Summary
System simulation is a valuable approach to the design of refrigerating and air-conditioning appliances. In the paper, a refrigeration system simulation method with ANN (artificial neural network)-based component models was developed. At first, ANN is used to construct the component model base instead of the traditional modelling method. Proper inputs and outputs of ANN component models are selected according to the traditional first-principle models and system simulation algorithm. Then the trained ANN component models are substituted into the traditional system simulation algorithm for system performance prediction. Finally, a case study shows that high precision is reached in component modelling and system performance prediction. Therefore, the method is fast and accurate for refrigeration system design.
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Details
- Original title: Refrigeration system simulation with ANN-based component models.
- Record ID : 2004-1106
- Languages: English
- Source: 21st IIR International Congress of Refrigeration: Serving the Needs of Mankind.
- Publication date: 2003/08/17
Links
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Indexing
- Themes: Compression systems
- Keywords: Artificial neural network; Compression system; Process; Modelling
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- Author(s) : TUMIALAN J. A. B., HERNANDEZ O. S. M., BANDARRA FILHO E. P., et al.
- Date : 2007/07/21
- Languages : English
- Source: ICR 2007. Refrigeration Creates the Future. Proceedings of the 22nd IIR International Congress of Refrigeration.
- Formats : PDF
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A physics-constrained data-driven modeling appr...
- Author(s) : MA J., QIAO H., LAUGHMAN C. R.
- Date : 2024/07/17
- Languages : English
- Source: 2024 Purdue Conferences. 20th International Refrigeration and Air-Conditioning Conference at Purdue.
- Formats : PDF
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Modeling of refrigerant flow through adiabatic ...
- Author(s) : LI Z., SHAO L., YANG L., et al.
- Date : 2015/08/16
- Languages : English
- Source: Proceedings of the 24th IIR International Congress of Refrigeration: Yokohama, Japan, August 16-22, 2015.
- Formats : PDF
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Fault detection and diagnosis of a refrigeratio...
- Author(s) : LIANG Q., HAN H., CUI X., et al.
- Date : 2015/08/16
- Languages : English
- Source: Proceedings of the 24th IIR International Congress of Refrigeration: Yokohama, Japan, August 16-22, 2015.
- Formats : PDF
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Developing computationally efficient artificial...
- Author(s) : HAIDER M., ELBEL S.
- Date : 2022
- Languages : English
- Source: 2022 Purdue Conferences. 19th International Refrigeration and Air-Conditioning Conference at Purdue.
- Formats : PDF
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