Research on the multi-objective optimization of regenerative cooling channel of SCRamjet based on NSGA-Ⅱ
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摘要:
超燃冲压发动机高马赫数飞行时，气动热载荷急剧增加，然而冷却剂携带量严格受限，发动机热结构冷却面临严峻挑战。对再生冷却通道优化设计，提高机载冷却剂热沉利用率，是缓解超燃冲压发动机冷却挑战的关键技术。着眼于超燃冲压发动机高热环境下冷却剂流量分配不合理、局部超温风险高等问题，提出沿发动机周向的通道高宽比、位置，以及沿轴向的通道连通结构位置、尺寸的同步设计和独立设计3种优化策略。以正癸烷作为典型碳氢燃料，在跨临界温区对再生冷却通道进行参数化建模，以加热面最大壁温和出口燃油温度相对偏差作为目标函数，基于非支配排序遗传算法NSGA-Ⅱ和RNFNN代理模型联合进行多目标优化设计，求解全局Pareto Front最优解解集。研究结果表明基于NSGA-Ⅱ的再生冷却通道多目标优化可有效优化冷却效果，在不增加冷却剂的前提下，降低热结构温度，缓解超燃冲压发动机冷却挑战。
Abstract:The aerodynamic thermal load increases sharply when SCRamjet is flying at high Mach number. But the coolant carrying capacity is strictly limited, and the cooling of engine thermal structure is faced with severe challenges. The key technology to alleviate the cooling challenge of SCRamjet engine is to optimize the structure of regenerative cooling channel and improve the utilization rate of onboard coolant heat sink. The study focused on the problems of unreasonable coolant flow distribution and high local overtemperature risk in SCRamjet engine high thermal environment. Three optimization strategies were proposed, including the aspect ratio and position of the channel along the engine circumference, and tsynchronous design and independent design of the position and size of the interconnection structure along the axial direction. Taking n-Decane as a typical hydrocarbon fuel, parametric modelling of regenerative cooling channels was performed in the supercritical temperature zone. The maximum wall temperature of heating surface and the relative deviation of outlet fuel temperature were taken as the objective function. The multi-objective optimization design was carried out based on NSGA-Ⅱ and RNFNN agent model, and the global Pareto Front optimal solution set was obtained. The results showed that the multi-objective optimization of regenerative cooling channel based on NSGA-Ⅱ can effectively optimize the cooling effect, reduce the thermal structure temperature and alleviate the cooling challenge of scramjet engine without increasing the coolant.
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Key words:
- multi-objective optimization /
- genetic algorithm /
- regenerative cooling /
- flow deviation /
- SCRamjet
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图 1 再生冷却通道优化模型示意图（单位：mm）
Figure 1. Schematic diagram of regeneration cooling channel optimization model （unit：mm）
图 6 RBFNN预测结果与CFD计算结果对比
Figure 6. Comparison of RBFNN prediction results with CFD calculation results
图 8 截面优化设计点的流量偏差系数
Figure 8. Flow deviation coefficient of the cross-section optimization design point
图 9 截面优化设计点的出口燃油温度分布
Figure 9. Distribution of the outlet fuel temperature at the cross-section optimized design point
图 10 截面优化设计点的最热通道中流体密度分布
Figure 10. Fluid density distribution in the hottest channel of the cross-section optimized design point
图 11 截面优化设计点的加热面壁温分布
Figure 11. Distribution of the heated surface wall temperature at the cross-section optimized design point
图 12 沿流向80 mm处周向截面温度分布
Figure 12. Circumferential cross-section temperature distribution at 80 mm along the flow direction
图 13 轴向ICS同步设计示意图（单位：mm）
Figure 13. Schematic diagram of ICS synchronous design along the axis （unit：mm）
图 14 初始模型沿程热侧近壁面流体密度分布
Figure 14. Fluid density distribution along the hot side near the wall of initial model
图 15 Case 1沿程热侧近壁面流体密度分布
Figure 15. Fluid density distribution along the hot side near the wall of Case 1
图 17 同步设计连通结构速度分布
Figure 17. Synchronously design the velocity distribution of the connected structure
图 18 ICS同步设计优化的流量偏差系数
Figure 18. Flow deviation coefficient for ICS synchronization design optimization
图 19 ICS同步设计优化的出口燃油温度分布
Figure 19. Optimization of the outlet fuel temperature distribution in ICS synchronization design
图 20 通道No.4沿程流体湍流动能分布
Figure 20. Turbulent kinetic energy distribution of fluid along channel No.4
图 21 ICS同步设计优化通道No.4沿程热侧壁温分布
Figure 21. ICS synchronization design optimization channel No.4 along-the-way hot sidewall temperature distribution
图 22 ICS同步设计优化的加热面壁温分布
Figure 22. Optimized heated wall temperature distribution for ICS synchronization design
图 23 轴向ICS独立设计示意图（单位：mm）
Figure 23. Schematic diagram of the ICS independent design along the axis （unit：mm）
图 24 连通结构进出口质量流量分配
Figure 24. Mass flow distribution at the inlet and outlet of the ICS
图 25 独立设计连通结构速度分布
Figure 25. Independently design the velocity distribution of the connected structure
图 26 ICS独立设计优化的流量偏差系数
Figure 26. Flow deviation coefficient for ICS independently design optimization
图 27 ICS独立设计的出口燃油温度分布
Figure 27. Optimization of the outlet fuel temperature distribution in ICS independently design
图 28 ICS独立设计优化通道No.4沿程热侧壁温分布
Figure 28. ICS independently design optimization channel No.4 along-the-way hot sidewall temperature distribution
图 29 ICS独立设计优化的加热面温度分布
Figure 29. Optimized heated wall temperature distribution for ICS independently design
表 1 计算模型边界条件
Table 1. Boundary condition of calculational model
mf/（g/s） Tin/K p0/MPa qf/（MW/m2） 7.5 550 3 133.3x+2.4 
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表 2 网格无关性验证相关信息
Table 2. Information about the grid independence test
网格 网格数 y+ Tw,avg/K uout/（m/s） Δp/Pa 1 682210 <1 1223.924 15.758 37146 2 1663029 1179.537 15.736 38095 3 3079951 1176.906 15.702 38314
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表 3 初始模型计算结果
Table 3. Calculation results of initial model
Tw,max/K $\varphi $/% $ {\beta _1} $/% $ {\beta _2} $/% $ {\beta _3} $/% $ {\beta _4} $/% 1356.62 2.20 3.58 4.31 −0.50 −7.39
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表 4 截面优化变量约束范围
Table 4. Constraint range of cross-section optimization variables
设计变量 约束范围 Hr 1～4 w1/mm −0.3～0.45 w2/mm −0.3～0.3 w3/mm −0.3～0.3 w4/mm −0.45～0.3
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表 5 截面优化后变量数据及目标函数
Table 5. Variable data and objective function after cross-section optimization
方案 Hr w1/mm w2/mm w3/mm w4/mm Tw,max/K φ/% Case 1 4 −0.206 0.351 0.446 0.577 1178.33 0.045 Case 2 4 −0.076 0.266 0.469 0.641 1176.67 0.241 Case 3 4 0.225 0.206 0.475 0.700 1174.94 0.626
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表 6 ICS同步设计优化变量约束范围
Table 6. Optimize the variable constraint range for ICS synchronization design
设计变量 约束范围 Ps/% 10～90 Φ 1～8
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表 7 ICS同步设计优化后变量数据及目标函数
Table 7. Variable data and objective function after ICS synchronization design optimization
方案 Ps/% Φ Tw,max/K φ/% Case 1 35.8 1 1330.12 2.031 Case 2 26.2 4.8 1295.50 2.286 Case 3 26.2 8 1290.67 2.755
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表 8 ICS独立设计优化变量约束范围
Table 8. Optimize the variable constraint range for ICS independent design
设计变量 约束范围 Ps1/% 10～90 Ps2/% 10～90 Ps3/% 10～90 Φ1 1～8 Φ2 1～8 Φ3 1～8
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表 9 ICS独立设计优化后变量数据及目标函数
Table 9. Variable data and objective function after ICS independently design optimization
方案 Ps1/% Ps2/% Ps3/% Φ1 Φ2 Φ3 Tw,max/K φ/% Case 1 35 30 72 5.1 7.5 7.2 1331.56 1.986 Case 2 38 27 20 5.4 3.3 1.3 1293.52 2.085 Case 3 41 16 30 4.9 6.1 3.0 1284.82 2.084
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[1] CURRAN E T. Scramjet engines: the first forty years[J]. Journal of Propulsion and Power, 2001, 17(6): 1138-1148. doi: 10.2514/2.5875 [2] WALTRUP P J, WHITE M E, ZARLINGO F, et al. History of U. S. navy ramjet, scramjet, and mixed-cycle propulsion development[J]. Journal of Propulsion and Power, 2002, 18(1): 14-27. doi: 10.2514/2.5928 [3] 刘世俭, 刘兴洲. 超燃冲压发动机可贮存碳氢燃料再生主动冷却换热过程分析[J]. 飞航导弹, 2009(3): 48-52. LIU Shijian, LIU Xingzhou. Analysis of regenerative active cooling heat transfer process of storable hydrocarbon fuel in scramjet[J]. Winged Missiles Journal, 2009(3): 48-52. (in ChineseLIU Shijian, LIU Xingzhou. Analysis of regenerative active cooling heat transfer process of storable hydrocarbon fuel in scramjet[J]. Winged Missiles Journal, 2009(3): 48-52. (in Chinese) [4] NING Wang, YU Pan, JIN Zhou. Research status of active cooling of endothermic hydrocarbon fueled scramjet engine[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2013, 227(11): 1780-1794. doi: 10.1177/0954410012463642 [5] CARLILE J A, QUENTMEYER R J. An experimental investigation of high-aspect-ratio cooling passages [J]. Joint Propulsion Conference and Exhibit, 1992. [6] WADEL M F, MEYER M L. Validation of high aspect ratio cooling in a 89 kN (20, 000 lb(sub f)) thrust combustion chamber[C]// 32nd Joint Propulsion Conference and Exhibit. Lake Buena Vista, US: AIAA, 1996: 2584. [7] 章思龙. 碳氢燃料超燃冲压发动机再生/膜复合冷却特性研究[D]. 哈尔滨: 哈尔滨工业大学, 2016. ZHANG Silong. Study on regeneration/film composite cooling characteristics of hydrocarbon fuel scramjet[D]. Harbin: Harbin Institute of Technology, 2016. (in ChineseZHANG Silong. Study on regeneration/film composite cooling characteristics of hydrocarbon fuel scramjet[D]. Harbin: Harbin Institute of Technology, 2016. (in Chinese) [8] ZHANG Silong, QIN Jiang, XIE Kaili, et al. Thermal behavior inside scramjet cooling channels at different channel aspect ratios[J]. Journal of Propulsion and Power, 2016, 32(1): 57-70. doi: 10.2514/1.B35563 [9] JIANG Yuguang, XU Yaxing, ZHANG Silong, et al. Parametric study on the distribution of flow rate and heat sink utilization in cooling channels of advanced aero-engines[J]. Energy, 2017, 138: 1056-1068. doi: 10.1016/j.energy.2017.07.091 [10] JIANG Yuguang, QIN Jiang, CHETEHOUNA K, et al. Parametric study on the hydrocarbon fuel flow rate distribution and cooling effect in non-uniformly heated parallel cooling channels[J]. International Journal of Heat and Mass Transfer, 2018, 126: 267-276. doi: 10.1016/j.ijheatmasstransfer.2018.05.124 [11] GUZMÁN A M, BEIZA M P, DIAZ A J, et al. Flow and heat transfer characteristics in micro and mini communicating pressure driven channel flows by numerical simulations[J]. International Journal of Heat and Mass Transfer, 2013, 58(1/2): 568-577. [12] JING Tingting, HE Guoqiang, QIN Fei, et al. An innovative self-adaptive method for improving heat sink utilization efficiency of hydrocarbon fuel in regenerative thermal protection system of combined cycle engine[J]. Energy Conversion and Management, 2018, 178: 369-382. doi: 10.1016/j.enconman.2018.10.038 [13] JIANG Yuguang, WANG Qi, ZHOU Qilin, et al. Influences of interconnection structure on the flow and heat transfer behaviors of the hydrocarbon fuel in parallel SCRamjet regenerative cooling channels[J]. Numerical Heat Transfer, Part A: Applications, 2023, 84(11): 1273-1296. doi: 10.1080/10407782.2023.2174627 [14] GAO F, ZHANG Q, XIAO H Y, et al. Optimization and design of regenerative cooling channel for scramjet engine[C]// Proceedings of the 3rd International Conference on Computer Information Science and Application Technology (CISAT). Dali, China: Journal of Physics Conference Series, 2020: 1634. [15] GUPTA D, SAHA P, ROY S. Multi-objective optimization of the perforated micro pin-fin heat sink using non-dominated sorting genetic algorithm-Ⅱ coupled with computational fluid dynamics simulation[J]. Journal of Heat Transfer, 2022, 144(9): 093301. doi: 10.1115/1.4054761 [16] ALPEREN Y, SERTAC C. Multi objective optimization of a micro-channel heat sink through genetic algorithm[J]. International Journal of Heat and Mass Transfer, 2020, 146: 118847. doi: 10.1016/j.ijheatmasstransfer.2019.118847 [17] LIU Feifei, CHEN Yangyang, QIN Wu, et al. Optimal design of liquid cooling structure with bionic leaf vein branch channel for power battery[J]. Applied Thermal Engineering, 2023, 218: 119283. doi: 10.1016/j.applthermaleng.2022.119283 [18] 秦昂, 张登成, 魏扬, 等. 超燃冲压发动机再生冷却结构的多目标优化设计[J]. 推进技术, 2018, 39(6): 1331-1339. QIN Ang, ZHANG Dengcheng, WEI Yang, et al. Multi-objective optimization on regenerative cooling structure of scramjet[J]. Journal of Propulsion Technology, 2018, 39(6): 1331-1339. (in ChineseQIN Ang, ZHANG Dengcheng, WEI Yang, et al. Multi-objective optimization on regenerative cooling structure of scramjet[J]. Journal of Propulsion Technology, 2018, 39(6): 1331-1339. (in Chinese) [19] 黄莺. 基于流量系数和冷却效率的扇形孔和圆转缝形孔多目标优化[D]. 南京: 南京航空航天大学, 2020. HUANG Ying. Multi-objective optimization of fan-shaped holes and circular slotted holes based on flow coefficient and cooling efficiency[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2020. (in ChineseHUANG Ying. Multi-objective optimization of fan-shaped holes and circular slotted holes based on flow coefficient and cooling efficiency[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2020. (in Chinese) [20] CHEN Qun, WANG Yifei, ZHANG Mengqi. Optimization strategies of heat transfer systems with consideration of heat transfer and flow resistance[J]. International Journal of Heat and Mass Transfer, 2017, 112: 137-146. doi: 10.1016/j.ijheatmasstransfer.2017.04.117 [21] XU Shaotong, WANG Changhui, YANG Chengxiao. Optimal design of regenerative cooling structure based on backpropagation neural network[J]. Journal of Thermophysics and Heat Transfer, 2022, 36(3): 637-649. doi: 10.2514/1.T6447 [22] 姜俞光. 热裂解型碳氢燃料并联通道流量分配及偏差抑制研究[D]. 哈尔滨: 哈尔滨工业大学, 2018. JIANG Yuguang. Study on flow distribution and deviation suppression of parallel channel of pyrolysis hydrocarbon fuel[D]. Harbin: Harbin Institute of Technology, 2018. (in ChineseJIANG Yuguang. Study on flow distribution and deviation suppression of parallel channel of pyrolysis hydrocarbon fuel[D]. Harbin: Harbin Institute of Technology, 2018. (in Chinese) [23] 袁鑫, 寇志海, 赵国昌, 等. 矩形通道超临界再生冷却技术研究综述[J]. 飞航导弹, 2017(5): 18-23, 42. YUAN Xin, KOU Zhihai, ZHAO Guochang, et al. Review on supercritical regenerative cooling technology in rectangular channel[J]. Aerodynamic Missile Journal, 2017(5): 18-23, 42. (in ChineseYUAN Xin, KOU Zhihai, ZHAO Guochang, et al. Review on supercritical regenerative cooling technology in rectangular channel[J]. Aerodynamic Missile Journal, 2017(5): 18-23, 42. (in Chinese) [24] YANG Qingchun, CHETEHOUNA K, GASCOIN N, et al. Experimental study on combustion modes and thrust performance of a staged-combustor of the scramjet with dual-strut[J]. Acta Astronautica, 2016, 122: 28-34. doi: 10.1016/j.actaastro.2016.01.002 [25] 张晓红, 姜俞光, 秦江, 等. 通道截面形状对碳氢燃料流量分配的影响[J]. 航空动力学报, 2019, 34(9): 1977-1987. ZHANG Xiaohong, JIANG Yuguang, QIN Jiang, et al. Effect of channel cross sectional shape on flow distribution of hydrocarbon fuel[J]. Journal of Aerospace Power, 2019, 34(9): 1977-1987. (in ChineseZHANG Xiaohong, JIANG Yuguang, QIN Jiang, et al. Effect of channel cross sectional shape on flow distribution of hydrocarbon fuel[J]. Journal of Aerospace Power, 2019, 34(9): 1977-1987. (in Chinese) [26] XIONG Yuefei, QIN Jiang, CHENG Kunlin, et al. Quasi-one-dimensional model of hydrocarbon-fueled scramjet combustor coupled with regenerative cooling[J]. International Journal of Aerospace Engineering, 2022, 2022: 9931498. [27] ZHANG Cong, YAO Zhanli, QIN Jiang, et al. Experimental study on measurement and calculation of heat flux in supersonic combustor of scramjet[J]. Journal of Thermal Science, 2015, 24(3): 254-259. doi: 10.1007/s11630-015-0781-3 [28] 贺武生. 超燃冲压发动机研究综述[J]. 火箭推进, 2005, 31(1): 29-32. HE Wusheng. Review of scramjet engine development[J]. Journal of Rocket Propulsion, 2005, 31(1): 29-32. (in Chinese doi: 10.3969/j.issn.1672-9374.2005.01.006HE Wusheng. Review of scramjet engine development[J]. Journal of Rocket Propulsion, 2005, 31(1): 29-32. (in Chinese) doi: 10.3969/j.issn.1672-9374.2005.01.006 [29] YAN Minggao, LIU Duopu, GAO Liang, et al. The China aeronautical materials handbook [M]. 2nd ed. Beijing: China Standard Press. 2002. [30] MENTER F R. Zonal two equation k-ω turbulence models for aerodynamic flows[R]. Orlando, US: AIAA, 1993: 2906. [31] KIM S K, CHOI H S, KIM Y. Thermodynamic modeling based on a generalized cubic equation of state for kerosene/LOx rocket combustion[J]. Combustion and Flame, 2012, 159(3): 1351-1365. doi: 10.1016/j.combustflame.2011.10.008 [32] POLING B E, PRAUSNITZ J M, JOHN PAUL O C, et al. The properties of gases and liquids[M]. New York: McGraw-Hill, 2001. [33] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197. doi: 10.1109/4235.996017 [34] 俞刚, 范学军. 超声速燃烧与高超声速推进[J]. 力学进展, 2013, 43(5): 449-472. YU Gang, FAN Xuejun. Supersonic combustion and hypersonic propulsion[J]. Advances in Mechanics, 2013, 43(5): 449-472. (in ChineseYU Gang, FAN Xuejun. Supersonic combustion and hypersonic propulsion[J]. Advances in Mechanics, 2013, 43(5): 449-472. (in Chinese) [35] 陶焰明, 肖为, 罗莲军, 等. 基于神经网络的变截面再生冷却结构优化设计[J]. 推进技术, 2021, 42(5): 1112-1120. TAO Yanming, XIAO Wei, LUO Lianjun, et al. Structural optimal design of regenerative cooling with variable section based on neural network[J]. Journal of Propulsion Technology, 2021, 42(5): 1112-1120. (in ChineseTAO Yanming, XIAO Wei, LUO Lianjun, et al. Structural optimal design of regenerative cooling with variable section based on neural network[J]. Journal of Propulsion Technology, 2021, 42(5): 1112-1120. (in Chinese) [36] 王夕. 超临界压力吸热型碳氢燃料热裂解及传热特性研究[D]. 北京: 清华大学, 2013. WANG Xi. Study on thermal cracking and heat transfer characteristics of supercritical pressure endothermic hydrocarbon fuel[D]. Beijing: Tsinghua University, 2013. (in ChineseWANG Xi. Study on thermal cracking and heat transfer characteristics of supercritical pressure endothermic hydrocarbon fuel[D]. Beijing: Tsinghua University, 2013. (in Chinese) [37] BAO W, QIN J, ZHOU W X, et al. Effect of cooling channel geometry on re-cooled cycle performance for hydrogen fueled scramjet[J]. International Journal of Hydrogen Energy, 2010, 35(13): 7002-7011. doi: 10.1016/j.ijhydene.2010.04.033 [38] JIANG Yuguang, WANG Leqing, ZHOU Qilin, et al. Flow and heat transfer of hydrocarbon fuel in the double-layer regenerative cooling channels[J]. Numerical Heat Transfer, Part A: Applications, 2024, 85(9): 1433-1455. doi: 10.1080/10407782.2023.2203872 [39] LI Xin, QIN Jiang, ZHANG Silong, et al. Effects of microribs on the thermal behavior of transcritical n-decane in asymmetric heated rectangular mini-channels under near critical pressure[J]. Journal of Heat Transfer, 2018, 140(12): 122402. doi: 10.1115/1.4041049 [40] FIEBIG M. Embedded vortices in internal flow: heat transfer and pressure loss enhancement[J]. International Journal of Heat and Fluid Flow, 1995, 16(5): 376-388. doi: 10.1016/0142-727X(95)00043-P [41] ACKERMAN J W. Pseudoboiling heat transfer to supercritical pressure water in smooth and ribbed tubes[J]. Journal of Heat Transfer, 1970, 92(3): 490-497. doi: 10.1115/1.3449698 -
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