create new component in order to simulate the existing solar dryer system in TRNSYS. The new combined collector storage component was created in TRNSYS using FORTRAN programing language to formulate the mathematical models for the combined collector storage system. Like the dryer component the parameters, inputs and outputs of the simulation were identified in order to develop the new combined component, and their mathematical relationships were also described.

13

Figure 3-2: Sectional view of the solar collector and heat storage system

The mathematical equations used to determine the outputs of the component are derived from the energy balance equations on each part. According to S. Aboul-Enein et al [19] the outlet and average temperature of air from the collector and storage temperature are described as follow; The air temperature at the collector outlet; 𝐴𝑉𝑅𝑓4 (𝑡)) 𝑡 𝑏 𝑡 𝑇𝑂𝑈𝑇 = (( ) ∗ (1 − 𝐸𝑋𝑃(−(𝐿𝑝𝑙𝑎𝑡 + ( )) ∗ ( 2 ))) + 𝑇𝐼𝑁 ∗ 𝐸𝑋𝑃(−(𝐿𝑝𝑙𝑎𝑡 + ( )) ∗ 𝑏2

𝑏2

( )) 2

𝑎1

𝑎1

2

Average air temperature of the collector; 𝐴𝑉𝑅𝑓4 (𝑡))

𝑇𝐵𝐴𝑅 = (( 𝑇𝐼𝑁

𝑏2 ∗𝐿𝑝𝑙𝑎𝑡

𝑏2

𝐴𝑉𝑅�𝑓4 (𝑡)�

) + (2 ∗ (

) ∗ 𝐸𝑋𝑃(−

(𝑏2 ∗𝑡) 2∗𝑎1

)) ∗ 𝐸𝑋𝑃( −

𝐿𝑝𝑙𝑎𝑡 ∗𝑏22 −𝑏2 ∗𝐿𝑝𝑙𝑎𝑡

)(1𝐸𝑋𝑃(−

2

))

(𝑏2 ∗𝑡) 2∗𝑎1

−𝑏2 ∗𝐿𝑝𝑙𝑎𝑡

) ∗ (𝐸𝑋𝑃(

2

) − 1) + (2 ∗

The heat storage temperature; 𝐴𝑉𝑅𝑓5 (𝑡)) 𝑇𝑟𝑜𝑐𝑘 = ( ( ) ∗ (1 − 𝐸𝑋𝑃(−(𝑎2 ∗ 𝑡))) + 𝑇𝑟𝑜𝑐𝑘_𝑖𝑛𝑖 ∗ 𝐸𝑋𝑃(−(𝑎2 ∗ 𝑡)) 𝑎2

(3.30)

(3.31)

(3.32)

3.3.3 Weather data preparation The weather data of Mekelle for the year 2011 was obtained from Ethiopian Meteorology Agency, Mekelle station. The temperature, relative humidity, wind speed and sunshine hour recorded on daily basis are collected from the station. But the solar radiation was not recorded on this station, and the solar radiation measured at Mekelle University, main campus in the year 2011, 2012 and January 2013 was used for the simulation. The hourly weather data (like average solar intensity, temperature and humidity), design and operational parameters of the dryer and the properties of product are the input parameters for the analysis in TRNSYS. a. Temperature Since the collected weather data are not on hourly basis this data will not be directly used for the simulation in TRNSYS. Hence estimation of hourly dry-bulb temperature from the daily mean maximum and daily mean minimum temperatures will give a reasonable result. It is

14

then good assumption to take a sinusoidal variation of the dry-bulb temperature through the day. 𝑇 −𝑇 𝑡𝜋−9𝜋 𝑇(𝑡) = 𝑇𝑚𝑎𝑥 − ( 𝑚𝑎𝑥 𝑚𝑖𝑛 )[1 − sin( ) (3.33) 12

2

b. Relative humidity The relative humidity also assumed to vary sinusoidal with time, and the daily minimum and maximum relative humidity are used to estimate the hourly data with the following equation. 𝑅𝐻𝑚𝑎𝑥 −𝑅𝐻𝑚𝑖𝑛

𝑅𝐻(𝑡) = 𝑅𝐻𝑚𝑖𝑛 + (

2

)[1 − sin(

𝑡𝜋−9𝜋 12

)

(3.34)

c. Solar radiation and wind speed The solar intensity, wind speed and ambient air temperature data recorded at 10minute interval for the year 2012 January 2013 was collected from Mekelle University main campus Meteorology station. To prepare the hourly data as input for TRNSYS the 10minute average data was averaged in to hourly basis using Matlab and Excel soft wares. 3. 4. EXPERIMENTAL SETUP 3.4.1 Description of the solar dryer The schematic diagram of the solar dryer system which is shown in Figure 3-4 consists of the solar collector, the drying cabinet and the heat storage. The solar collector has a parallelepiped shape with dimension of 2 m length by 1 m width and 0.13 m gap between the absorber plate and glass, and consists of a 4 mm thick glass cover and corrugated iron sheet absorber plate with its upper surface painted black to increase the absorptivity of the system. The drying cabinet consists of three drying trays having a size of 0.92 m length by 0.64 m width and manufactured from plastic screen to prevent contamination, and also 0.80 m long chimney above the cabinet. The cabinet wall was well insulated by Styrofoam and the outer part was painted black to reduce heat loss through the walls. The heat storage material has 0.20 m thickness and placed directly under the absorber plate. The system was insulated from all sides and bottom by fiber glass to reduce the heat losses to ambient air. The drying air flows between the glass cover and absorber plate, where it gains thermal energy from the absorber plate, and then it flows through the chamber to the drying trays where it releases the heat to dry the product. Part of the heat energy from the absorber plate was stored in the heat storage material. Further, the solar collector was oriented to face south and tilted 15o with respect to the horizontal. The solar dryer was tested outdoors with and without heat storage to dry fruits and vegetables under the natural convection mode of operation. 3.4.2 Setup without heat storage The experimental setup for solar dryer without heat storage system was arranged to conduct the first experiment. Pyranometer, K-type thermocouples and thermometers arranged at different place of the dryer cabinet and solar collector shown in the Figure 3-3, were connected to National Instrument data logger.

15

Figure 3-3: Schematic view of Solar dryer without heat storage

3.4.3 Setup with heat storage To conduct an experiment with heat storage dryer the sensors were positioned as shown below in the Figure 3-4. The K-type thermocouples were used to measure the temperatures of various elements of the solar dryer as functions of time with the help of National Instrument data logger and Lab VIEW software. The ambient air temperature, the total solar radiation incident on the solar collector and wet bulb temperature at the dryer inlet and chimney outlet are measured.

16

Figure 3-4: Schematic view of solar dryer with rock storage

3.4.4 Experimental procedure The drying test experiment was conducted in two rounds, and the experiment in the first round was conducted to dry fruits and vegetables on solar dryer without heat storage, and in the second round experiment with heat storage. Before starting the experiment these fruits and vegetables were washed to remove dirt and prepared by peeling and slicing thinly, then to prevent oxidation that damage the flavor and vitamin content the slices were pretreated by blanching and dipping in to citric acid or ascorbic acid solutions. Every new experiment was started at 9:30AM, and the general procedure adopted for these experiments were; 1) First empty trays were weighted individually. 2) The treated slices were placed on the trays by giving space between slices as shown in Figure A-2(a). 3) The loaded trays were again weighted individually. 4) The loaded trays were placed in the drying chamber as shown in Figure A-2(b). 5) The thermocouples were positioned on the trays and connect all thermocouples with data logger which connected with computer as shown in Figure A-3, then configure and start logging data every second. 6) The solar radiation logging instrument METEON was programed by computer that have installed software METEON and start recording data every ten seconds because of low memory capacity of the instrument. 17

7) The wet bulb temperature data also collected at 10minute interval using the thermometers at the dryer inlet and chimney outlet. 8) The daily recorded data are exported in to excel format from the Lab VIEW software for analysis at 6:00PM. 9) To estimate daily drying rate by the weight loss of the product the loaded trays were weighted at the end of every day. 10) The experiment was performed until the desired final moisture of the product attains. 3.4.5 Instrumentations Drying experiments was conducted outdoor at Mekelle University main campus for the duration of 15 days for drying of selected sliced fruits and vegetables to study the effects of the climatic conditions, operational parameters and the heat storage system on the dryer performance. The instruments required to collect the data for experiment were; 1) Thermocouples The K-type thermocouples connected with data logger will be used to measure the dry bulb temperature at different locations of the solar collector, heat storage and the drying chamber during experiment.

Figure 3-5: K-type thermocouples

2) Pyranometer METEON irradiation meter type Pyranometer was used to measure the global solar radiation. The device displays an output reading in W/m2 which is the sum of the beam and diffused solar radiation. The sensitivity of the device is 71.00µV/W/m2. The total solar radiation was logged by METEON device on its memory and converts the data to computer using METEON software.

18

Figure 3-6: METEON Pyranometer

3) Data Logger The NIDAQ-9172 type data logger was used to record and store the different measurements made by thermocouples and it has 15 ports to measure temperatures including the ambient.

Figure 3-7: National Instrument data logger

4) Digital Weighing Balance PT-600 type digital weighing balance was used to weigh the drying product to determine the weight lost. 5) Thermometers Wet wicks laboratory bulb thermometers were used to measure the wet bulb temperature in the inlet and outlet of the solar dryer. The thermometers have ± 0.5oC accuracy. 19

Figure 3-8: Thermometer

6) Moisture Balance MB-200 OHAUS Model moisture balance instrument was used to determine the amount of moisture content in the product before and after drying. The instrument has a precision of + 0.007 in gram.

Figure 3-9: Moisture balance

7) Computer interface and analogue to digital converter The Lab VIEW Signal Express program software was used to convert the data collected by the data logger in to digital form for analysis.

20

4. RESULTS AND DISCUSSION 4.1

RESULTS OF HEAT STORAGE DESIGN

4.1.1 Heat storage rock selection A rock bed was used as solar energy storing material which can be integrated with the solar dryer to improve the performance. The rock bed was heated during the day directly from collector’s absorber and released the stored energy to the collector whenever there was a temperature difference between the absorber plate and storage material. The geological map profile of the rock types around Mekelle city was found from Mekelle University, Geology Department [24]. The identified rock types were; 1. Limestone 2. Sandstone 3. Dolerite 4. Gypsum 5. Marl 6. Shale Since no experiments was done by the department to identify the thermal properties of these rocks, the thermo-physical properties (conductivity, density and specific heat capacity) were found from literatures. Based on their thermo-physical properties, availabilities and accessibilities the sandstone was selected as sensible heat storage material for this research work. For better temperature distribution along the storage volume the rock bed was prepared from sandstone having dimension 2 – 4 cm. The Thermo- physical properties of different rock types identified around Mekelle area are summarized below in Table 4-1. Table 4-1: Thermo-Physical properties of Rocks for sensible heat storage[25] Rock Type

Density [ρ] kg/m3

Specific heat [Cp] J/kg. K

Limestone Sandstone

2500 2350

900 775

Volumetric Heat Capacity (ρ Cp)x10-6J/m3.K

2.25 1.821

Thermal conductivity [k] W/m. K

1.26 – 1.33 1.83

Thermal Diffusivity [α], (k/ρ Cp)x106 m2/s

0.56-0.59 1.01

4.1.2 Heat storage volume and thickness calculations i. The amount of water need to be removed from 10kg of tomatoes was calculated from Eqn. (3-1). 10(0.92−0.15) 𝑚𝑤𝑓 = 1−0.15 𝑚𝑤𝑓 = 9.1𝑘𝑔 ii. The total energy required by the air to evaporate 9.1kg of water from the tomatoes was calculated using Eqn. (3-2) and (3-3). ℎ𝑓𝑔 = 2537𝐾𝐽/𝑘𝑔 𝑚𝑎 ∗ 𝐶𝑃𝑎 ∆𝑇 = 9.1𝑘𝑔 ∗ 2537𝐾𝐽/𝑘𝑔 21

𝑚𝑎 ∗ 𝐶𝑃𝑎 ∆𝑇 = 23093.98𝐾𝐽 iii. Fiber glass was used as insulation material. Its thermal conductivity, the bottom and side thickness were 0.0519W/m. K, 0.03m and 0.025m respectively. The total heat loss (UL ) was calculated from Eqn. (3-4). 𝑈𝐿 = 1.73 + 2.076 𝑈𝐿 = 3.806 𝑊/𝐾 The energy equivalent to 3.806W power in 24hr operation was about 328.84KJ. iv. The volume of the storage material was calculated using Eqn. (3-5) and (3-6). 23093.98+328.84

𝑉𝑠 = 0.7∗1821∗20 𝑉𝑠 = 0.91 𝑚3 v. The thickness of the rock storage material was determined from Eqn. (3-7). 0.91 𝑍𝑠𝑚 = 2 𝑍𝑠𝑚 = 0.459 𝑚 Since most of the crop moisture would be evaporated during day time directly by the solar energy the optimized thickness of the storage was taken as 40% of calculated bed thickness. 𝑍𝑠𝑚 = 0.20 𝑚

4.2

RESULTS OF MATHEMATICAL MODELINGS

4.2.1 Component creating and FORTRAN programing flow chart To study the solar dryer performance using transient analysis the dryer component proforma was created from TRNSYS simulation studio. The input, output and the parameter variables needed for this component were properly declared. The new component proforma was saved on “%TRNSYS%\studio\proformas” in order to be accessed for simulation and exported as FORTRAN to Microsoft visual studio (MsVS) which integrated with Intel(R) Visual FORTRAN compiler to create the dynamic link library (DLL). Figure 4-1 shows the flow chart how the proforma of new component is created in TRNSYS studio. The FORTRAN programing flow chart used to create the new component is shown on Figure 4-2. Open TRNSYS studio Declaring Type number Create new component proforma

Declaring variables  Inputs  Parameters  output

Save proforma “%TRNSYS%\studio\proformas”

Export proforma as FORTRAN

Figure 4-1: New component proforma creating flow chart

22

Open MsVS

1. 2. 3.

Describing variables Declaring output’s initial values Writing formulas (Output= Input + Parameter)

  

Yes

SOURCE FILE

Configure to release Build Compile

DLL

Compile-time error

No Use TRNS solver

Yes

Object File

Any run-time error

No Done

Figure 4-2: Flow chart of FORTRAN programing

4.2.2 FORTRAN programing of the mathematical modeling Once the proforma is exported in can be opened on Microsoft visual studio and become ready to write the mathematical modeling equations needed to the component. The inputs required by the component were the weather data (temperature, solar radiation, wind speed and relative humidity) of Mekelle prepared on hourly basis. The outputs were the combination of the parameters and inputs variables. The inputs and parameters were arranged according to the formulas described in methodology part from Eqn. (3-20) to (3-29) to predict the outputs of the component. The mathematical modeling equations needed to the component were written using the FORTRAN programing language on Microsoft visual studio FORTRAN compiler environment as shown on Figure A-7. Since the TRNSYS studio requires the release configuration the new component was configured to release, then build and compile the dynamic link library (DLL). The component used the TRNS solver from the TRNSYS library 23

to solve the mathematical equations described by the component. The full FORTRAN programing code used to develop the new component is attached on Appendix 1.

4.3 TRNSYS SIMULATION AND RESULTS Once the mathematical equations were written properly and imported to TRNSYS the simulation project were created by selecting the component required for complete system.

Figure 4-3: Creating TRNSYS project for simulation

For this simulation purpose the weather, collector and the new dryer Type 214 components were selected and connected as shown on Figure 4-3. The weather component output was connected with the collector input and the collector output is connected with the dryer component input, since the dryer need the weather data the some of the dryer inputs were connected with the weather component, the step to create new TRNSYS project is shown in Appendix 3-(b).

24

Figure 4-4 Moisture content and weight loss of tomato with time

Figure 4-5 Heat gain and drying air predictions

The simulation result shown in Figure 4-4 one can observe that drying of tomatoes slices on the rainy season takes about four days to reach the desired dried moisture content of the slices dried with dryer integrated with heat storage system.

25

4.4 EXPERIMENTAL RESULTS AND DISCUSSION The new solar dryer was constructed with some modifications on the system. Experiment was conducted to analyze the performance of the dryer. To evaluate the performance of the storage system, experiment was conducted on a dryer without storage and a dried with a storage system integrated. The results obtained from both cases will be present follows. 4.4.1 Drying with dryer without heat storage A. Mangoes Slices Drying The first drying experiment was conducted for 3days. The mangoes slices were prepared from 10kg of mango fruit with uniform pattern and size. From 10kg of mango fruit 4.41 kg of slices were prepared. To analyze the effect of pretreatment on the quality of dried product, half of the slices were pre-treated by using citric acid solution in warm water for 4 – 5 minutes. The prepared slices were laid on thin layer on each of the three drying trays made from plastic screen to prevent contamination as shown in Figure A-2(a). The pre-treated slices were laid on the first tray and the untreated slices were placed on the other two trays. The trays were placed on the dryer cabinet and connected with the thermocouples. The dryer cabinet door was closed during data logging. During the test the initial moisture content of mango slices was determined using moisture balance instrument. This typical mango variety presented an initial moisture content of 87%. The required final moisture content was 13%. The amount of moisture to be removed was calculated using Eqn. (3-20), and 3.742 kg of moisture needed be removed from the mango slices. i. Drying Air Temperature and Solar Radiation Distribution Figure 4- 6 to 4-8 show drying air temperature from collector outlet and on the drying trays, absorber plate temperature, ambient air temperature and solar radiation intensity from the mango slice drying experiment.

26

1200

90 80 70 60 50 40 30 20 10 0

1000 800 600 400 200 11:00

12:00

13:00

14:00

15:00

16:00

0

Global Radiation (W/m2)

Temperature (oC)

Temperature and Solar Radiation Distribution

Time (hr) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Radation

Figure 4-6: Day 1 drying air temperature and solar radiation distribution

80

Temperature (oC)

70 60 50 40 30 20 10 0

09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

1000 900 800 700 600 500 400 300 200 100 0

Global Radiation (W/m2)

Temprature and Solar radiation distribution

Time (hr) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Figure 4-7: Day 2 dryinf air temperature and solar radiation distribution

27

Radation

90 80 70 60 50 40 30 20 10 0

10:00

11:00

12:00

13:00

14:00

Global Radiation (W/m2)

Temperature (oC)

Temperature and solar radiation distribution 1000 900 800 700 600 500 400 300 200 100 0

Time (hr) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Radation

Figure 4-8: Day 3 drying air temperature and solar radiation distribution

From the graphs of drying air temperature and solar radiation distribution results on Figure 46 to 4-8, the maximum of 67.8oC average drying air temperature from the collector outlet was obtained on day 2 at average solar radiation of 872W/m2. On the same day good drying air temperature was achieved for relatively longer time than day 1 and 3. This was due to longer sunshine hour on that day.

Weight (grams)

ii. Instantaneous Weight Loss of Mangoes Slices Figure 4-9 summarizes the instantaneous weight loss of mangoes slices resulted from the experiment on day 1, 2 and 3.

5000 4500 4000 3500 3000 2500 2000 1500 1000 500 0

Weight loss of mango slices

Day 1 Day 2 Day 3

09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Time (hr) Figure 4-9: Instantaneous weight loss of mangoe slices for three drying days

28

The instantaneous weight loss of the mangoes slices summarized result graphs on Figure 4-9 shows that most of the moisture content of mangoes slices about 2221.98 g was removed on day 2, and also the weight of the slices at the end day 1 and 2 was lower that the weight of the slices at the beginning of day 2 and 3 respectively. These overlaps of the graphs clearly show there was moisture re-absorption. iii. Useful Heat Gain of the Solar Collector Figure 4-10 presents the hourly useful heat gain obtained from the collector on days 1 to 3. Useful heat gain of the collector

Heat gain (W)

350 300

Day 1 Day 2 Day 3

250 200 150 100 50 0

09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Time (hr) Figure 4-10: Useful heat gain of the solar collector

The graphs on Figure 4-10 shows that 227.39 , 328.09 and 315.8W maximum average hourly useful heat gain of the solar collector was obtained around mid-day for days 1, 2 and 3 respectively. iv. Nocturnal Moisture Re-absorption or Loss of Mangoes Slices Moisture re-absorption or loss of the slices at the second day was calculated from the weight differences between the end of the first day and the beginning of the second day. The weight of the slice at the first day was 3193.95 g and at beginning of the next day the weight of slice was 3328.17 g. Therefore, the nocturnal moisture re-absorption of the slices was calculated using Eqn. (3-21); 3328.17 − 3193.95 𝑅𝑛 = ∗ 100% 3193.95 𝑅𝑛 = 4.2% The nocturnal moisture re-absorption or loss from the second to the third day was also calculated in the same way. The weight at the end of the second day 1106.02 g and at the beginning of the third day was 1166.527g. 1166.527 − 1106.02 𝑅𝑛 = ∗ 100% 1106.02 𝑅𝑛 = 5.47% Since the nocturnal moisture calculation results have positive values the mango slices had moisture re-absorption of 4.2% and 5.47% during the first and second nights respectively. 29

v. Daily Drying Efficiency The daily drying efficiency of the dryer is calculated from Eqns. 3-15, 3-19 and 3-22. Figure 4-11 shows the daily efficiency of the solar dryer system.

Efficiency

0.3

Daily Drying efficiency

0.2

Daily efficiency

0.1 0

1

2 3 Time (Day) Figure 4-11: Daily mango drying efficiency of the system And from Figure 4-11 graph it is clearly seen that maximum of 27.4% daily drying efficiency of the system was obtained on day 3 for drying mangoes slices. The lower average daily solar radiation and longer drying time at lower solar radiation were the reasons for lower daily drying efficiency of the system on day 2 than day 3. B. Tomatoes Slices Drying Drying tomatoes slices experiment was conducted for 3 days. Like the mangoes slices the tomatoes slices were prepared from 10 kg of tomato in uniform pattern and size. The tomatoes slices were prepared first boiling the tomatoes by water in order to remove the skin and cut in to half to remove the seeds and uniform pattern thin slices were made as shown in the Figure A- 1(b). 3.56 kg of tomatoes slices were prepared. Out of this, to analyze the effect of pre-treatment on the quality of dried tomato half of the prepared slice was pre-treated by using ascorbic acid solution in cold water for 10 minutes. The pre-treated slices were laid on the first tray and the untreated slices were equally laid on each of the other two trays. The trays were placed on the dryer cabinet and connected with thermocouples. The dryer cabinet door was closed and data logging was started. The initial moisture content of tomato was measured using the moisture balance instrument and this typical tomato variety presented 95% initial moisture content. The required final moisture content is 13%. The amount of water to be removed was calculated using Eqn. (3-20), and 3.357 kg of water needed be removed from the tomatoes slices. i. Drying Air Temperature and Solar Radiation Distribution Figure 4-12 to 4-14 show the distribution of solar radiation intensity, absorber plate temperature, ambient air temperatures and drying air temperature from the collector outlet and on drying trays.

30

Temperature (oC)

1200 1000

80

800

60

600

40

400

20

200 0

0

Tplate

Tout

Time (min)

Tray 1

Tray 2

Tray 3

Tamb

Global Radiation (W/m2)

Temperature and Solar Radiation Distribution

100

Radation

100 90 80 70 60 50 40 30 20 10 0

Temperature and Solar Radiation Distribution

1200 1000 800 600 400 200

Global Radiation (W/m2)

Temperature (oC)

Figure 4-12: Day 1 tomato drying air temperature and solar radiation distribution

0

Time (min) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Radation

Figure 4-13: Day 2 tomato drying air temperature and solar radiation distribution

31

Temperature and Solar radiation distribution 90

1000

Temperature (oC)

80 70

800

60

600

50 40

400

30 20

200

0

10:00 10:10 10:20 10:30 10:40 10:50 11:00 11:10 11:20 11:30 11:40 11:50 12:00 12:10 12:20 12:30 12:40 12:50 13:00 13:10 13:20 13:30 13:40 13:50

10

Global radiation (W/m2)

1200

100

0

Time(min) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Radation

Figure 4-14: Day 3 tomato drying air temperature and solar radiation distribution

The linear line fitted to the collector outlet temperatures on the drying air temperature and solar radiation distribution graphs on Figure 4-12 to 4-14 show the average drying air temperature of 51.5, 49.8 and 49.9oC was obtained on days 1, 2 and 3 respectively. It is also shows more than half of the collector outlet temperature on day 1 drying is above the average temperature. ii. Instantaneous Weight Loss of Tomatoes Slices Figure 4-15 shows the instantaneous weight loss of the tomatoes slices resulted from experiments on days 1, 2 and 3.

32

Weight loss of tomatoes slices

4000

Weight (grams)

3500 3000 2500

Day 1 Day 2 Day 3

2000 1500 1000 500 0

Time (min) Figure 4-15: Instantaneous weight loss of tomato slices for the three drying days

The instantaneous weight loss of the tomatoes slices graphs on Figure 4-15 shows most of the moisture content of the tomatoes slices was removed during the first drying day and it was about 2242.22 g. From the daily weight of tomato slices it is clearly seen that there was an overlap at the end of day 1 and 2 and at the beginning of day 2 and 3. iii. Useful Heat Gain of the Solar Collector The instantaneous useful heat gain results of the solar collector during the experiment days of drying tomatoes slices were summarized in Figure 4-16.

Heat Gain (W)

Useful heat gain of the collector 350 300 250 200 150 100 50 0

Time (min) Day 1

Day 2

Day 3

Figure 4-16: Useful heat gain of the solar collector

33

Figure 4-22 shows that the average useful heat gain of 210.7, 128.14 and 139.62W were obtained by collector on days 1, 2 and 3 respectively. This variation of useful heat gain was mainly due to fluctuation of solar radiation intensity on these days. iv. Nocturnal Moisture Re-absorption or Loss of Tomatoes Slices Moisture re-absorption or loss of the slices at the second day was calculated from the weight differences between the end of the first day and the beginning of the second day. The weight of the slice at the first day was 1283.67 g and at beginning of the other day the weight of slice was 1412.54 g. Therefore, the nocturnal moisture re-absorption the tomato slices was calculated using Eqn. (3-21); 1412.54 − 1283.67 𝑅𝑛 = ∗ 100% 1283.67 𝑅𝑛 = 10.04% The nocturnal moisture re-absorption or loss from the second to the third day was also calculated in the same way. The weight at the end of the second day was 551.84 g and at the beginning of the third day was 575.78 g. 575.78 − 551.84 𝑅𝑛 = ∗ 100% 551.84 𝑅𝑛 = 4.34% The nocturnal moisture calculation results have positive values, and these result shows that the tomato slices had moisture re-absorption of 10.04% and 4.34% respectively during day 1 and 2 nights. Daily Drying Efficiency

Efficiency

v.

0.25 0.2 0.15 0.1 0.05 0

Daily drying efficiency Daily efficiency

1

2 Time (day)

3

Figure 4-17: Daily drying efficiency of the solar dryer system

As shown on the Figure 4-17 daily drying efficiency graph the maximum efficiency of the system 19.33% was obtained on day 1. 4.4.2 Drying with heat storage integrated dryer To conduct the second phase of the experiment, the solar dryer used for the first phase experiment was rebuild by integrating heat storage rock system with the collector as shown in the Figure A-4. The new system also arranged for experiment by connecting with Pyranometer and thermocouples at different place of the dryer cabinet, solar collector and 34

heat storage system. The global radiation and temperature distribution were measured during the drying. A. Tomatoes slices drying Drying tomatoes slices with dryer integrated with rock bed was conducted for two days. The tomatoes slices were prepared with the same method used for the first phase experiment. 3.4 kg of tomatoes slices were prepared from 10kg of tomato. To evaluate the effect of pretreatment on the quality of dried tomato one third of the prepared slice was pre-treated by using ascorbic acid solution in cold water for 10 minutes. The pre-treated slices were laid on the first tray and the untreated slices were equally laid on each of the other two trays. The trays were placed on the dryer cabinet and connected with thermocouples. The dryer cabinet door was closed during data logging. The initial moisture content of tomato was measured using the moisture balance instrument. This typical tomato variety used for this experiment presented 94% initial moisture content. The required final moisture content of dry tomato was 13%. The amount of moisture to be removed from the tomato slices was calculated using Eqn. (3-20), and 3.166 kg of moisture needed be removed. i. Drying air temperature and solar radiation distribution Figure 4-18 and 4-19 summarizes the results of the solar radiation intensity, drying air temperature from the collector outlet and on each drying trays distribution, absorber plate and ambient air temperatures for drying experiment on day 1 and 2.

80

900

70

800

60

700 600

50

500

40

400

30

300

20

200

10 0

100 10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

Global Radiation (W/m2)

Temperature (oC)

Temperature and Solar Radiation Distribution

0

Time (hr) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Radation

Figure 4-18: Day 1 tomato drying air temperature and solar radiation distribution

35

Temperature and Solar Radiation Distribution

900

70

800

60

700 600

50

500

40

400

30

300

20

200

10

100

0

10:00

11:00

12:00

13:00

14:00

15:00

16:00

Global Radiation (W/m2)

Temperature (oC)

80

0

Time (hr) Tplate

Tout

Tray 1

Tray 2

Tray 3

Tamb

Radation

Figure 4-19: Day 2 tomato drying air temperature and solar radiation distribution

The linear fitted curve to the collector outlet temperatures on the drying air temperature and solar radiation distribution graphs on Figure 4-18, and 4-19 show the maximum average drying air temperature of 42.86 and 48.26oC was obtained on days 1 and 2 respectively. The linear fit line also shows most of the drying air temperature distributions were above the line on day 1. ii. Heat Storage Temperature Distribution Figure 4-20 and 4-21 show the summarized graphs of heat storage, absorber plate, collector outlet and ambient air temperature distributions.

Temperature (oC)

Temperature Vs Time Distribution 80 70 60 50 40 30 20 10 0

Tplate Trock Tout Tamb 10:0011:0012:0013:0014:0015:0016:0017:00

Time (hr) Figure 4-20: Day 1 heat storage and collector temperatures distribution

36

Temperature Vs Time Distribution Temperature (oC)

70 60

Tplate

50

Trock

40 30

Tout

20

Tamb

10 0

10:00 11:00 12:00 13:00 14:00 15:00 16:00

Time (hr) Figure 4-21: Day 2 heat storage and collector temperatures distribution

The heat storage rock temperature distributions are clearly shown by the graphs on Figure 420 and 4-21. From these graphs it is possible to see that the maximum temperature achieved by the heat storage rock was 35oC on day 1 and 2. Since the available solar radiation duration was limited due to bad weather the storage could not able to store sufficient energy.

Weight (grams)

iii. Instantaneous Weight Loss of Tomatoes Slices Figure 4-22 shows the tomatoes slices instantaneous weight loss with time during the drying experiment on days 1 and 2. 4000 3500 3000 2500 2000 1500 1000 500 0

Tomato Weight Loss With Time

Day 1 Day 2

10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Time (hr) Figure 4-22: Instantaneous weight loss of tomatoes’ slices for two days drying

The instantaneous weight loss of the tomatoes slices graphs on Figure 4-22 shows most of the moisture content of the tomatoes slices was removed during the first drying day and it was about 1994.18 g. The daily weight loss graphs of tomato slices had shown some overlap at the end of the first day and beginning of the second day. Which means the moisture content of the tomato slices at the beginning of the second day was slightly higher than the moisture content of the slices at the end of previous day. 37

iv. Useful Heat Gain of the Solar Collector The graphs on Figure 4-23 and 4-24 describe the hourly useful heat gain of the solar collector and solar radiation intensity measured from the experiment.

y = 7.035x + 104.59

1000 800 600 400 200

10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

0

Time (hr) Qcoll

Radation

Global Radiation (W/m2)

Heat Gain (W)

Useful Heat Gain and Solar Radiation Distributio

350 300 250 200 150 100 50 0

Linear (Qcoll )

Figure 4-23: Useful heat gain of the collector at the first drying day

180 160 140 120 100 80 60 40 20 0

900

y = -3.464x + 120.78 800

10:00 11:00 12:00 13:00 14:00 15:00 16:00

700 600 500 400 300 200 100 0

Global Radiation (W/m2)

Heat Transfer (W)

Useful Heat Gain and Solar Radiarion Distribution

Time (hr) Qcoll

Radation

Linear (Qcoll )

Figure 4-24: Useful heat gain of the collector for the second drying day

From Figure 4-23 and 4-24 graphs linear fit lines shows minimum average useful heat gain of 104.59W on day 1 and 120.78W maximum average useful heat gain on day 2. v. Nocturnal Moisture Re-Absorption or Loss of Tomatoes Slices Moisture re-absorption or loss of the slices at the second day was calculated from the weight differences between the end of the first day and the beginning of the second day. The weight of the slice at the first day was 1343.15 g and at beginning of the next day the weight of slice was 1452.65 g. The nocturnal moisture re-absorption of tomato slices was calculated using Eqn. (3-21);

38

1452. .65 − 1343.15 ∗ 100% 1343.15 𝑅𝑛 = 8.15%

𝑅𝑛 =

The positive values of nocturnal moisture calculation result shows that the tomato slices had moisture re-absorption of 8.15% at night. The maximum daily drying efficiency of the system was 21.55% during the first day. B. Mangoes Slices Drying The mangoes slices for the experiment were prepared from 10 kg of mango fruit in the same method of preparation as the first phase experiment, and 3.91 kg of mangoes slices were prepared. To examine the effect of pre-treatment on the quality of dried product, one third of the prepared slices were pre-treated using citric acid solution in warmed water for 5 minutes, and laid on the trays for thin layer drying. The trays were placed on the dryer cabinet and connected with thermocouples. The dryer cabinet door was closed during data logging. The initial moisture content of mango slice was determined using moisture balance instrument. This typical mango fruit variety used for this experiment presented an initial moisture content of 85.7%. The required final moisture content was 13%. The amount of moisture to be removed was calculated using Eqn. (3-20), and 3.267 kg of moisture needed be removed from the slices.

90 80 70 60 50 40 30 20 10 0

Temperature and solar radiation distribution

1000 900 800 y = -0.6775x + 55.405 700 600 500 400 300 200 100 0

Global Radiation (W/m2)

Temperature (oC)

i. Drying Air Temperature and Solar Radiation Distribution The intensity of global radiation, drying air temperature from the collector outlet and drying trays, absorber plate temperature and ambient air temperature measured from day 1, 2 and 3 experiment were summarized in Figure 4-25 to 4-27 respectively.

Time (min) Tplate Tray 3

Tout Tamb

Tray 1 Radation

Tray 2 Linear (Tout)

Figure 4-25: Day 1 mango drying air temperature and solar radiation distributions

39

Temperature and solar radiation distribution 90

Temperature (oC)

80

1000

70 60

800

50

600

40 30

400

20

y = 1.4417x + 38.164

10 0

200

Global Radiation (W/m2)

1200

0

09:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00

Time (min) Tplate Tray 3

Tout Tamb

Tray 1 Radation

Tray 2 Linear (Tout)

Figure 4-26: Day 2 mango drying air temperature and solar radiation distributions

Temprature and solar radiation distribution

1200

Temperature (oC)

80

1000

70

800

60

y = -1.922x + 56.908

50

600

40 30

400

20

200

10 0

10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00

Global Radiation (Wm2)

90

0

Time (min) Tplate Tray 3

Tout Tamb

Tray 1 Radation

Tray 2 Linear (Tout)

Figure 4-27: Day 3 mango drying air temperature and solar radiation distributions

The graphs of drying air temperature and solar radiation distribution results on Figure 4-25 to 4-27, the maximum of 58 and 59 oC average drying air temperature from the collector outlet were obtained on day 1 and 3. The linear fit curve to the collector outlet temperature on day 1 and 3 shows most of the collector outlet temperatures were above the line, and this means on these days better drying air temperature was achieved for relatively longer time.

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ii. Heat Storage Temperature Distribution The graphs of the following three figures show the absorber plate, collector outlet, heat storage and ambient air temperatures distribution.

90 80 70 60 50 40 30 20 10 0

Tplate Trock Tout Tamb 10:40 10:50 11:00 11:10 11:30 11:40 11:50 12:00 12:10 12:20 12:30 12:40 12:50 13:00

Temperature (oC)

Temperature Vs Time Distribution

Time (hr) Figure 4-28: Day 1 heat storage and collector temperatures distribution

Temperature (oC)

Temperature Vs Time Distribution 90 80 70 60 50 40 30 20 10 0

Tplate Trock Tout Tamb

Time (hr) Figure 4-29: Day 2 heat storage and collector temperatures distribution

41

Temperature (oC)

Temperature Vs Time Distribution 90 80 70 60 50 40 30 20 10 0

Tplate Trock Tout Tamb

Time (hr) Figure 4-30: Day 3 heat storage and collector temperatures distribution

The heat storage rock temperature distributions shown on Figure 4-28 to 4-30, the maximum possible temperature of the heat storage achieved on day 1, 2 and 3 were 34.6 oC, 38 oC and 38 oC respectively. These temperatures of the storage were not sufficient to the dryer to work at night.

4500 4000 3500 3000 2500 2000 1500 1000 500 0

Weight loss of mangoes slices

Day 1 10:40 10:50 11:00 11:10 11:30 11:40 11:50 12:00 12:10 12:20 12:30 12:40 12:50 13:00

Weight (grams)

iii. Instantaneous Weight Loss of Mangoes Slices Figure 4-31 shows the weight loss of the mangoes slices versus time on day 1 and the other two days day 2 and 3 weight loss was summarized by the graph in Figure 4-32.

Time (min) Figure 4-31: Instantaneous weight loss of mangoes slices on the first day

42

Weight loss of mangoes slices

Day 2 Day 3 09:00 09:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30

Weight (grams)

3500 3000 2500 2000 1500 1000 500 0

Time (min) Figure 4-32: Instantaneous weight loss of mangoes slices on day 2 and 3

The instantaneous weight loss of the mangoes slices graphs on Figure 4-31 and 4-32 shows that the daily maximum of 1415.5 g and 1021 g of the moisture content of mangoes slices were removed on day 2 and 3. The daily weight loss graphs of mango slices have shown some overlap. Which means the moisture content of the tomato slices at the beginning of the day 2 and 3 were slightly higher than the moisture of the slices at the end of day 1 and 2.

200 180 160 140 120 100 80 60 40 20 0

Useful heat gain and solar radiation distribution

1000 900 800 700 600 500 400 300 200 100 0

Global radiation (W/m2)

Heat Transfer (W)

iv. Useful Heat Gain of the Solar Collector Figure 4-33 and 4-34 show the instantaneous useful heat gain distribution of the collector and solar radiation intensity measured during the drying.

Time (min) Qcoll

Radation

Figure 4-33: Useful heat gain of the collector during the first day

43

Useful heat gain distribution Heat Transfer (W)

400 350 300 250 200

Day 2

150

Day 3

100 50 0

Time (min) Figure 4-34: Useful heat gain of the collector for the 2nd and 3rd days

From Figure 4-33 the maximum hourly useful heat gain of the collector 183.7W was obtained before noon and after noon on day 1 drying. Figure 4-34 shows the maximum hourly useful heat gain of 347W was obtained at mid-day on day 2. v. Nocturnal Moisture Re-absorption or Loss of Mangoes Slices Moisture re-absorption or loss of the slices at the second day was calculated from the weight differences between the end of the first day and the beginning of the second day. The weight of the slice at end of the first day was 3054.38 g and at beginning of the next day the weight of slice was 2946.24 g. The nocturnal moisture re-absorption of mango slices was calculated using Eqn. (3-21); 3054.38 − 2946.24 ∗ 100% 𝑅𝑛 = 2946.24 𝑅𝑛 = 3.67% The nocturnal moisture re-absorption or loss from the second to the third day was also calculated in the same way. The weight at the end of the second day 1662.64 g and at the beginning of the third day was 1638.52 g. 1662.64 − 1638.52 𝑅𝑛 = ∗ 100% 1638.52 𝑅𝑛 = 1.47% Since the nocturnal moisture content calculation results have positive values, the mango slices were exposed moisture re-absorption of 3.67% and 1.47% during the first and second nights respectively.

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vi. Daily Drying Efficiency Daily drying efficiency

Efficiency

0.3 0.2

Daily efficiency

0.1 0

1

2 Time (day)

3

Figure 4-35: Daily drying efficiency of the solar dryer system

Figure 4-35 shows the daily drying efficiency of the system. The maximum daily drying efficiency of the system was 21.9, 19 and 24.7 % on days 1, 2 and 3.

4.5

COMPARING THE DRYER PERFORMANCE AND PRODUCT QUALITY

4.3.1. Dryer performance comparison Since the performances of the dryers were tested at season that have lower sunshine hour duration the performance of the dryers were compared by considering the worst cases scenario. The average performance of the solar dryer system without heat storage material for drying mango slices was 27.4 % and for tomato slices was 19.33 %. Even if the drying efficiency of the system for drying tomato slices was lower than mango slices, the drying time for tomato was less than mango. The daily drying performances of the solar dryer integrated with heat storage system for drying tomato slices was 21.55 % and drying of mango slices was 24.7 %. Here also the tomato drying time was less than the mango drying time. The performance of the dryer with heat storage for drying tomato slices slightly increases than without heat storage system. The performance of the dryer without heat storage for drying mango slices was better than dryer with heat storage system. Even if the bad weather condition affects both types of dryer but the performance of the dryer with heat storage system was affected more. Since there was lower global radiation intensity and shorter hour sunshine duration during this season the collector doesn’t get sufficient energy to store rather than drying. 4.3.2. Product quality comparison Pre-treatment of fruits and vegetables using pre-treatment chemicals helps them not to undertake oxidation process with oxygen which leads them to color change. Figure 4-36 and 4-37 shows the pre-treated and untreated dried mango slices with and without heat storage dryer respectively. The products labeled 1 are pre-treated and those labeled 2 are untreated mangoes slices. And from the figures it is clear that the natural color of the untreated dried products is changed on both drying methods. The color quality of both pre-treated and untreated dried products have also slight quality difference with and without heat storage dried products as shown in Figure 4-36 and 4-37. 45

2

1

Figure 4-36: Dried mangoes slices by dryer with heat storage system.

1

2

Figure 4-37: Dried mangoes slices by dryer without heat storage system

1

2

Figure 4-38: Dried tomatoes slices by dryer with heat storage system

1

2

Figure 4-39: Dried tomatoes slices by dryer without heat storage system

46

Figure 4-38 and 4-39 shows the pre-treated and untreated dried tomato slices respectively. The products labeled 1 are pre-treated and those labeled 2 are untreated tomatoes slices. From these figures one can easily observe that the natural color of the untreated dried product is changed on both drying methods. The color quality of both pre-treated and untreated dried products have also slight quality difference with and without heat storage dried products as shown in Figure 4-38 and 4-39. The products textural quality also checked by mechanical crushing, and both pre-treated and untreated products of mango and tomato have the same quality.

4.6

SUMMARY

Due to the rain and cloud cover it was not possible to get consistent drying time with good solar radiation. This fluctuation of solar radiation availability affects the dryer performance, and it was the main reason for the dryer daily drying efficiency difference for drying the same product. Since the dryers were not able to operate with their full potential, comparison of these two types dryer performance was difficult. But it is clearly seen that the quality of product dried with dryer with heat storage system have better quality in terms color quality. Even if tomato has slightly more moisture content than mango, the experimental results show that the drying time of tomato was lower than the drying time required to mango. From the result of product quality comparison, it is possible to see the color quality of dried fruits and vegetables can be maintained by applying pre-treatment.

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5. CONCLUSION AND RECOMMENDATIONS 5.1.

CONCLUSION

The Natural convection indirect solar dryer manufactured without heat storage system has maximum drying air temperature of 63-68 oC during peak solar radiation, and the daily drying efficiency of 19 %. The solar dryer with rock bed heat storage system integrated with the collector can have a maximum drying air temperature of 55-58 oC at peak solar radiation. This is the preferable drying air temperature for fruits and vegetables drying. The daily drying efficiency of the system is 21 %. The heat storage system temperature gradually increases from ambient temperature and attains temperature of 38 oC. Since the temperature of the heat storage system decreases gradually, it can keep the minimum drying air temperature variation at high and low radiations. This helps to maintain the product quality as well. The pre-treated or untreated product dried without heat storage dryer has less quality than dried with heat storage dryer. Pre-treated dried fruits and vegetables have better quality in terms of color and it is more similar to the raw fruits and vegetables color. 5.2. RECOMMENDATIONS The following areas of interest can be looked to extend the research work on natural convection solar dryers. Since the new created solar dryer is the first version it can be upgrade by considering additional parametric to integrate with psychometric chart in addition to the mathematical manipulation for better predictions and comparison of the simulation. The re-circulation of the drying air temperature from chimney outlet can be considered for further study to improve the dryer efficiency.

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6. REFERENCES 1. D. Tarık (2007) “Determination of Effective Parameters for Drying of Apples”, Thesis Paper, İzmir Institute of Technology, İzmir Turkey. 2. W. Mulatu (2010) “Solar Drying of Fruits and Windows of Opportunities in Ethiopia”, African Journal of Food Science Vol. 4. No.13. pp. 790 – 802. 3. P. Rajkumar (2007) “Comparative Performance of Solar Cabinet, Vacuum Assisted Solar and Open Sun Drying Methods”, Thesis Paper, McGill University, Montreal, Canada. 4. S. Kamaruzzaman, Y. O. Mohd and H. Z. Saleem, (2010) “Advances In Solar Assisted Drying Systems for Marine and Agricultural Products”, Solar Energy Research Institute Universiti Kebangsaan, Malaysia. 5. T. Aklilu, (2009) “Experimental Analysis for Performance Evaluation of Solar Dryer”, Thesis Paper, AAU, Addis Ababa. 6. S. Singh and S. Kumar (2012) “Testing method for thermal performance based rating of various solar dryer designs”, Solar Energy Vol.86. pp. 87–98. 7. W. Aissa, M. El-Sallak and A. Elhake, (2011) “Performance of Solar Dryer Chamber used for Convective Drying of Sponge-Cotton”, Thesis Paper, Cairo University, Cairo, Egypt. 8. J.A Duffle and, W.A Beckman (1991) “Solar Engineering of Thermal Processes”, New York, NY: John Wiley & Sons, Inc. 9. M. Mohanraj1, P. Chandrasekar (2009) “Performance of A Forced Convection Solar Drier Integrated with Gravel as Heat Storage Material for Chili Drying”, Journal of Engineering Science and Technology, Vol. 4. No. 3. pp. 305 – 314. 10. K. Mu’azu, I.M Bugaje and I.A Mohammed (2012) “Performance Evaluation of Forced Air-Convection Vegetable Drying System”, Basic. Appl. Sci. Res., Vol.2. No. 3. pp. 2562-2568. 11. A. Sharma, C.R. Chen and Nguyen Vu Lan (2009) “Solar-energy drying systems: A review”, Renewable and Sustainable Energy, Vol. 13. pp. 1185–1210. 12. M. Subarna and others (2011) “Performance evaluation of a small scale indirect solar dryer with static reflectors during non-summer months in the Saurashtra region of western India”, Solar Energy, Vol. 85. pp. 2686–2696 13. T.A. Dawit (2012) “Design, Manufacturing and Performance Testing of Solar Crop Dryer for Rural Application”, Thesis Paper, Mekelle, Mechanical Engineering Department, Mekelle University. 14. T. Anteneh and G. Assab (2010) “Design and Prototype of Seed Dryer”, Final year Project, Mekelle, Mechanical Engineering Department, Mekelle University. 15. S. V. VenkataRaman, S. Iniyan and R. Goic (2012) “A review of solar drying technologies”, Renewable and Sustainable Energy Reviews, Vol. 16. pp. 2652– 2670. 16. Hassan E. and S. Fath (1995) “Thermal Performance of A Simple Design Solar Air Heater with Built-in Thermal Energy Storage System”, Energy Convers. Mgmt. Vol. 36. No. 10. pp. 989-997. 17. P. T. Saravana kumar, K. Mayilsamy, and M. Mohanraj (2012) “Numerical Study and Thermal Performance of the Flat Plate Solar Air Heaters with and without Thermal Storage”, Engineering and Applied Sciences, Vol. 7. No. 4. pp. 467-471. 49

18. R. K. Goyal, G. N. Tiwari and H. P. Garg (1998) “Effect of Thermal Storage on the Performance of an Air Collector: A Periodic Analysis”, Energy Convers. Mgmt. Vol. 39. No. 3/4. pp. 193-202. 19. S. Aboul-Enein et al and others (2000) “Parametric study of a solar air heater with and without thermal storage for solar drying applications”, Renewable Energy Vol. 21. pp. 505-522. 20. R.J. Goldstein (2005) “Heat transfer- a review of 2002 literature”, International Journal of Heat and Mass Transfer, Vol. 48. pp. 819–927. 21. A.A. El-Sebaii and others (2002) “Experimental investigation of an indirect type natural convection solar dryer”, Energy Conversion and Management, Vol. 43. pp. 2251–2266. 22. A.A. El-Sebaii and others (2002) “Empirical correlations for drying kinetics of some fruits and vegetables”, Energy, Vol.27. pp. 845–859. 23. M.K. Krokida, V.T. Karathanos and Z.B. Maroulis (2000) “Compression analysis of dehydrated agricultural products”, Drying Technology, Vol.18. pp. 395–408. 24. B.Gebremedhin (2002) “Engineering Geological Investigation of Mekelle Area, Tigray, Northern Ethiopia”, AAU, School of Graduate Studies, Engineering Geology, Addis Ababa. 25. Somerton, W.H., (1958), “Some thermal characteristics of porous rocks”, American Institute of Mining Engineering Transactions, Vol. 213, pp. 375-378.

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7. APPENDIXES A. APPENDIX 1: Fortran programing code SUBROUTINE TYPE214(TIME,XIN,OUT,T,DTDT,PAR,INFO,ICNTRL,*) C******************************************************************* C Object: TRAYS C Simulation Studio Model: Type214 C Author: ATKILT MULU C Editor: ATKILT MULU C Date: July 26, 2013 last modified: July 26, 2013 C *** C *** Model Parameters C *** C ITC1 C [-Inf;+Inf] C CPC1 kJ/kg.K [-Inf;+Inf] C CPA1 kJ/kg.K [-Inf;+Inf] C MC1 kg [-Inf;+Inf] C AC1 m^2 [-Inf;+Inf] C MO1 Fraction [-Inf;+Inf] C MF1 Fraction [-Inf;+Inf] C WO1 kg [-Inf;+Inf] C WF1 kg [-Inf;+Inf] C Hcfc1 kJ/hr.m^2.K [-Inf;+Inf] C IMAIR1 kg/hr [-Inf;+Inf] C *** C *** Model Inputs C *** C TAIR1 C [-Inf;+Inf] C TIN C [-Inf;+Inf] C VWIND m/s [-Inf;+Inf] C RH1 Fraction [-Inf;+Inf] C *** C *** Model Outputs C *** C TC1 C [-Inf;+Inf] C MAIR1 kg/hr [-Inf;+Inf] C Hfg1 kJ/kg.K [-Inf;+Inf] C Meq1 Fraction [-Inf;+Inf] C K1 - [-Inf;+Inf] C MT1 Fraction [-Inf;+Inf] C MW1 kg [-Inf;+Inf] C Wt1 kg [-Inf;+Inf] C TAIR2 C [-Inf;+Inf] C Qu1 kJ/hr [-Inf;+Inf] C *** C *** Model Derivatives C ***

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C (Comments and routine interface generated by TRNSYS Studio) C******************************************************************* C TRNSYS acess functions (allow to acess TIME etc.) USE TrnsysConstants USE TrnsysFunctions C------------------------------------------------------------------C REQUIRED BY THE MULTI-DLL VERSION OF TRNSYS !DEC$ATTRIBUTES DLLEXPORT :: TYPE214 !SET THE CORRECT TYPE NUMBER HERE C------------------------------------------------------------------C------------------------------------------------------------------C TRNSYS DECLARATIONS IMPLICIT NONE !REQUIRES THE USER TO DEFINE ALL VARIABLES BEFORE USING THEM DOUBLE PRECISION XIN !THE ARRAY FROM WHICH THE INPUTS TO THIS TYPE WILL BE RETRIEVED DOUBLE PRECISION OUT !THE ARRAY WHICH WILL BE USED TO STORE THE OUTPUTS FROM THIS TYPE DOUBLE PRECISION TIME !THE CURRENT SIMULATION TIME - YOU MAY USE THIS VARIABLE BUT DO NOT SET IT! DOUBLE PRECISION PAR !THE ARRAY FROM WHICH THE PARAMETERS FOR THIS TYPE WILL BE RETRIEVED DOUBLE PRECISION STORED !THE STORAGE ARRAY FOR HOLDING VARIABLES FROM TIMESTEP TO TIMESTEP DOUBLE PRECISION T !AN ARRAY CONTAINING THE RESULTS FROM THE DIFFERENTIAL EQUATION SOLVER DOUBLE PRECISION DTDT !AN ARRAY CONTAINING THE DERIVATIVES TO BE PASSED TO THE DIFF.EQ. SOLVER INTEGER*4 INFO(15) !THE INFO ARRAY STORES AND PASSES VALUABLE INFORMATION TO AND FROM THIS TYPE INTEGER*4 NP,NI,NOUT,ND !VARIABLES FOR THE MAXIMUM NUMBER OF PARAMETERS,INPUTS,OUTPUTS AND DERIVATIVES INTEGER*4 NPAR,NIN,NDER !VARIABLES FOR THE CORRECT NUMBER OF PARAMETERS,INPUTS,OUTPUTS AND DERIVATIVES INTEGER*4 IUNIT,ITYPE !THE UNIT NUMBER AND TYPE NUMBER FOR THIS COMPONENT INTEGER*4 ICNTRL !AN ARRAY FOR HOLDING VALUES OF CONTROL FUNCTIONS WITH THE NEW SOLVER INTEGER*4 NSTORED !THE NUMBER OF VARIABLES THAT WILL BE PASSED INTO AND OUT OF STORAGE CHARACTER*3 OCHECK !AN ARRAY TO BE FILLED WITH THE CORRECT VARIABLE TYPES FOR THE OUTPUTS CHARACTER*3 YCHECK !AN ARRAY TO BE FILLED WITH THE CORRECT VARIABLE TYPES FOR THE INPUTS C------------------------------------------------------------------C------------------------------------------------------------------C USER DECLARATIONS - SET THE MAXIMUM NUMBER OF PARAMETERS (NP), INPUTS (NI),

52

C OUTPUTS (NOUT), AND DERIVATIVES (ND) THAT MAY BE SUPPLIED FOR THIS TYPE PARAMETER (NP=11,NI=4,NOUT=10,ND=0,NSTORED=2) C------------------------------------------------------------------C------------------------------------------------------------------C REQUIRED TRNSYS DIMENSIONS DIMENSION XIN(NI),OUT(NOUT),PAR(NP),YCHECK(NI),OCHECK(NOUT), 1 STORED(NSTORED),T(ND),DTDT(ND) INTEGER NITEMS C------------------------------------------------------------------C------------------------------------------------------------------C ADD DECLARATIONS AND DEFINITIONS FOR THE USER-VARIABLES HERE C PARAMETERS DOUBLE PRECISION ITC1 !CROP INITIAL TEMPERATURE DOUBLE PRECISION CPC1 !CROP SPECIFIC HEAT CAPACITY DOUBLE PRECISION CPA1 !FLOWING AIR SPECIFIC HEAT CAPACITY DOUBLE PRECISION MC1 !MASS OF CROP DOUBLE PRECISION AC1 !CROP SURFACE AREA DOUBLE PRECISION MO1 !CROP INITIAL MOISTURE CONTENT DOUBLE PRECISION MF1 !CROP FINAL MOISTURE CONTENT DOUBLE PRECISION WO1 !INITIAL WEIGHT OF CROP DOUBLE PRECISION WF1 ! FINAL WEIGHT OF CROP DOUBLE PRECISION Hcfc1 !HEAT TRANSFER COEFICIENT DOUBLE PRECISION IMAIR1 C INPUTS DOUBLE PRECISION TAIR1 !COLLECTOR OUTLET TEMPERATURE DOUBLE PRECISION TIN !COLLECTOR INLET TEMPERATURE DOUBLE PRECISION VWIND !WIND SPEED DOUBLE PRECISION RH1 !RELATIVE HUMIDITY C LOCAL AND INTERNAL VARIABLES DECLARATIONS DOUBLE PRECISION TC1 DOUBLE PRECISION MAIR1 DOUBLE PRECISION TAIR2 DOUBLE PRECISION Qu1 DOUBLE PRECISION Hfg1 DOUBLE PRECISION MW1 DOUBLE PRECISION Wt1 DOUBLE PRECISION MT1 DOUBLE PRECISION Meq1 DOUBLE PRECISION K1 DOUBLE PRECISION TIME0 DOUBLE PRECISION TFINAL DOUBLE PRECISION DELT DOUBLE PRECISION TI,AA,BB,TF,TCBAR C------------------------------------------------------------------C READ IN THE VALUES OF THE PARAMETERS IN SEQUENTIAL ORDER ITC1=PAR(1) CPC1=PAR(2) CPA1=PAR(3) MC1=PAR(4)

53

AC1=PAR(5) MO1=PAR(6) MF1=PAR(7) WO1=PAR(8) WF1=PAR(9) Hcfc1=PAR(10) IMAIR1=PAR(11) C------------------------------------------------------------------C RETRIEVE THE CURRENT VALUES OF THE INPUTS TO THIS MODEL FROM THE XIN ARRAY IN SEQUENTIAL ORDER TAIR1=XIN(1) TIN=XIN(2) VWIND=XIN(3) RH1=XIN(4) IUNIT=INFO(1) ITYPE=INFO(2) C------------------------------------------------------------------C GET GLOBAL TRNSYS SIMULATION VARIABLES TIME0=getSimulationStartTime() TFINAL=getSimulationStopTime() DELT=getSimulationTimeStep() C------------------------------------------------------------------C SET THE VERSION INFORMATION FOR TRNSYS IF(INFO(7).EQ.-2) THEN INFO(12)=16 RETURN 1 ENDIF C------------------------------------------------------------------C DO ALL THE VERY LAST CALL OF THE SIMULATION MANIPULATIONS HERE IF (INFO(8).EQ.-1) THEN RETURN 1 ENDIF C------------------------------------------------------------------C PERFORM ANY 'AFTER-ITERATION' MANIPULATIONS THAT ARE REQUIRED HERE C e.g. save variables to storage array for the next timestep IF (INFO(13).GT.0) THEN NITEMS=0 C STORED(1)=.... C CALL setStorageVars(STORED,NITEMS,INFO) RETURN 1 ENDIF C------------------------------------------------------------------C DO ALL THE VERY FIRST CALL OF THE SIMULATION MANIPULATIONS HERE IF (INFO(7).EQ.-1) THEN C SET SOME INFO ARRAY VARIABLES TO TELL THE TRNSYS ENGINE HOW THIS TYPE IS TO WORK INFO(6)=NOUT INFO(9)=1

54

INFO(10)=0

!STORAGE FOR VERSION 16 HAS BEEN CHANGED

C SET THE REQUIRED NUMBER OF INPUTS, PARAMETERS AND DERIVATIVES THAT THE USER SHOULD SUPPLY IN THE INPUT FILE C IN SOME CASES, THE NUMBER OF VARIABLES MAY DEPEND ON THE VALUE OF PARAMETERS TO THIS MODEL.... NIN=NI NPAR=NP NDER=ND C CALL THE TYPE CHECK SUBROUTINE TO COMPARE WHAT THIS COMPONENT REQUIRES TO WHAT IS SUPPLIED IN C THE TRNSYS INPUT FILE CALL TYPECK(1,INFO,NIN,NPAR,NDER) C SET THE NUMBER OF STORAGE SPOTS NEEDED FOR THIS COMPONENT NITEMS=2 CALL setStorageSize(NITEMS,INFO) C RETURN TO THE CALLING PROGRAM RETURN 1 ENDIF C------------------------------------------------------------------C DO ALL OF THE INITIAL TIMESTEP MANIPULATIONS HERE - THERE ARE NO ITERATIONS AT THE INTIAL TIME IF (TIME.LT.(TIME0+DELT/2.D0)) THEN C SET THE UNIT NUMBER FOR FUTURE CALLS IUNIT=INFO(1) ITYPE=INFO(2) C CHECK THE PARAMETERS FOR PROBLEMS AND RETURN FROM THE SUBROUTINE IF AN ERROR IS FOUND C IF(...) CALL TYPECK(-4,INFO,0,"BAD PARAMETER #",0) C RE-READ IN THE VALUES OF THE PARAMETERS IN SEQUENTIAL ORDER IF(INFO(1).NE.IUNIT) THEN C RESET THE UNIT NUMBER IUNIT=INFO(1) ITYPE=INFO(2) !reread the parameters ITC1=PAR(1) CPC1=PAR(2) CPA1=PAR(3) MC1=PAR(4) AC1=PAR(5) MO1=PAR(6) MF1=PAR(7) WO1=PAR(8) WF1=PAR(9) Hcfc1=PAR(10) IMAIR1=PAR(11) ENDIF C PERFORM ANY REQUIRED CALCULATIONS TO SET THE INITIAL VALUES OF THE OUTPUTS HERE

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C

TC1

OUT(1)=PAR(1) C MAIR1 OUT(2)=0 C Hfg1 OUT(3)=2501+1.84*PAR(1) C Meq1 OUT(4)=0 C K1 OUT(5)=0 C MT1 OUT(6)=PAR(6) C MW1 OUT(7)=0 C Wt1 OUT(8)=PAR(8) C TAIR2 OUT(9)=XIN(1) C Qu1 OUT(10)=0 C PERFORM ANY REQUIRED CALCULATIONS TO SET THE INITIAL STORAGE VARIABLES HERE IF(INFO(7).EQ.13) THEN CALL getStorageVars(STORED,NITEMS,INFO) STORED(1)=STORED(2) CALL getStorageVars(STORED,NITEMS,INFO) TI=STORED(1) AA=-(Hcfc1*AC1)/(MC1*CPC1) BB=(TAIR1*TIME*Hcfc1*AC1)/(MC1*CPC1) CALL DIFFERENTIAL_EQN(TIME,AA,BB,TI,TF,TCBAR) STORED(2)=TF ENDIF C PUT THE STORED ARRAY IN THE GLOBAL STORED ARRAY CALL setStorageVars(STORED,NITEMS,INFO) C RETURN TO THE CALLING PROGRAM RETURN 1 ENDIF C------------------------------------------------------------------C *** ITS AN ITERATIVE CALL TO THIS COMPONENT *** C------------------------------------------------------------------C RETRIEVE THE VALUES IN THE STORAGE ARRAY FOR THIS ITERATION C NITEMS=2 C CALL getStorageVars(STORED,NITEMS,INFO) C STORED(1)=...... C------------------------------------------------------------------C CHECK THE INPUTS FOR PROBLEMS C IF(...) CALL TYPECK(-3,INFO,'BAD INPUT #',0,0) C IF(IERROR.GT.0) RETURN 1 C------------------------------------------------------------------C *** PERFORM ALL THE CALCULATION HERE FOR THIS MODEL. ***

56

C------------------------------------------------------------------C ADD YOUR COMPONENT EQUATIONS HERE; BASICALLY THE EQUATIONS THAT WILL C CALCULATE THE OUTPUTS BASED ON THE PARAMETERS AND THE INPUTS. REFER TO C CHAPTER 3 OF THE TRNSYS VOLUME 1 MANUAL FOR DETAILED INFORMATION ON C WRITING TRNSYS COMPONENTS. C CROP TEMPERATURE CALCULATION TC1=TCBAR*TIME C AIR FLOW RATE CALCULATION MAIR1=VWIND*0.13*1.225*3.6*TIME C LATENT HEAT CALCULATION Hfg1=2501+(1.84*TAIR1) C INSTANTANEOUS MOISTURE CONTENT CALCULATION Meq1=(0.65392/(TAIR1*TIME*1.688E-2))**0.3384 K1=(TAIR1*3.29**-6)-(9.75**-4) MT1=Meq1+(MO1-Meq1)*EXP(-K1*TIME) C INSTANTANEOUS WATER CONTENT REMOVED MW1=WO1*((MO1-MT1)/(1-MT1)) C INSTANTANEOUS WEIGHT LOSS CALCULATION Wt1=WO1-MW1 C DRYING AIR TEMPERATURE CALCULATION TAIR2=TAIR1-((MW1*Hfg1)/(MAIR1*10*CPA1)) !DRYING AIR ENTERING THE 2ND TRAY C ABSORBED HEAT CALCULATION Qu1=(-1*MAIR1*CPA1*(TAIR2-TAIR1)) C------------------------------------------------------------------C SET THE STORAGE ARRAY AT THE END OF THIS ITERATION IF NECESSARY C NITEMS= C STORED(1)=....... C CALL setStorageVars(STORED,NITEMS,INFO) C------------------------------------------------------------------C REPORT ANY PROBLEMS THAT HAVE BEEN FOUND USING CALLS LIKE THIS: C CALL MESSAGES(-1,'put your message here','MESSAGE',IUNIT,ITYPE) C CALL MESSAGES(-1,'put your message here','WARNING',IUNIT,ITYPE) C CALL MESSAGES(-1,'put your message here','SEVERE',IUNIT,ITYPE) C CALL MESSAGES(-1,'put your message here','FATAL',IUNIT,ITYPE) C------------------------------------------------------------------C SET THE OUTPUTS FROM THIS MODEL IN SEQUENTIAL ORDER AND GET OUT C TC1 OUT(1)=TCBAR*TIME C MAIR1 OUT(2)=XIN(3)*0.13*1.225*3.6*TIME C Hfg1 OUT(3)=2501+(1.84*XIN(1)) C Meq1

57

OUT(4)=(0.65392/(XIN(1)*TIME*1.688E-2))**0.3384 C

K1

C

MT1

C

MW1

C

Wt1

OUT(5)=(XIN(1)*3.29**-6)-(9.75**-4) OUT(6)=OUT(4)+(PAR(6)-OUT(4))*EXP(-K1*TIME) OUT(7)=PAR(8)*((PAR(6)-OUT(6))/(1-OUT(6))) OUT(8)=PAR(8)-OUT(7) TAIR2 OUT(9)=XIN(1)-(OUT(7)*OUT(3)/(OUT(2)*10*PAR(3))) C Qu1 OUT(10)=(-1*OUT(2)*PAR(3)*(OUT(9)-XIN(1))) C------------------------------------------------------------------C EVERYTHING IS DONE - RETURN FROM THIS SUBROUTINE AND MOVE ON RETURN 1 END C-------------------------------------------------------------------

C

58

B. APPENDIX 2:

(a) Mangoes slices (b) Tomatoes slices Figure A 1: Samples slices preparation

(a) Slices distribution on thin layer (b) Tray arrangement on the cabinet Figure A 2: Samples distribution on trays and drying cabinet

(a) Without heat storage (b) With heat storage Figure A 3: Experimental setup

59

Figure A 4: Construction of dryer with heat storage rock

C. APPENDIX 3: a. Steps to create new component proforma

Figure A 5: Creating new component proforma

60

Figure A 6: Generating FORTRAN code skeleton and a compiler project

Figure A 7:Writing Mathematical equations on microsoft visual stidio

61

b. Steps to create new TRNSYS project

Figure A 8: Component selection from TRNSYS studio

Figure A 9: Connecting components inputs and outputs

Figure A 10: Configuring connections for simulation

62

D. APPENDIX 4: Prepared weather data for simulation

The hourly weather data of Mekelle city prepared for TRNSYS simulation is summarized in the figures below.

Figure A 11: Typical meteorological year format weather data of Mekelle

63

Figure A 12: Graphical representations of the prepared data

64

E. APPENDIX 5: Practical measured data A. Data for mango drying

Table A 1: Drying without heat storage on 16/06/13 Tg Tplate 32.51 71.87 32.88 84.99 33.56 79.66 31.57 73.10 31.74 69.78 23.72 58.32 31.00 72.95

Tout Wb din RH % Dew (C) Tray 1 Tray 2 Tray 3 53.73 26.26 11.01 14.29 45.90 45.96 43.77 57.51 27.60 10.11 15.16 49.54 49.49 48.47 60.79 28.02 8.41 14.52 55.97 52.09 52.62 53.40 28.36 18.97 19.05 49.96 47.83 46.59 50.73 27.37 18.45 18.62 48.57 47.13 45.16 32.42 23.29 46.90 19.48 33.78 33.36 30.71 51.43 26.82 18.97 16.85 47.29 45.97 44.55

Table A 2: Drying without heat storage on 17/06/13 Tg Tplate 26.01 59.63 28.46 63.49 32.60 64.55 35.50 68.26 36.21 73.97 36.00 73.13 36.62 71.11 33.26 60.90 30.70 69.78 32.82 67.20

Tout Wb din RH % Dew (C) Tray 1 Tray 2 Tray 3 36.02 22.09 29.40 15.40 29.88 29.01 29.59 42.43 23.28 19.32 14.10 36.61 35.55 36.26 52.34 24.69 9.84 10.93 47.07 45.70 46.61 63.11 26.44 4.72 7.78 56.74 55.09 56.19 67.80 29.13 5.58 12.44 61.59 59.79 60.99 64.90 26.58 4.09 6.68 60.84 59.07 60.25 64.65 27.36 4.98 9.86 60.86 59.09 60.27 51.64 24.74 10.37 11.40 44.55 43.26 44.12 47.67 21.42 7.90 4.12 36.73 35.66 36.37 54.51 25.08 10.69 10.30 48.32 46.91 47.85

Tamb Ch out Wb cout RH % Dew (C) Radation 22.95 34.99 19.51 22.40 10.34 727 27.82 45.76 23.63 14.93 12.52 985 30.95 44.55 23.82 17.70 13.90 867 28.48 38.90 24.03 29.79 17.55 720 28.24 38.41 22.58 25.55 14.98 673 23.17 29.18 21.92 53.78 18.68 503 26.93 38.63 22.58 27.36 14.66 746

Tamb Ch out Wb cout RH % Dew (C) Radation 23.56 27.55 19.32 41.36 14.29 872 25.47 33.76 21.59 29.95 14.89 847 28.06 38.40 24.74 19.04 15.70 835 29.06 43.04 29.11 15.48 20.27 708 29.70 46.79 29.78 11.95 19.50 872 28.35 46.10 25.01 5.56 6.69 735 29.17 45.12 25.41 6.68 7.81 869 27.74 41.08 24.14 21.06 15.73 565 25.67 33.87 17.28 13.86 3.55 439 27.42 39.53 24.04 18.33 13.16 749

Table A 3: Drying without heat storage on 18/06/13 Tg Tplate 30.72 55.16 33.10 67.05 35.62 73.26 36.80 78.36 37.12 75.55 34.67 69.88

Tout Wb din RH % Dew (C) Tray 1 Tray 2 Tray 3 Tamb Ch out Wb cout RH % Dew (C) Radation 42.45 21.59 14.49 9.88 40.28 38.70 38.12 22.77 27.55 20.32 19.87 10.54 782 50.10 23.87 10.25 10.36 46.28 45.13 43.46 23.77 33.76 22.28 16.24 11.61 857 60.59 26.19 5.83 9.19 55.21 53.91 52.35 25.47 38.40 24.74 10.76 11.86 940 65.58 27.15 4.34 8.28 61.43 58.37 59.24 28.13 43.04 26.48 7.75 12.05 913 64.35 26.80 4.62 7.84 61.22 57.16 54.30 27.68 46.79 25.00 9.35 11.20 738 56.61 25.12 7.90 9.11 52.88 50.66 49.49 25.56 37.91 23.76 12.80 11.45 846

Table A 4: Drying with heat storage on 03/07/13 TIME

Tg

Tplate

Trock

TRB

Tout

Wb din

RH %

Dew

Tray 1

Tray 2

Tray 3

Tamb

Ch out

Wb cout

RH %

Dew

Radation

10:40 10:50 11:00 11:10 11:30 11:40 11:50 12:00 12:10 12:20 12:30 12:40 12:50 13:00

33.85 32.38 33.47 34.63 34.35 34.24 34.72 35.59 39.50 39.29 35.70 32.14 29.85 27.62 34.10

64.12 59.61 68.63 72.37 73.65 70.74 74.69 77.01 81.57 76.16 61.73 51.97 46.85 41.22 65.74

25.05 26.34 26.58 27.86 28.75 30.15 30.97 31.89 33.33 33.71 34.20 34.50 34.60 34.52 30.89

19.49 20.09 19.87 20.64 21.16 21.88 22.22 22.70 23.60 23.55 23.78 24.05 24.32 24.51 22.28

45.46 48.80 53.78 56.93 58.08 53.34 48.60 52.09 56.56 56.78 50.99 44.93 41.06 37.11 50.32

20.09 21.43 22.76 24.10 25.44 23.29 23.57 24.06 24.10 24.39 25.83 25.40 25.36 24.73 23.90

7.09 6.60 5.04 5.01 6.18 6.20 11.09 8.55 5.24 5.51 13.05 20.65 28.34 36.60 11.80

1.80 3.18 2.82 4.88 8.74 5.47 10.59 9.29 5.28 6.16 14.88 17.29 19.11 19.81 9.24

40.58 44.64 49.34 52.13 52.73 46.21 44.74 47.92 53.83 53.79 44.49 38.84 35.92 33.01 45.58

33.51 37.07 38.69 41.20 42.38 39.56 38.76 41.02 46.57 47.43 39.33 35.29 31.26 31.16 38.80

37.33 41.07 45.39 47.96 48.52 42.51 41.16 44.09 49.52 49.49 40.93 36.73 33.05 32.96 42.19

25.58 24.74 25.24 26.81 27.71 28.39 29.17 29.83 30.32 29.79 29.24 27.61 26.57 25.30 27.59

35.09 38.61 42.67 45.08 45.61 39.96 38.69 41.45 46.55 46.52 40.48 34.53 34.07 30.98 40.02

24.41 24.06 24.26 24.59 24.29 24.59 23.68 26.69 29.74 27.40 23.56 22.54 24.50 23.35 24.83

41.75 29.88 21.56 18.24 16.65 28.35 28.31 31.87 29.77 23.22 23.82 35.57 45.90 52.84 30.55

20.16 17.87 16.12 15.46 14.47 18.19 17.09 21.34 24.58 20.47 15.87 17.10 20.77 20.23 18.55

722 896 918 924 876 813 895 932 773 536 399 262 174 127 661

65

Table A 5: Drying with heat storage on 04/07/13 Tg

Tplate

30 31 35 34 35 30 28 29 28 25 31

Trock

69 65 67 71 77 54 49 52 48 40 59

Trb

23 24 27 30 33 38 38 38 37 37 33

Tout

18 18 20 21 23 26 27 28 28 29 24

45 50 55 55 59 45 39 41 40 33 46

Wb din RH % 20 7 21 5 23 5 24 6 25 5 25 21 26 38 26 30 25 31 24 45 24 19

Dew

27 29 31 30 28 29 34 34 33 30 31

Tplate Trock 57 23 62 25 64 26 64 27 61 29 64 30 79 33 81 35 75 37 56 38 66 30

Trb

Tout

21 21 21 21 22 23 23 24 25 26 23

39 41 44 43 41 43 55 56 53 46 46

Wb din RH % 22 23 23 22 25 20 24 20 23 20 23 18 26 10 26 10 26 11 24 16 24 17

Dew

14 15 16 15 14 13 13 14 14 14 14

Tray 2

Wb cout RH % 20 11 21 11 23 10 24 12 26 13 26 31 27 45 26 37 25 33 25 57 24 26

Dew

Tray 1 Tray 2 Tray 3 Tamb Ch out Wb cout RH % 36 32 27 23 33 21 32 40 36 30 23 35 22 31 42 38 32 24 38 24 30 41 37 32 24 37 24 35 41 37 33 24 36 23 33 42 38 34 25 37 24 34 53 48 41 28 44 26 23 54 50 44 29 46 24 15 51 47 43 29 45 22 12 44 41 39 27 39 22 22 44 41 36 26 39 23 27

Dew

44 49 54 54 58 44 37 40 38 32 45

Table A 6: Drying with heat storage on 05/07/13 Tg

Tray 1

2 1 4 7 7 16 22 20 19 20 12

Tray 3 41 46 50 50 54 41 35 38 36 30 42

Tamb 39 43 48 48 51 39 33 36 34 29 40

Ch out 22 23 25 26 27 26 25 26 27 25 25

38 42 46 46 50 38 32 35 33 28 39

6 7 9 12 14 21 23 21 19 22 16

Radation 853 886 925 954 966 660 530 489 529 179 697

14 16 17 19 17 18 19 13 9 13 16

Radation 630 744 813 721 606 644 871 1064 808 863 776

B. Data for drying tomato

Table A 7: Drying without heat storage on 20/06/13 Tg

Tplate

Tout

Wb din

RH %

Dew

Tray 1

Tray 2

Tray 3

Tamb

Ch out

Wb cout

RH %

Dew

Radation

31.20 30.55 29.98 30.18 28.24 27.74 31.21 32.04 32.43 34.32 35.42 35.48 35.08 32.93 33.15 33.52 32.09 31.96 31.74 30.80 30.46 31.96 29.89 31.71 32.95 29.78 29.98

64.64 61.40 60.54 53.35 45.37 68.04 77.55 80.89 82.74 82.59 85.80 83.51 70.73 71.97 76.51 64.29 62.47 56.97 56.32 71.60 59.87 62.73 68.84 59.91 50.98 42.05 33.11

45.02 41.84 42.52 39.76 35.41 42.31 50.67 54.82 56.47 57.65 60.89 60.85 53.03 53.05 57.22 49.66 47.78 44.84 43.56 48.75 44.59 45.02 50.24 38.61 34.32 30.03 25.74

19.49 19.31 18.66 17.95 16.05 18.87 20.59 20.98 21.47 21.89 22.56 23.03 21.39 21.33 22.17 20.16 19.33 18.71 18.17 19.94 18.71 18.76 20.37 18.45 17.98 17.50 16.62

6.22 9.44 7.04 8.69 9.72 7.77 3.62 1.77 1.65 1.66 1.15 1.69 3.37 3.28 2.22 3.59 3.50 4.75 4.81 3.87 4.99 4.70 3.56 11.76 18.31 27.75 39.11

-0.27 3.19 -0.36 0.49 -1.07 0.81 -3.35 -9.31 -9.24 -8.51 -10.93 -6.58 -2.81 -3.13 -5.41 -4.04 -5.45 -3.61 -4.25 -3.70 -3.20 -3.64 -3.81 3.87 6.86 9.41 10.80

42.64 40.62 39.71 39.20 35.90 38.75 46.28 49.92 52.15 53.57 56.73 57.59 50.80 50.73 54.70 48.05 46.13 43.60 42.60 46.50 43.40 43.30 47.13 36.50 30.77 25.04 21.31

41.81 39.00 39.66 37.36 32.51 33.81 38.10 40.55 42.81 44.51 45.75 47.17 46.73 44.72 45.86 44.10 41.16 40.97 40.56 39.51 38.45 40.14 42.80 33.84 29.98 24.11 20.24

41.83 41.24 39.86 38.49 34.23 40.63 44.74 45.80 47.46 48.48 50.49 51.75 46.76 47.83 50.37 43.53 42.67 40.69 40.04 45.04 41.28 41.40 38.46 31.18 29.18 23.18 19.17

19.68 19.50 18.85 18.13 16.22 19.06 20.80 21.19 21.69 22.11 22.79 23.26 21.60 21.55 22.39 20.36 19.53 18.90 18.36 20.14 18.90 18.95 20.58 18.64 18.16 17.67 17.19

36.91 36.39 35.17 33.96 30.20 35.85 39.48 40.41 41.88 42.78 44.55 45.66 41.26 42.20 44.44 38.41 37.65 35.91 35.33 39.74 36.42 36.53 39.53 33.07 30.03 26.98 23.93

17.71 17.55 16.97 16.32 14.59 17.15 18.72 19.07 19.52 19.90 20.51 20.93 19.44 19.40 20.16 18.32 17.58 17.01 16.52 18.12 17.01 17.06 18.52 16.78 16.34 15.91 15.47

12.36 12.76 13.08 13.22 14.92 12.44 11.18 10.77 9.93 9.72 9.00 8.70 10.56 9.20 8.32 11.71 10.72 11.90 11.34 9.17 11.01 10.98 10.55 16.72 22.65 30.40 40.50

3.27 3.32 2.73 1.93 0.65 2.55 3.81 3.98 3.93 4.30 4.52 4.85 4.35 3.09 3.32 3.66 1.83 1.96 0.85 1.23 1.27 1.32 3.04 4.54 6.43 8.14 9.71

639 592 579 430 400 978 962 964 970 959 968 855 616 845 643 479 374 350 454 517 426 670 924 542 435 372 301

66

Table A 8: Drying without heat storage on 21/06/13 Tg

Tplate

Tout

Wb din

RH %

Dew

29.07 29.02 29.38 30.64 31.32 32.28 31.47 32.48 32.34 32.26 32.32 33.63 35.15 38.71 34.16 36.59 36.75 32.18 32.36 34.02 31.33 34.79 37.98 35.02 34.79 31.33 25.99

60.83 62.85 64.53 69.65 72.44 73.98 74.14 75.73 76.39 74.33 78.77 80.51 82.64 80.99 74.51 86.13 86.81 57.46 61.02 77.65 58.77 54.42 86.31 91.16 74.80 45.60 38.87

41.23 42.66 44.38 48.07 50.81 51.83 52.33 53.92 53.70 53.83 56.73 58.50 61.29 62.89 57.22 65.49 68.02 52.89 51.47 59.57 52.68 46.86 64.56 71.21 64.04 43.41 38.18

21.44 24.09 27.86 26.71 25.55 28.65 28.94 29.37 28.10 27.88 28.64 26.58 26.01 25.62 24.94 26.46 25.24 25.85 25.83 24.66 24.70 24.40 24.09 25.79 23.49 21.18 20.88

16.02 21.05 28.81 18.89 12.67 17.93 17.89 16.72 14.46 13.90 12.29 7.56 5.06 3.79 6.03 3.60 1.51 12.12 13.66 4.91 10.13 16.41 1.94 1.49 1.48 13.26 21.59

10.41 15.74 22.20 18.41 14.29 20.57 20.93 21.09 18.58 18.04 18.29 12.04 7.98 4.85 7.77 5.78 -4.12 14.40 15.18 5.57 11.50 14.51 -3.65 -3.39 -7.09 8.64 11.84

Tray 1 Tray 2 Tray 3 39.17 40.53 42.16 45.67 48.27 49.24 49.71 51.22 51.02 51.14 53.89 55.57 58.23 59.74 54.36 62.21 64.62 49.26 47.94 55.48 49.07 43.64 60.13 66.32 59.64 40.43 35.56

35.64 36.88 38.37 41.56 43.93 44.81 45.24 46.61 46.43 46.53 49.04 50.57 52.99 54.37 49.47 56.61 58.81 44.83 43.62 50.49 44.65 39.72 54.71 60.35 54.28 36.79 32.36

36.04 37.29 38.79 42.01 44.41 45.30 45.74 47.12 46.94 47.04 49.58 51.13 53.57 54.96 50.01 57.23 59.45 45.32 44.10 51.04 45.14 40.15 55.32 61.02 54.87 37.19 32.72

Tamb

Ch out Wb cout

RH %

Dew

Radation

21.72 22.87 23.36 25.15 26.45 27.13 27.23 27.90 27.92 27.94 29.19 30.19 31.62 32.63 30.14 34.61 36.75 28.11 27.67 32.15 28.29 25.85 35.17 37.60 33.05 22.43 20.10

33.15 34.30 35.69 38.65 40.86 41.68 42.08 43.35 43.18 43.28 45.62 47.04 49.29 50.57 46.01 52.66 54.70 41.70 40.57 46.96 41.53 36.94 50.89 56.13 50.48 34.22 30.10

22.08 23.21 30.36 22.16 15.52 20.29 19.68 19.63 17.51 16.28 14.18 9.56 6.69 4.69 7.26 5.14 4.02 14.03 15.19 5.61 11.79 19.10 3.50 1.68 7.82 13.85 22.81

8.65 10.35 15.62 13.25 9.65 14.36 14.22 15.22 13.31 12.28 12.02 7.22 3.72 -0.31 2.54 2.33 0.29 8.81 9.11 -0.32 6.13 9.61 -3.63 -9.16 6.81 2.79 6.59

694 726 754 775 797 720 840 861 890 888 836 944 974 985 632 996 1103 444 514 696 585 313 955 989 733 156 153

18.24 19.29 22.10 21.84 21.04 23.19 23.24 24.03 23.15 22.75 23.29 22.03 21.70 21.17 20.44 22.34 22.48 20.99 20.76 20.08 20.05 19.83 20.60 21.38 22.87 16.65 16.42

Table A 9: Drying without heat storage on 22/06/13 Tg

Tplate

Tout

31.47 32.66 33.26 33.90 34.57 31.80 29.68 30.51 30.39 30.09 28.42 27.01 26.84 27.12 32.18 32.36 34.02 31.33 34.79 37.98 35.02 34.79 31.33 25.99

71.11 74.42 77.42 81.53 66.05 59.93 62.82 65.55 60.89 50.64 45.52 45.54 47.76 48.21 57.46 61.02 77.65 58.77 54.42 86.31 91.16 74.80 45.60 38.87

50.16 53.17 55.71 58.48 53.16 47.72 49.29 51.50 49.63 44.03 39.97 39.32 40.47 40.85 51.86 50.46 58.40 51.65 45.94 63.29 69.81 62.78 42.56 37.43

Wb din RH % 23.11 24.50 25.09 26.52 24.05 21.91 22.18 22.89 22.12 20.30 18.54 18.22 18.45 18.70 25.85 25.83 24.66 24.70 24.40 24.09 25.79 23.49 21.18 20.88

8.56 8.37 7.31 7.49 7.61 8.59 7.59 6.97 7.16 9.13 9.98 10.04 9.04 9.18 12.12 13.66 4.91 10.13 16.41 1.94 1.49 1.48 13.26 21.59

Dew

Tray 1

Tray 2

Tray 3

Tamb

Ch out

Wb cout

RH %

Dew

Radation

7.91 9.75 9.56 11.87 8.34 6.18 5.53 5.88 4.93 4.34 2.58 2.18 1.57 2.07 14.40 15.18 5.57 11.50 14.51 -3.65 -3.39 -7.09 8.64 11.84

46.92 49.29 51.69 54.63 51.67 46.36 47.56 49.57 48.08 43.42 39.46 38.21 39.04 39.51 49.26 47.94 55.48 49.07 43.64 60.13 66.32 59.64 40.43 35.56

43.64 45.84 48.07 50.80 48.05 43.11 44.23 46.10 44.71 40.38 36.70 35.53 36.30 36.75 44.83 43.62 50.49 44.65 39.72 54.71 60.35 54.28 36.79 32.36

43.43 45.79 48.12 50.55 48.71 44.84 45.40 47.14 46.23 43.02 39.05 35.75 34.77 34.49 45.32 44.10 51.04 45.14 40.15 55.32 61.02 54.87 37.19 32.72

24.85 26.34 26.98 28.52 25.86 23.56 23.85 24.62 23.78 21.83 19.94 19.60 19.84 20.11 28.11 27.67 32.15 28.29 25.85 35.17 37.60 33.05 22.43 20.10

39.91 42.09 44.22 46.46 44.77 41.21 41.73 43.32 42.49 38.63 35.89 32.85 31.95 31.70 37.94 36.92 42.73 37.79 33.62 46.31 51.08 45.94 31.14 27.39

24.11 25.55 26.17 27.66 25.08 22.85 23.13 23.88 23.07 21.17 19.34 19.01 19.24 19.50 20.99 20.76 20.08 20.05 19.83 20.60 21.38 22.87 16.65 16.42

18.97 18.84 16.81 16.82 13.60 13.59 13.48 12.93 12.25 13.38 13.01 18.08 19.08 19.69 14.03 15.19 5.61 11.79 19.10 3.50 1.68 7.82 13.85 22.81

15.10 16.91 16.99 18.93 14.15 11.11 11.43 12.15 10.63 8.69 5.95 8.12 9.58 10.45 8.81 9.11 -0.32 6.13 9.61 -3.63 -9.16 6.81 2.79 6.59

732 763 789 840 905 819 473 542 612 542 403 276 307 332 444 514 696 585 313 955 989 733 413 324

67

Table A 10: Drying without heat storage on 28/06/13 Tg 35.69 38.23 25.97 26.25 28.79 30.85 29.03 26.48 26.88 29.08 28.15 25.79 24.62 25.11 25.42

Tp 40.75 51.92 60.89 55.53 72.10 72.71 58.44 46.28 51.59 74.90 60.10 46.96 42.18 42.90 42.56

Trt 23.50 23.00 24.58 25.81 27.50 30.34 46.43 31.79 31.80 32.99 34.93 35.22 34.94 34.75 33.81

Trb 19.88 19.93 20.17 20.43 20.67 22.07 22.14 22.86 24.88 24.72 25.05 25.67 26.37 26.73 26.23

Tout 36.30 40.35 39.29 41.13 49.76 44.04 41.23 40.60 38.00 54.61 49.61 41.24 37.32 38.61 39.12

Wb din 22.43 21.74 22.11 20.91 19.72 20.38 20.60 21.62 23.65 21.80 22.28 23.12 24.94 23.70 23.99

RH % 29.93 18.45 21.67 14.70 2.76 9.30 4.70 17.64 29.96 3.07 7.50 20.90 36.80 28.57 28.34

Dew 15.92 11.83 13.43 9.06 -7.05 4.61 -1.09 11.37 17.39 -3.05 5.58 14.47 20.09 17.16 17.47

Tray 1 31.60 33.98 39.88 38.79 45.94 42.82 40.62 39.19 36.30 49.40 46.58 36.07 34.35 37.32 37.57

Table A 11: Drying without heat storage on 29/06/13 Tg 26 30 28 27 28 25 25

Tplate 56 72 52 57 64 44 43

Trock 26 29 30 32 34 35 35

Trb 20 21 23 25 25 26 26

Tout 41 52 45 42 52 39 38

Wb din 25 27 28 27 28 26 24

RH % 26 15 31 35 18 37 33

Dew 18 17 21 22 18 21 18

Tray 1 39 48 42 37 48 35 34

68

Tray 2 28.38 30.26 38.30 37.70 41.35 40.38 39.94 36.83 35.13 43.37 45.67 35.21 32.48 34.91 36.83

Tray 2 38 44 40 36 45 33 32

Tray 3 22.25 24.33 26.13 26.39 28.72 30.88 29.07 27.47 28.26 31.34 29.42 26.75 25.39 25.86 26.02

Tray 3 37 40 38 34 41 29 26

Tamb 19.37 19.97 21.47 21.25 21.87 23.76 23.98 23.02 23.92 26.98 25.07 22.52 22.04 21.83 22.08

Tamb 21 22 23 24 25 23 25

Ch out 31.40 33.00 32.11 29.54 32.92 32.79 31.37 30.11 30.85 38.53 41.65 32.72 27.15 28.38 29.91

Ch out 30 33 31 31 41 30 27

Wb cout 21.37 22.44 24.60 23.81 24.84 24.45 23.88 22.70 21.80 24.66 29.87 26.82 21.26 22.41 23.35

Wb cout 24 25 23 22 28 24 22

RH % 41.08 40.26 54.37 62.32 52.13 50.67 53.94 53.26 45.37 32.23 42.81 63.48 59.54 60.03 57.76

RH % 62 52 54 44 43 61 61

Dew 16.60 17.71 21.74 21.58 21.79 21.22 20.92 19.56 17.67 19.01 26.43 24.88 18.59 19.87 20.69

Dew 22 21 20 17 25 22 19

Radation 450 662 499 847 967 591 368 294 505 954 576 307 215 452 521

Radation 766 779 331 624 663 425 221