高温燃气流瞬态热试验快速寻参方法仿真研究

王日; 齐玢; 阿嵘; 董素君; 周印佳; 陈鑫

doi:10.13224/j.cnki.jasp.20230393

高温燃气流瞬态热试验快速寻参方法仿真研究

doi: 10.13224/j.cnki.jasp.20230393

王日¹,
齐玢^{1, 2,*, ,},
阿嵘²,
董素君¹,
周印佳²,
陈鑫³

1.
北京航空航天大学航空科学与工程学院，北京 100191
2.
中国空间技术研究院钱学森空间技术实验室，北京 100094
3.
中国运载火箭技术研究院空间物理重点实验室，北京 100076

基金项目: 国家自然科学基金（11902026，12102056）

详细信息

作者简介:
王日（1989-），男，博士生，主要从事飞行器热管理及热试验技术研究

通讯作者:
齐玢（1986-），男，高级工程师，博士，主要从事飞行器热管理及热试验技术研究。E-mail：qionline@163.com

中图分类号: V216.5
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出版历程
- 收稿日期: 2023-06-17
- 网络出版日期: 2024-11-01

Simulation study on rapid method for high temperature gas flow parameter search in transient thermal test

WANG Ri¹,
QI Bin^{1, 2,*
, ,},
A Rong²,
DONG Sujun¹,
ZHOU Yinjia²,
CHEN Xin³

1.
School of Aeronautics Science and Engineering，Beihang University，Beijing 100191，China
2.
Qian Xuesen Laboratory of Space Technology，China Academy of Space Technology，Beijing 100094，China
3.
Science and Technology on Space Physics Laboratory，China Academy of Launch Vehicle Technology，Beijing 100076，China

摘要

摘要:
高温燃气流热试验采用固定燃气质量流量、调节燃气流温度的方法实现气动热等效模拟。利用高温燃气流数值计算结果，通过建立热流代理模型，快速确定燃气流试验参数，进而形成以燃气流温度为控制目标的闭环控制方法。采用Kriging代理模型方法建立不同质量流量、不同燃气流温度下冷壁热流代理模型和固定燃气质量流量、不同燃气流温度和试件表面温度下热壁热流代理模型。两者在测试工况点的预测热流平均相对误差分别为0.27%和0.48%，具有较高的预测精度。进一步针对某飞行包线9个典型状态点气动热模拟需求确定高温燃气流质量流量及燃气温度，数值仿真验证表明燃气流加热热壁热流与气动热模拟需求间最大相对误差为3.04%，平均相对误差为0.87%，实现了全时序高精度模拟功能。
- 热试验 /
- 气动热 /
- 尖楔结构 /
- 高温燃气 /
- 代理模型
Abstract:
The method of fixing gas mass flow rate and adjusting gas flow temperature is generally used to achieve aerodynamic thermal equivalent simulation in high temperature gas flow thermal tests. A method was proposed to quickly determine the test parameters of the gas flow by using the numerical calculation results of the high temperature gas flow and establishing a heat flux surrogate model, thus forming a closed-loop control method with the gas flow temperature as the control target. Kriging surrogate model method was used to establish the cold wall heat flux surrogate model under different flow rates and gas flow temperatures, and the hot wall heat flux surrogate model under fixed gas flow rates, and different gas flow temperatures and specimen surface temperatures. The average relative errors of the predicted heat flux at the test operating points were 0.27% and 0.48%, respectively, indicating high prediction accuracy. Further, the mass flow rate and temperature of gas flow were determined according to the aerodynamic thermal simulation requirements of 9 typical status points of a flight envelope. The relevant numerical calculation verification showed that the maximum relative error between the high-temperature gas flow heating hot wall heat flux and the aerodynamic thermal simulation requirements of each status point was 3.04%, and the average relative error was 0.87%, realizing the full-time sequence high-precision simulation function.
- thermal test /
- aerodynamic heating /
- tip wedge structure /
- high temperature gas flow /
- surrogate model

HTML

图 1 基于燃气温度反馈信号的闭环控制方法

Figure 1. Simulation method of thermal test based on gas temperature feedback

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图 2 典型尖楔前缘结构外形图

Figure 2. Geometry model of typical tip wedge structure

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图 3 高温燃气流热模拟试验方案示意图

Figure 3. Schematic of thermal test by gas flow heating

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图 4 计算网格模型

Figure 4. Mesh structure of computational model

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图 5 某工况对称面气流温度分布云图

Figure 5. Contour of gas flow temperature distribution on symmetry plane at some condition

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图 6 不同网格获得试件表面热流密度沿气流方向分布

Figure 6. Heat flux distribution on specimen wall for different mesh sizes

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图 7 驻点热流试验结果与仿真结果对比

Figure 7. Comparison between test results and simulation results of stagnation point heat flux

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图 8 代理模型样本点取值分布

Figure 8. Samples distribution of surrogate model

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图 9 燃气加热驻点区域冷壁热流代理模型预测结果

Figure 9. Prediction results of gas heating cold wall heat flux surrogate model of stagnation point

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图 10 燃气加热驻点区域热壁热流代理模型预测结果

Figure 10. Prediction results of gas heating hot wall heat flux surrogate model of stagnation point

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图 11 燃气温度时序变化曲线

Figure 11. Time varying curve of gas temperature

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表 1 冷壁热流代理模型设计变量取值范围

Table 1. Value ranges of design variables of cold wall heat flux surrogate model

设计变量	取值范围
设计变量	下限	上限
T_g/K	900	2200
$ \dot m $/（g/s）	50	250
T_w/K	300	1600

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表 2 代理模型参数

Table 2. Parameters of surrogate models

代理模型	β	σ²/10¹¹	θ
冷壁热流	−0.487	6.71	[0.526　0.1]
热壁热流	−0.337	5.87	[0.526　0.1]

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表 3 Mo-10Cu材料热物性参数

Table 3. Thermophysical parameters of Mo-10Cu material

温度/K	密度/ （kg/m³）	比定压热容/ （J/（kg·K））	热导率/ （W/（m·K））
293.15	10500	269	134
473.15		286	111
673.15		307	115
873.15		329	116
1073.15		353	113

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表 4 典型包线各状态点气动热已知条件及试验目标

Table 4. Aerodynamic heat conditions and test objectives at each state point of a typical envelope

状态点	时刻/s	气动热已知条件		热试验目标
状态点	时刻/s	冷壁热流/ （MW/m²）	气流恢复焓/ （kJ/kg）	壁面温度/K	热壁热流/ （MW/m²）
0	0	0.69	614.3	300	0.69
1	10	0.89	704.9	353	0.77
2	17	1.40	906.3	449	1.05
3	25	2.70	1158.1	627	1.66
4	30	4.75	1329.2	852	2.18
5	35	4.65	1409.8	951	1.9
6	40	3.99	1359.5	1005	1.31
7	45	2.94	1309.1	1021	0.82
8	50	1.95	1309.1	1028	0.53

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表 5 热流试验各状态点热流密度

Table 5. Heat flux of thermal test at each state point

状态点	流热试验工况仿真结果			目标热流/ （MW/m²）	相对误差/%
状态点	壁面温度/K	气流温度/K	热流密度/ （MW/m²）	目标热流/ （MW/m²）	相对误差/%
0	300	974.0	0.711	0.69	3.04
1	353	1052.8	0.779	0.77	1.17
2	449	1280.3	1.04	1.05	−0.95
3	627	1719.4	1.65	1.66	−0.60
4	852	2116.2	2.19	2.18	0.46
5	951	2059.7	1.91	1.9	0.53
6	1005	1809.9	1.3	1.31	−0.76
7	1021	1558.8	0.819	0.82	−0.12
8	1028	1394.8	0.531	0.53	0.19

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