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CFD-Based Optimization of a Diesel Engine Waste Heat Recycle System

Da Li, Guodong Zhang, Ke Sun*, Shuzhan Bai, Guoxiang Li*

School of Energy and Power Engineering, Shandong University, Jinan, 250061, China

* Corresponding Authors: Ke Sun. Email: email; Guoxiang Li. Email: email

(This article belongs to the Special Issue: Recent Advances in Fluid Mechanics and Thermal Sciences II)

Fluid Dynamics & Materials Processing 2023, 19(6), 1479-1493. https://doi.org/10.32604/fdmp.2023.022634

Abstract

A dedicated heat exchanger model is introduced for the optimization of heavy-duty diesel engines. The model is a prerequisite for the execution of CFD simulations, which are used to improve waste heat recovery in these systems. Several optimization methods coupled with different types of working fluids are compared in terms of exergy efficiency and heat exchanger complicity. The three considered optimization methods all lead to significant improvements in the R245fa and R1233zd systems with a comparatively low evaporation temperature. The optimal R245fa system has the highest efficiency increase (77.49%). The cyclopentane system displays the highest effi- ciency among the optimized ORC (Organic Rankine Cycle) systems, yet achieved by using a much heavier evaporator HEC (Heat Exchanging Core). In contrast, the 96.84% efficiency increase for the optimized R1233zd is achieved with only 68.96% evaporator weight.

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APA Style
Li, D., Zhang, G., Sun, K., Bai, S., Li, G. (2023). Cfd-based optimization of a diesel engine waste heat recycle system. Fluid Dynamics & Materials Processing, 19(6), 1479-1493. https://doi.org/10.32604/fdmp.2023.022634
Vancouver Style
Li D, Zhang G, Sun K, Bai S, Li G. Cfd-based optimization of a diesel engine waste heat recycle system. Fluid Dyn Mater Proc. 2023;19(6):1479-1493 https://doi.org/10.32604/fdmp.2023.022634
IEEE Style
D. Li, G. Zhang, K. Sun, S. Bai, and G. Li "CFD-Based Optimization of a Diesel Engine Waste Heat Recycle System," Fluid Dyn. Mater. Proc., vol. 19, no. 6, pp. 1479-1493. 2023. https://doi.org/10.32604/fdmp.2023.022634



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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