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데이터 학습 기반 열역학 해석모델을 이용한 히트펌프 건조기 시스템 모델 개발
이강욱(Kang Wook Lee),이진욱(Jin Wook Lee),황윤제(Yoon Jei Hwang),박만수(Mansu Park),오세기(Sai Kee Oh) 대한설비공학회 2022 대한설비공학회 학술발표대회논문집 Vol.2022 No.6
This study integrates and verifies a numerical model and a data learning model by implementing a digital mockup of a heat pump dryer from a model-based design perspective. The refrigerant cycle of the heat pump dryer was calculated by solving the momentum and energy conservation equations, and the drum part was predicted through the artificial neural network(ANN) learned from the accumulated experimental data. In order to verify the system model that integrates the refrigerant cycle and drum model in the Dymola<SUP>Ⓡ</SUP> environment, the dynamic characteristics data of the dryer for 2 - 8 kg drying load conditions were acquired. As a result of verification of the analysis model, a drying time error of less than 6% was shown for a low drying load of less than 5 kg, but an error of 14% was shown for a load of 8 kg.