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Heat Pump Dryer Design Optimization Algorithm

1
Centro Federal de Educação Tecnológica de Minas Gerais, Belo Horizonte 30421-169, Brazil
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Mechanical Technology Department, Polytechnic Institute of Bragança, 5300-252 Bragança, Portugal
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Departamento Acadadêmico de Mecânica, Universidade Tecnológica Federal do Paraná, Ponta Grossa 84017-220, Brazil
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Team4cooling, 2795-898 Terrugem, Portugal
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Department of International Economic Relations, Lutsk National Technical University, 43000 Lutsk, Ukraine
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Centre for Renewable Energy Research—INEGI, 4200-465 Porto, Portugal
*
Author to whom correspondence should be addressed.
Inventions 2019, 4(4), 63; https://doi.org/10.3390/inventions4040063
Received: 16 September 2019 / Revised: 3 October 2019 / Accepted: 4 October 2019 / Published: 10 October 2019
(This article belongs to the Special Issue Computational Intelligence in Agriculture and Natural Resources)
Drying food involves complex physical atmospheric mechanisms with non-linear relations from the air-food interactions, and those relations are strongly dependent on the moisture contents and the type of food. Such dependence makes it complex to design suitable dryers dedicated to a single drying process. To streamline the design of a novel compact food-drying machine, a heat pump dryer component design optimization algorithm was developed as a subprogram of a Computer Aided Engineering tool. The algorithm requires inputting food and air properties, the volume of the drying container, and the technical specifications of the heat pump off-the-shelf components. The heat required to dehumidify the food supplied by the heat exchange process from condenser to evaporator, and the compressor’s requirements (refrigerant mass flow rate and operating pressures) are then calculated. Compressors can then be selected based on the volume and type of food to be dried. The algorithm is shown via a flow chart to guide the user through three different stages: Changes in drying air properties, heat flow within dryer and product moisture content. Example results of how different compressors are selected for different types of produces and quantities (Agaricus blazei mushroom with three different moisture contents or fish from Thunnini tribe) conclude this article. View Full-Text
Keywords: algorithm; heat-pump; drying; food; design; optimization algorithm; heat-pump; drying; food; design; optimization
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Andrade, B.; Amorim, I.; Silva, M.; Savosh, L.; Frölén Ribeiro, L. Heat Pump Dryer Design Optimization Algorithm. Inventions 2019, 4, 63.

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