Psychrometric Analysis of an Open-Loop Batch-Type Heat Pump Drying Process

Fernando, Arachchige Jayaruwani and Amaratunga, Kahawaththage Sanath Priyantha (2023) Psychrometric Analysis of an Open-Loop Batch-Type Heat Pump Drying Process. Asian Journal of Agriculture and Allied Sciences, 6 (1). pp. 61-68.

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Abstract

Psychrometric processes are vital in agriculture and food processing as they contribute to storage and preservation, drying and dehydration, quality control, cold chain management, process optimization, food safety, and the maintenance of sensory attributes. By effectively managing temperature and humidity, these processes ensure product quality, extend shelf life and enhance the safety of agricultural and food products. Further, the psychrometric equations can be applied to study the drying behavior of hot-air dryers. Therefore, this study aimed to develop models to analyze the psychrometric properties of batch-type, open-loop heat pump drying systems for coffee beans. Coffee beans (370 kg) at 70.01±1.26% (w.b.) moisture content were dried in an open-loop batch-type heat pump dryer. The weight reduction of coffee beans in the drying chamber and the amount of condensed moisture at the evaporator were measured. Two models for condensation and evaporation processes were developed and validated with experimental data. The models indicated that the humidity ratio is essential in developing models for condensation and evaporation processes in heat pump dryers.

Further, the model-validated results showed that the developed models could be used to analyze the air properties in an open-loop heat pump drying system, especially in the drying chamber and the evaporator. These models would support researchers and engineers in making informed decisions to optimize system design, improve energy efficiency, and implement measures that contribute to more effective and environmentally sustainable drying operations.

Item Type: Article
Subjects: Journal Eprints > Biological Science
Depositing User: Managing Editor
Date Deposited: 22 Nov 2023 05:20
Last Modified: 22 Nov 2023 05:20
URI: http://repository.journal4submission.com/id/eprint/3188

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