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• W2133921276 abstract "Heat recovery wheels represent key components in air handling units (AHU) that can be used in commercial and industrial building air-conditioning-systems for energy saving. For example, in health facilities, heat transfer process is to be applied in air-conditioning systems for heat recovery of the exhaust (return) air from the patient's room without contamination. Thus, heat recovery wheels are much suitable for such applications. Heat recovery wheels are also known as heat conservation wheels. A conservation wheel consists of a rotor with permeable storage mass fitted in a casing, which operates intermittently between two sections of hot and cold fluids. The rotor is driven by a low-speed electric motor. Thus, the two streams of exhaust and fresh air are alternately passed through the wheel. The present investigation considers computationally the different parameters that affect the operation of heat recovery wheels. These parameters signify actual operating conditions such as flow velocity, shape of cross-section of flow path, and wall material. Moreover, both the artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques were utilized to predict the critical characteristics of the heat exchange system. These artificial intelligence techniques use the present computational results as training and verification data." @default.
• W2133921276 created "2016-06-24" @default.
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• W2133921276 date "2015-01-01" @default.
• W2133921276 modified "2023-09-27" @default.
• W2133921276 title "Computational and Artificial Intelligence Study of the Parameters Affecting the Performance of Heat Recovery Wheels" @default.
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• W2133921276 doi "https://doi.org/10.11648/j.ajee.s.2015030401.16" @default.
• W2133921276 hasPublicationYear "2015" @default.
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