EXPERIMENTAL INVESTIGATION AND NEURAL NETWORK PREDICTION OF THE PERFORMANCE OF A MIXED MODE SOLAR DRYER FOR COCONUT

Journal Title: JOURNAL OF ADVANCES IN CHEMISTRY - Year 2016, Vol 12, Issue 25

Abstract

The shelf life of agricultural food products may be enhanced by reducing their moisture contents, by means of a drying process. The present work aims at drying coconut yielding copra. This paper presents the design, analysis of a mixed mode solar dryer for food preservation and energy saving. In the mixed mode solar dryer, the drying cabinet absorbs solar energy directly through the transparent roof and during the same time the heated air from a solar collector is passed through a tray. Various measurements like solar radiation, mass flow rate, and moisture content and relative humidity have been observed. From previous literature four different models (Newton, Page, Henderson & Pabis and Wang & Singh) are chosen for testing the performance of mixed mode solar dryer. Selected models are evaluated by using EMD, ERMS, R2 and 𝜒2 and it is concluded that page model is more suitable for the fabricated cabinet solar dryer at air flow rate 0.009Kg/s based on the experimental analysis. The direct radiant solar energy and a convective hot air stream dry the products, resulting in longer life for the products which are also free from impurities. The experimental results are utilized to evolve a suitable mathematical model, among the different models that are chosen, for copra. This will help in designing suitable dryers for actual users. Also, a multilayer neural network approach has been used to predict the performance of a mixed mode solar dryer for drying coconut. The simulation of neural network is based on the feed forward back propagation algorithm.

Authors and Affiliations

K. Kalidasa Murugavel, V. Subbian, R. Thirupathieswaran

Keywords

Related Articles

A novel electrical and mechanical MPPT for Solar Photovoltaic System at any climatic condition and sudden changes in the irradiance

Maximum power point tracking (MPPT) techniques are widely used in photovoltaic (PV) systems to make the best use of the PV panel power output by tracking frequently the maximum power point (MPP) which depends on panel’...

Steric and Polar Factors Affecting Heteroring Opening of 2-[2-carboxy-3,4,5,6-tetrachloro]phenyl-4H-3,1-Benzoxazin-4-one by Nitrogen and Carbon Nucleophiles

The behavior of 2-[2-carboxy-3,4,5,6-tetrachloro]phenyl-4H-3,1-Benzoxazin-4-  one towards Nitrogen nucleophiles and Carbon nucleophiles under Friedel–Crafts' reaction conditions has been investigated and steric versus...

Static and Dynamic Studies of Gasoline in View of its Octane Number and its Toxic Effect

Gasoline come primarily from petroleum cuts, it is the preferred liquid fuel in our lives. Two gasoline samples of octane numbers 91 and 95 from Saudi Arabia petrol stations were studied. This study was achieved at three...

CASCADED BOOST CONVERTER USING FUZZY AND SLIDING MODE CONTROL TO IMPROVE THE CAPABILITY OF GRID INTERACTED PV SYSTEMS

Switching dc to dc converters are mainly used to connect the distribution system with the output of renewable energy sources. The cascaded boost converters are controlled by the sliding mode control. This will not mainta...

Removal of crystal violate dye from aqueous solution by adsorption on mixture of activated carbon: A kinetic & equilibrium study

 The kinetics and equilibrium study of crystal violate dye adsorption on mixture of activated carbon (PWCAC) and (CSAC) was studied. The use of low cost ecofriendly adsorbent has been investigated as an ideal alternativ...

Download PDF file
  • EP ID EP653026
  • DOI 10.24297/jac.v12i25.4395
  • Views 134
  • Downloads 0

How To Cite

K. Kalidasa Murugavel, V. Subbian, R. Thirupathieswaran (2016). EXPERIMENTAL INVESTIGATION AND NEURAL NETWORK PREDICTION OF THE PERFORMANCE OF A MIXED MODE SOLAR DRYER FOR COCONUT. JOURNAL OF ADVANCES IN CHEMISTRY, 12(25), 5635-5644. https://europub.co.uk/articles/-A-653026