Abstract Understanding thermo-mechanical behavior is often crucial to the development of new materials and processes, but the key physical properties can be difficult and time-consuming to measure accurately. Herein, an image inversion method is developed to simultaneously determine the thermal diffusivity and coefficient of thermal expansion for thermally conductive solid materials. The method leverages the rich spatio-temporal information contained in coupled infrared thermography and digital image correlation measurements of the transient temperature and displacement fields of a sample, respectively. The complete set of experimental image data is fitted to numerical models to extract the parameters of interest. In the case of an aluminum alloy rod (T6061), the measured thermal diffusivity ( 8.3 × 10 − 5 m 2 s − 1 ) agrees with a standard flash diffusivity measurement within 5%, and the coefficient of thermal expansion ( 27.6 μ m m − 1 K − 1 ) is within the anticipated range from literature. The possibility of image-based data-driven discovery of thermo-mechanical properties could find many applications, as a method of automated, convenient, non-destructive evaluation.

中文翻译：

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光学和红外图像数据的同时反演，以确定导热固体材料的热机械性能

摘要 了解热机械行为对于新材料和新工艺的开发通常是至关重要的，但关键物理特性的准确测量可能既困难又耗时。在此，开发了一种图像反演方法来同时确定导热固体材料的热扩散率和热膨胀系数。该方法分别利用耦合红外热成像和数字图像相关测量中包含的丰富时空信息，分别测量样品的瞬态温度和位移场。完整的实验图像数据集适合数值模型以提取感兴趣的参数。对于铝合金棒 (T6061)，测得的热扩散率 (8. 3 × 10 - 5 m 2 s - 1 ) 与标准闪光扩散率测量值一致，误差在 5% 以内，热膨胀系数 (27.6 μ mm - 1 K - 1 ) 在文献的预期范围内。基于图像的数据驱动的热机械特性发现的可能性可以找到许多应用，作为一种自动化、方便、无损评估的方法。