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Evaporator modeling - A hybrid approach

Author

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  • Ding, Xudong
  • Cai, Wenjian
  • Jia, Lei
  • Wen, Changyun

Abstract

In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis.

Suggested Citation

  • Ding, Xudong & Cai, Wenjian & Jia, Lei & Wen, Changyun, 2009. "Evaporator modeling - A hybrid approach," Applied Energy, Elsevier, vol. 86(1), pages 81-88, January.
  • Handle: RePEc:eee:appene:v:86:y:2009:i:1:p:81-88
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    Citations

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    Cited by:

    1. Chen, Can & Cai, Wenjian & Giridharan, Karunagaran & Wang, Youyi, 2014. "A hybrid dynamic modeling of active chilled beam terminal unit," Applied Energy, Elsevier, vol. 128(C), pages 133-143.
    2. Silvia Macchitella & Gianpiero Colangelo & Giuseppe Starace, 2023. "Performance Prediction of Plate-Finned Tube Heat Exchangers for Refrigeration: A Review on Modeling and Optimization Methods," Energies, MDPI, vol. 16(4), pages 1-30, February.
    3. Wang, Xinli & Cai, Wenjian & Lu, Jiangang & Sun, Youxian & Ding, Xudong, 2013. "A hybrid dehumidifier model for real-time performance monitoring, control and optimization in liquid desiccant dehumidification system," Applied Energy, Elsevier, vol. 111(C), pages 449-455.
    4. Shen, Suping & Cai, Wenjian & Wang, Xinli & Wu, Qiong & Yon, Haoren, 2016. "Hybrid model for heat recovery heat pipe system in Liquid Desiccant Dehumidification System," Applied Energy, Elsevier, vol. 182(C), pages 383-393.
    5. Om Prakash Verma & Suryakant & Gaurav Manik, 2017. "Solution of SNLAE model of backward feed multiple effect evaporator system using genetic algorithm approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 63-78, March.
    6. Zhao, Lei & Cai, Wenjian & Ding, Xudong & Chang, Weichung, 2013. "Model-based optimization for vapor compression refrigeration cycle," Energy, Elsevier, vol. 55(C), pages 392-402.
    7. Shen, Suping & Cai, Wenjian & Wang, Xinli & Wu, Qiong & Yon, Haoren, 2017. "Investigation of liquid desiccant regenerator with fixed-plate heat recovery system," Energy, Elsevier, vol. 137(C), pages 172-182.

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