M. Manoj et al., International Journal of Advanced Engineering Technology E-ISSN 0976-3945 Research Paper SIMULATION OF SOLAR DRYER UTILIZING GREEN HOUSE EFFECT FOR COCOA BEAN DRYING M.Manoj 1, A. Manivannan 2
Address for Correspondence 1Department of Energy Engineering, Regional Centre, Anna University Tirunelveli Region, Tirunelveli-627 007. 2 Assistant Professor, Department of Energy Engineering, Regional Centre, Anna University Tirunelveli Region, Tirunelveli- 627 007. ABSTRACT Drying is an excellent way to preserve food and solar food dryers are appropriate food preservation technology for sustainable development. The aim of the work is to develop a MATLAB-based modeling and simulation to predict the air flow properties, equilibrium moisture content of the solar dryer technology for food crop drying especially cocoa and other cash crops. In the model practical and technological ways by which the Crank – Nicholson equation is applied to heat equations using finite difference method to develop a solar dryer utilizing Green House Effect (GHE) for drying cocoa beans. The mathematical model for the general case of the 3D (three-dimensional) conduction equation for green house dryer has been derived and simulated by Matlab program.The results show that the dryer performed at it optimal range and dried beans within 7 days to a moisture content of 7% to the weight of the bean. A mathematical model was developed to predict the performance of the green house effect type solar dryer and the 3D modeling was drawn using ProE. KEYWORDS : Cocoa, Green house effect, MATLAB, Simulation, Solar dryer. I. INTRODUCTION processing, statistics and data analysis, control design Cocoa beans are the seeds of Theobroma cacao and mathematical modeling. Technical computing (Sterculiaceae family), a tropical tree which is grown with MATLAB allowed us to accelerate our research mostly in the wet tropical forest climate countries work, costs, reduce development time and deliver such as Ivory Coast, Nigeria, Brazil and Malaysia. better cocoa products[21]. The three varieties are Trinitarios Forasteros, and II. DESCRIPTION OF A GREEN HOUSE Criollos; but Criollos has become negligible in world EFFECT SOLAR DRYER trade. Cocoa is used in the production of milk The initial cost of a solar drying system can be chocolate, chocolate bars, cocoa powder, cosmetics further reduced by using a Green House Effect(GHE) and pharmaceutical products. The cocoa shells are mechanism since the function of solar collector unit used for stock feed and manure. It is also a source of can be substituted by transparent structure which also theobromine, vitamin D and shell fat. The pod simultaneously function as the drying chamber . The contains rich in potash and is used for soap entire wall is made of transparent materials such as production. Then, after harvesting of ripe cocoa pods, fiberglass, UV stabilized plastic or polycarbonate fresh cocoa beans are fermented for 5-7 days and sheets. The transparent sheets are fixed on steel frame dried immediately after fermentation to safe moisture support or pillars with bolts and nuts and rubber level of 7.5% (wet basis). At these stages the cocoa packing to prevent humid air leaking into the beans undergo various chemical and biochemical chamber other than those introduced from the changes that form the necessary flavour precursors opening of the inlet. Blackened steel plates is needed during processing. Drying is usually carried provided to enhanced solar radiation absorption out using natural sun drying. The solar powered within the structure and are located either on the cocoa bean dryer has advantage over the traditional upper section of the structure or at both sides near the method of drying because it brings more hygienic wall. Based on the type of commodity to be dried, way of drying cocoa beans in lesser time, with less cabinets or drying bin the racks can be placed at the foreign materials. center section of the transparent structure so that maximum access to drying air can be obtained. Inlet and exhaust fan are placed at proper position within the structure to ensure even distribution of the drying air within the chamber. can be installed. Whenever necessary, auxiliary heating system using kerosene stove with heat exchanger unit can also be installed.
Fig 1: Cocoa beans. In this work, the technological ways by which the green house type of solar dryer is used in drying cocoa beans is modeled and simulated using MATLAB programming. The software for modeling and simulation was MATLAB R2010a. With a
Pentium IV that had processor speed of 2.0 GHz, Fig 2: The greenhouse solar dryer. RAM of 2.O GB and hard disk drive of 520 GB. III. GREEN HOUSE EFFECT SOLAR DRYER MATLAB was selected as the modeling and A solar dryer with greenhouse as a collector is shown simulation software because it produces immediate in Fig.3. It consists of a greenhouse of length 50 m, access to good performance of numerical computing. as a collector linked to a wooden stack chamber. The The functionality of MATLAB is extended with solar dryer has trays stacked inside a wooden shed. interactive graphical capability for creating images, Trays of size 2 m x 2 m are fixed in the wooden surfaces, plots and volumetric representation. chamber to spread cocoa beans. The fan and plastic Furthermore, toolbox algorithms enhance MATLAB film together forms an efficient solar collector system functionality in domains such as signal and image that shows no need of separate collector unit, which
IJAET/Vol. IV/ Issue II/April-June, 2013/24-27 M. Manoj et al., International Journal of Advanced Engineering Technology E-ISSN 0976-3945 can increase the air temperature inside the where h 1,h 2,h 3 and τ are the steps of discretization greenhouse by about 250C. Heated air inside the with respect to x,y,z,t. The equation 3 has the greenhouse passes through the trays stacked in the numerical scheme which is the Crank-Nicholson wooden chamber. With respect to obtain a regular air method of the 3-D conduction equation is an implicit flow through the trays, a fan is placed on the rear side numerical scheme because the values at the previous of the stack chamber. For practical purpose of time step which are not readily available. This needs loading, the size of the dryer shed is fixed at 2 m3. In us to solve a set of simultaneous linear equations at order to avoid saturation of the outlet air and to keep every time step. The Crank-Nicholson method is the water gradient of the cocoa beans small, the superior to finite difference scheme, because of length of the shed is maintained at 2 m. It is observed accuracy, stability and convergence [19]. The that recycling of air is not financially viable in this simulated graph of equation 3 is shown in figure 4 type of dryer. and 5 explains the heat conduction mechanism during drying of the beans. V. MATHEMATICAL MODELING A mathematical model was developed for foretelling the performance of this type of green house effect solar dryer. 1. Mass of water to be lost from the product. The mass of water to be lost from the product is, 1 where
Fig 3: 2D of Green House Solar Dryer. mw = Mass of water loss IV. EQUATIONS TO SOLVE PDE IN PDE mc = Mass of product to be dried TOOL BOX OF MATLAB wi = Initial moisture content The system was assumed to be in a steady flow 0 process and thus the mass flow rate of dry air remains constant during the entire process. The numerical solution of Partial Differential Equations is a topic of wf = Final moisture content great importance in science and engineering because 2. The mass flow rate of air. of many applications. Finite Volumes, Finite The mass flow rate of air is, Differences, Finite Elements, Boundary Elements are among the most valuable numerical tools that we can where Air flow rate=Air flow x Drying area use in order to approximate the theoretical solution Specific volume is obtained from psychometric chart. with a numerical one. Suppose that we have to solve 3. The amount of moisture removed per hour. the 1-D (one-dimensional) conduction equation. The amount of moisture removed per hour is, (1) We consider the grid of the points as a where discretization of the continuous space of x,t of R 2 HRI = Humidity Ratio Increase where the function f(i 1,i 2) which approximates the HRA= Humidity Ratio of Air f(x,t). These finite difference scheme suffers from 4. The approximate time for the cocoa beans to be convergence problems, errors and instability, dried using the green house solar dryer. therefore another better method the so called Crank- The drying time is calculated using the formula Nicholson method is applied. The Crank-Nicholson method for the general case of the 3-D (three- Where mw=Mass of water loss dimensional) conduction equation is applied to the MR=Amount of moisture removed parabolic equation: 5. Pickup efficiency. (2) The pickup efficiency is given by ℎ ℎ A point that does not belong to the grid of the points ℎ ℎ (i 1,i 2,i 3,i 4) is considered. It is the at where this point we approximate to numerical scheme ho =absolute humidity of air leaving the drying chamber below: hi = absolute humidity of air entering the drying chamber h = adiabatic saturation humidity of the air entering the a dryer. VI. 3D MODELING OF GREEN HOUSE 1−1 2 3 4 1 1 2 3 4−2 1 2 3 4 1ℎ12 SOLAR DRYER 1 2−1 3 4 1 2 1 3 4−2 1 2 3 4ℎ22 1 2−1 3 4 1 1 1 2 3 4 1 −2 1 2 3 4 1ℎ22 1 2 3−1 4 1 2 3 1 4−2 1 2 3 4ℎ32 1 2 3−1 4 1 1 2 3 1 4 1 −2 1 2 3 4 1ℎ32 1 2 3 4 1 − 1 2 3 4 (3)
Fig 4: 3D modeling of green house dryer in ProE. IJAET/Vol. IV/ Issue II/April-June, 2013/24-27 M. Manoj et al., International Journal of Advanced Engineering Technology E-ISSN 0976-3945 VII. RESULTS AND DISCUSSION In MATLAB the partial differential equations (PDE) Toolbox was used to build system of equations to model heat conduction of drying cocoa beans from Crank-Nicholson method and obtaining numerical approximation for the solution and the results as shown in the fig.5. The direction of heated airflow is indicated as red arrows. The pink colour indicates evaporated moisture and blue and green as equilibrium moisture.
Fig 8: Drying Rate from 50% to 7% Moisture . The simulated graph in fig.9 shows the drying rate of the cocoa beans with initial moisture content of 60% to dried beans of moisture 7% of the weight.
Fig 5: Simulation in PDE Toolbox a) DEHYDRATION RATES FROM MATLAB Fig 9: Drying Rate from 60% to 8% Moisture. SIMULATION The simulated graph in fig.10 shows the drying rate The parabolic graph of three-dimensional heat of the cocoa beans with initial moisture content of conduction simulation for drying cocoa beans in the 70% to dried beans of moisture 7% of the weight. dryer from the Crank-Nicholson method is shown in fig.6.
Fig 10: Drying Rate from 70% to 10% Moisture. c) Combined drying rates The simulated graph in fig.11 shows the combined drying rate of the cocoa beans with initial moisture content of 50%, 60% and 70% of the weight. The rose colour indicates the initial moisture of 70% and Fig 6: Crank-Nicholson 3-D Dehydration of Cocoa final moisture of 10% of the weight after drying. The Beans. green colour indicates the initial moisture of 60% to Fig.7 shows the dehydration curve for simulated final moisture 8% of the weight after drying. The cocoa beans drying. The section of the straight line blue colour indicates the 50% initial moisture and (A, B) represents the constant temperature till the final moisture 7% of the weight after drying. X max latent heat of vaporization of water is reach. The indicates the total time of drying of beans 84 hours. Y falling curve (B, C), shows the rate of water min indicates the moisture at 7% of cocoa beans. evaporated with respect to temperature, to a This represents that the cocoa beans with moisture corresponding critical moisture content of 7.5%. content of 50% are the perfect choice for this dryer. Therefore, the dryer performed at it optimal range and dried beans within 7 days to a moisture content of 7% to the weight of the beans.
Fig 7: Dehydration Rates in Solar Dryer. b) Drying rates The simulated graph in fig.8 shows the drying rate of the cocoa beans with initial moisture content of 50% to dried beans of moisture 7% of the weight. Fig 11: The Combined Drying Rate of Cocoa Beans.
IJAET/Vol. IV/ Issue II/April-June, 2013/24-27 M. Manoj et al., International Journal of Advanced Engineering Technology E-ISSN 0976-3945 VIII. CONCLUSION 18. Nicolas Roux, Daniel Jung, Jerome Pannejon, Cyrille The MATLAB coding was developed for the Lemoine(2010), “Modelling of the solar sludge drying process solia”, 20 th European Symposium on Computer simulation of solar dryer for drying cocoa beans from Aided Process Engineering – ESCAPE20. the Crank-Nicholson method using PDE Toolbox in 19. Nikos E. Mastorakis, “An extended Crank-Nicholson MATLAB and the simulation is done in MATLAB method and its Application in the Solution of Partial version 10a.From the simulation results it is Differential Equations: 1-D and 3-D Conduction Equations”, Proceedings of the 10 th WSEAS Intern. concluded that the dryer performed at it optimal Conf. on Applied Mathematics, Dallas, Texas, USA, range and dried beans within 7 days to a moisture November 1-3, 2006. content of 7% to the weight of the bean. The drying 20. Nikrooz Bagheri, Sayed Saeed Mohtasebi(2012), processes of greenhouse solar dryer were enhanced “Simulation and control of fan speed in a solar dryer for optimization of energy efficiency”, International by the heated air at very low humidity. It is the most Journal of Agricultural Engg. Vol. 14, No.157. hygienic drying way; cocoa processing companies 21. Palm W.J “Introduction to MATLAB 6 for Engineers”, need not blow ambient air through beans to remove McGraw-Hill, New York, pp.228-296. foreign materials. Hence reducing time, production 22. Ryan Blair, George Calota,Adam Crossman,Finlay Drake & Kevin O'Keefe(2007),“Design of a Solar cost and cocoa dried in the dryer would give cocoa of Powered Fruit and Vegetable Dryer”. Northeastern grades one and two which meet international University. standard. 23. Shahab Abdulla, Paul Wen, Richard Landers and B. F. REFERENCES Yousif, “Fruit drying process: Analysis, modeling and simulation”,Scientific Research and Essays Vol. 6(23), 1. Abano E. E. and Sam-Amoah L. K., “Effects of pp. 4915-4924, October, 2011. different pretreatments on drying characteristics of 24. Tawon Usuba, Lamul Wiset, “Thin layer solar drying banana slices”, ARPN Journal of Engineering and characteristics of silkworm pupae” ,Food and Applied Sciences. VOL. 6, NO. 3, 2011. bioproducts processing 8 8 ( 2 0 1 0 ) 149–160. 2. Amer BMA, Hossain MA, Gottschalk K (2010). Design 25. Tunde-Akintunde T.Y., T.J. Afolabi, Akintunde B.O., and performance evaluation of a new hybrid solar dryer “Influence of drying methods on drying of bell-pepper”, for banana. Ener. Convers. Manage., 51(4): 813-820. Journal of Food Engineering 68 (2005) 439–442. 3. Aware R. and Thorat B.N.,“ Solar Drying: 26. Wang, D. C.; Fon, D. S.; Fang, Wei; Sokhansanj, S. Fundamentals, Applications and Innovations”, 2004, Development of a visual method to test the range Publications from TPR Group (2005 - Present). of applicability of thin layer drying equations using 4. Ayensu .A, “Dehydration of food crop using a Solar MATLAB tools. Drying Technology 2004,22(8). Dryer with convective heat flow, Great Britain, pp 121- 126, 1997. 5. Azad.E(2008), “Design and experimental study of solar agricultural dryer for rural area” Solar Energy Laboratory, Iranian Research Organization for Science & Technology (IROST), 71 Forsat Avenue, Tehran, Iran. 6. Bahnasawy A.H., Shenana M.E., “A mathematical model of direct sun and solar drying of some fermented dairy products” Journal of Food Engineering 61 (2004) 309–319. 7. Cengel Y.A, Boles M.A, “Thermodynamics an Engineering Approach” McGraw-Hill Companies, USA, pp 104-111 and 724-732,1998. 8. Cristiana Brasil Maia , Andre Guimaraes Ferreira, Luben Cabezas-Gomez, Sergio de Morais Hanriot & Tiago de Oliveira Martins(2012), “Simulation of the airflow inside a hybrid dryer”, International Journal of Agricultural Engg. Vol10Issue3. 9. Fuller.R.J, “Solar drying - a technology for sustainable agriculture and food production”, Encyclopedia of Life Support Systems (EOLSS).Solar energy conversion and photoenergy systems - Solar Drying - A Technology For Sustainable Agriculture And Food Production. 10. GEDA-Gujarat Energy Development Agency, 2003, www.geda.com . 11. Gikuru Mwithiga, Stephen Njoroge Kigo,“Performance of a solar dryer with limited sun tracking capability”, Journal of Food Engineering 74 (2006) 247–252. 12. Inci Turk Togrul , Dursun Pehlivan, “Mathematical modelling of solar drying of apricots in thin layers”, Journal of Food Engineering 55 (2002) 209–216. 13. Kituu G.M. , Shitanda.D , Kanali.C.L. , Mailutha J.T., “Thin layer drying model for simulating the drying of tilapia fish in a solar tunnel dryer”, Journal of Food Engineering 98 (2010) 325–33. 14. Lyes Bennamoun, Azeddine Belhamri, “Numerical simulation of drying under variable external conditions: Application to solar drying of seedless grapes”, Journal of Food Engineering 76 (2006) 179–187. 15. McCable W.L, Smith J.C, Harriott P,” Unit Operation of Chemical Engineering, McGraw-Hill, New York, pp.707-743 and 660-683. 16. Mohamed Ayoub Ismail, W. Luecke(2009), “Design and construction of a solar dryer for mango slices”, Energy Research Institue, Ministry of Science and Technology, Khartoum, Sudan. 17. Nandi P., Solar Thermal Energy Utilization in Food Processing Industry in India, Pacific Journal of Science and Technology, 2009, 10(1), p. 123-131.
IJAET/Vol. IV/ Issue II/April-June, 2013/24-27