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Inverse Identification of Temperature-Dependent Thermal Conductivity for Charring Ablators
International Journal of Thermophysics ( IF 2.5 ) Pub Date : 2021-01-12 , DOI: 10.1007/s10765-020-02781-x
Xiang-Yang Wang , Na Liu , Rui Zhao , Yong-Le Nian , Wen-Long Cheng

Estimation of thermal conductivity of charring composite is a key issue for both design and optimization of an ablative thermal protection system. This paper presents a method for predicting temperature-dependent thermal conductivity of charring ablator using genetic algorithm and cubic spline interpolation, and a special ablative material composed of phenolic resin, glass fibers and quartz fibers is concerned. In this study, by considering the effects of pyrolysis, carbon–silica reaction, and the convective heat transfer between pyrolysis gas and charred layer, the ablative heat transfer model is developed to simulate the ablation process first. Then based on the measured temperature profiles and built model, the temperature-dependent thermal conductivity without prior information on the functional form is predicted which is parameterized by cubic spline. The predicted thermal conductivity curve is continuous and smooth everywhere, and the changes of the curve can reveal the ablation characteristic of the concerned material precisely. Consequently, the calculated temperature profiles using the predicted results show good agreement with experimental data. Also, the reliability of the prediction is discussed through analyzing the iterative process and the number of interpolation nodes. It is concluded that the improvement is limited through adding nodes when the thermal conductivity is already well defined by existing nodes.

中文翻译:

炭化烧蚀剂随温度变化的热导率的逆识别

炭化复合材料的热导率估计是烧蚀热保护系统设计和优化的关键问题。本文提出了一种利用遗传算法和三次样条插值法预测炭化烧蚀剂随温度变化的热导率的方法,研究了一种由酚醛树脂、玻璃纤维和石英纤维组成的特殊烧蚀材料。在本研究中,通过考虑热解、碳-二氧化硅反应以及热解气体与焦化层之间的对流传热的影响,首先建立了烧蚀传热模型来模拟烧蚀过程。然后根据测得的温度曲线和建立的模型,在没有函数形式的先验信息的情况下,预测温度相关的热导率,该热导率由三次样条参数化。预测的热导率曲线处处连续平滑,曲线的变化可以准确地揭示有关材料的烧蚀特性。因此,使用预测结果计算出的温度曲线与实验数据显示出良好的一致性。此外,通过分析迭代过程和插值节点的数量,讨论了预测的可靠性。结论是,当现有节点已经很好地定义了热导率时,通过添加节点来限制改进。并且曲线的变化可以准确地揭示有关材料的烧蚀特性。因此,使用预测结果计算出的温度曲线与实验数据显示出良好的一致性。此外,通过分析迭代过程和插值节点的数量,讨论了预测的可靠性。结论是,当现有节点已经很好地定义了热导率时,通过添加节点来限制改进。并且曲线的变化可以准确地揭示有关材料的烧蚀特性。因此,使用预测结果计算出的温度曲线与实验数据显示出良好的一致性。此外,通过分析迭代过程和插值节点的数量,讨论了预测的可靠性。结论是,当现有节点已经很好地定义了热导率时,通过添加节点来限制改进。
更新日期:2021-01-12
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