Abstract In many practical problems, a body is subjected to a thermal load and experience a temperature change. In some cases, the temperature change can be very high and it would be better to consider thermal and mechanical properties as a function of temperature whereas in many cases, temperature-dependent thermal and mechanical properties are unknown. In this article, an inverse method is presented for identification of the thermal conductivity, the specific heat, the coefficient of thermal expansion, and the elastic modulus, where all the properties are considered as functions of temperature. It is assumed that these four material properties are simultaneously unknown. In the proposed method, the unknown parameters of the inverse problem are calculated using measured data from a transient thermomechanical experiment. Sensitivity analysis is carried out by an analytical direct differentiation method and a meshfree technique. Several important factors affecting the identification of the thermal and mechanical properties, such as the error of measuring sensors, the number of sensors, and the number of sampling data are studied in the numerical analyses. The obtained results show that identification of the properties using the proposed inverse method can be achieved with a suitable accuracy even in the cases with measurement errors.

中文翻译：

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用于识别与温度相关的热和机械材料特性的逆无网格热弹性分析

摘要 在许多实际问题中，物体承受热负荷并经历温度变化。在某些情况下，温度变化可能非常大，最好将热和机械特性视为温度的函数，而在许多情况下，与温度相关的热和机械特性是未知的。在本文中，提出了一种用于识别热导率、比热、热膨胀系数和弹性模量的逆方法，其中所有属性都被视为温度的函数。假设这四种材料特性同时未知。在所提出的方法中，使用来自瞬态热机械实验的测量数据计算逆问题的未知参数。灵敏度分析通过解析直接微分法和无网格技术进行。在数值分析中研究了影响热力学性能识别的几个重要因素，如测量传感器的误差、传感器的数量和采样数据的数量。获得的结果表明，即使在存在测量误差的情况下，使用所提出的逆方法也可以以合适的精度实现属性识别。