组合发动机内复杂换热结构热流性能评估与快速预测方法

孙靖阳; 毛红威; 陈盛林; 罗盛浓; 张欣宇; 刘金鑫

doi:10.13224/j.cnki.jasp.20250608

组合发动机内复杂换热结构热流性能评估与快速预测方法

doi: 10.13224/j.cnki.jasp.20250608

1.
西安交通大学机械工程学院，西安 710049
2.
西安交通大学未来技术学院，西安 710049

基金项目: 国家自然科学基金青年项目（52306025）；中国博士后科学基金面上项目（2023M732763）；陕西省重点研发计划（2025ZG-JBGS-006）

详细信息

作者简介:
孙靖阳（1998-），男，博士生，研究方向为发动机内复杂流态与热管理系统。E-mail：syrupinnight@163.com

通讯作者:
毛红威（1993-），男，副研究员，博士，研究领域为预冷组合发动机高效换热技术。E-mail：maohongwei@xjtu.edu.cn

中图分类号: V236
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出版历程
- 收稿日期: 2025-12-30
- 网络出版日期: 2026-03-27

Thermal-hydraulic performance assessment and rapid prediction of complex heat-exchanger in combined aero engines

1.
School of Mechanical Engineering，Xi’an Jiaotong University，Xi’an 710049，China
2.
School of Future Technology，Xi’an Jiaotong University，Xi’an 710049，China

摘要

摘要:
三周期极小曲面（triply periodic minimal surface，TPMS）结构凭借其卓越的热-流耦合传输性能，被视为新一代航空航天推进系统内高性能热交换器技术革新的理想候选结构。TPMS结构固有的几何复杂性显著增加了数值求解的资源消耗，已成为其工程化设计与应用的关键制约。针对孔隙率为60%～80%的TPMS结构开展了全三维数值模拟，系统揭示了不同孔隙率构型在极端工况下的热流性能，进而提出了耦合功质比的性能评价指标（weight-aware performance evaluation criterion，WPEC）。研究结果表明：75%孔隙率的TPMS结构在该指标下展现出最优的综合性能，其WPEC值可达2.5。基于重叠网格法与粒子迹线追踪法，构建了面向TPMS结构的宏观性能-微观流场协同快速预测模型，实现了兼具精度与计算效率的快速性能评估，其计算耗时降低90%以上，针对总换热量、冷流压降、热流压降的平均预测误差分别为3.91%、4.62%、5.42%。
- 三周期极小曲面（TPMS） /
- 预冷器 /
- 组合动力发动机 /
- 快速预测 /
- 重叠网格法 /
- 性能评估
Abstract:
The inherent geometric complexity of triply periodic minimal surface (TPMS) significantly increases the computational consumption of numerical simulations, which has become a critical constraint on their engineering design and application. This study conducted full three-dimensional numerical simulations on TPMS structures with porosities ranging from 60% to 80%, systematically revealing the thermal-hydraulic performance of different porosity configurations under extreme operating conditions, and proposed a performance evaluation criterion coupling the power-to-weight ratio (WPEC). The results demonstrated that the TPMS structures with 75% porosity exhibited the optimal comprehensive performance under this criterion, achieving a WPEC value of 2.5. Furthermore, based on the overlapping mesh method and particle trajectory tracking method, a rapid prediction model for TPMS structures that coupled macroscopic performance with microscopic flow fields was constructed, achieving accurate performance evaluation with high computational efficiency. The computational time was reduced by over 90%, while the average prediction errors for total heat transfer, cold-side pressure drop, and hot-side pressure drop were 3.91%, 4.62%, and 5.42%, respectively.
- triply periodic minimal surface (TPMS) /
- precooler /
- combined aero engines /
- rapid prediction /
- overlap mesh method /
- performance assessment

HTML

图 1 Gyroid型TPMS单晶胞

Figure 1. Gyroid TPMS unit cell

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图 2 TPMS换热结构

Figure 2. TPMS structure for heat transfer

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图 3 计算域结构与重叠网格划分

Figure 3. Computational domain and overlap mesh generation

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图 4 网格无关性验证

Figure 4. Mesh independence verification

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图 5 重叠网格法快速预测逻辑

Figure 5. Rapid prediction logic of the overlap mesh method

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图 6 无质量粒子入射与流线分布

Figure 6. Massless particle incidence and streamline distribution

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图 7 不同孔隙率结构内Re_c与温差分布特性

Figure 7. Distribution characteristics of Re_c and temperature difference within structures of varying porosity

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图 8 不同孔隙率结构内总换热量分布特性

Figure 8. Distribution characteristics of total heat transfer within structures of varying porosity

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图 9 不同孔隙率结构内冷流压降随Re_c变化特性

Figure 9. Characteristics of Re_c and pressure drop of cold fluid within structures of varying porosity

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图 10 不同孔隙率结构内PEC与WPEC变化特性

Figure 10. Characteristics of PEC and WPEC within structures of varying porosity

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图 11 冷流温度对比

Figure 11. Comparison of cold fluid temperatures

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图 12 热流温度对比

Figure 12. Comparison of hot fluid temperatures

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图 13 冷流压降对比

Figure 13. Comparison of cold fluid pressure drops

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图 14 热流压降对比

Figure 14. Comparison of hot fluid pressure drops

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表 1 不同孔隙率下Gyroid晶胞的结构参数

Table 1. Structural parameters of Gyroid unit cell under varying porosity

孔隙率φ/%	晶胞周期长度l/mm	总换热面积A_htf/mm²	比表面积ε/（1/mm）	水力直径D/mm
60	10.1	40499.2	0.63	3.78
65	11.7	36442.7	0.57	4.57
70	13.8	32418.4	0.51	5.53
75	16.8	28555.0	0.47	6.72
80	21.5	24012.7	0.38	8.54

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表 2 数值模拟计算边界条件

Table 2. Boundary conditions for numerical simulation

流体	温度/K	压力/MPa	流速/（m/s）
氦气	256.68	6.0	2.03
			2.29
			2.55
			2.80
			3.06
燃气	1187.35	0.5	2.47
			3.71
			4.95
			6.18
			7.42

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表 3 不同质量流量工况对应边界

Table 3. Boundary conditions for different flow rate cases

质量流量工况/%	冷流入口流速/（m/s）	热流入口流速/（m/s）
100	3.06	7.42
92	2.80	6.18
83	2.55	4.95
75	2.29	3.71
67	2.03	2.47

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表 4 重叠网格快速预测模型误差分布

Table 4. Error distribution of the overlap mesh rapid prediction model %

孔隙率	质量流量工况	总换热量误差	冷流压降误差	热流压降误差
60	100	3.50	4.11	−5.70
	92	3.83	3.01	−4.86
	83	4.16	1.89	−2.60
	75	4.32	0.76	2.20
	67	4.01	−0.16	11.69
65	100	5.20	−7.14	3.87
	92	5.59	−8.12	3.99
	83	5.99	−9.07	5.11
	75	6.23	−9.92	8.25
	67	5.79	−10.63	14.10
70	100	3.80	1.02	1.74
	92	4.43	0.10	2.02
	83	5.15	−0.80	3.18
	75	5.85	−1.54	6.10
	67	5.99	−2.21	12.08
75	100	1.26	−7.48	8.57
	92	−2.25	−6.70	7.97
	83	3.45	−5.95	6.40
	75	−2.25	−6.70	7.97
	67	−1.26	−7.48	8.57
80	100	0.82	−6.17	1.68
	92	−0.47	−5.15	1.69
	83	−2.03	−4.18	1.49
	75	−3.88	−3.13	0.49
	67	−6.30	−2.09	−3.22

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表 5 快速预测模型性能分析

Table 5. Rapid prediction model performance analysis

指标	孔隙率/%	全结构数值模拟	快速预测模型
网格数量/万	60	472	62
	65	405
	70	327
	75	292
	80	223
前处理耗时/h	60	≈3	≈0.5
	65	≈3
	70	≈2
	75	≈2
	80	≈1.5
湍流模型		Realizable k-ε	无需计算湍流
计算耗时/h	60	≈12	≈0.5
	65	≈10
	70	≈8
	75	≈8
	80	≈7

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