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Inverse determination of temperature-dependent thermal conductivity using steady surface data on arbitrary objects

机译:使用任意物体上的稳定表面数据对温度相关的导热系数进行反演

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An inverse computational method has been developed for the non-intrusive and non-destructive evaluation of the temperature-dependence of thermal conductivity. The methodology is based on an inverse computational procedure that can be used in conjunction with an experiment. Given steady state heat flux mesurements or convection heat transfer coefficients on the surface of the speciment, in addition to a finite number of steady state surface temperature measurements, the algorithm can predict the variation of thermal conductivity o ver the entire range of measured temperatures. Thus, this method requires only one temperature probe and one heat flux probe. The thermal conductivity dependence on temperature (k-T curve) can be completely arbitrary, although a priori knowledge of the general form of the k-T curve substantially improves the accuracy of the algorithm. The influence of errors of measured surface temperatures and heat fluxes on the predicted thermal conductivity has been evaluated. In was found that measurement errors of temperature up to 5 percent standard deviation were not magnified by this inverse procedure, while the effect of errors in measured heat fluxes were even lower. The method is applicable to two-dimensional and three-dimensional solids of arbitrary shape and size.
机译:已经开发了一种反计算方法,用于对导热系数的温度依赖性进行非侵入性和非破坏性评估。该方法基于可与实验结合使用的逆计算程序。给定样本表面上的稳态热通量测量值或对流传热系数,除了有限数量的稳态表面温度测量值之外,该算法还可以预测整个测量温度范围内的热导率变化。因此,该方法仅需要一个温度探针和一个热通量探针。尽管对k-T曲线的一般形式的先验知识大大提高了算法的准确性,但热导率对温度的依赖性(k-T曲线)可以完全任意。已经评估了测量的表面温度和热通量的误差对预测的热导率的影响。在该过程中发现,高达5%标准偏差的温度测量误差不会被这种逆过程放大,而在测量的热通量中误差的影响甚至更低。该方法适用于任意形状和大小的二维和三维实体。

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