This study addresses the estimation of material properties at a mesoscopic level using the PuMA software from an uncertainty quantification perspective. Stochastic simulation with PuMA is primarily related to the random distribution of fibers, which is an intrinsic source of uncertainty. Additionally, the selection of certain physical parameters, such as the fiber's thermal conductivity, introduces further uncertainties. The first contribution of this study is to propose a low-cost surrogate-based methodology with an unequal allocation scheme, applied for the first time to the stochastic mesoscale characterization of ablative materials. The second contribution is a study on uncertainty propagation and sensitivity analysis of material properties, providing a systematic assessment of the choice of voxel resolution for both the fibers and the domain. Specifically, the convergence of quantities of interest can be monitored, thus identifying the minimal reference elementary volume.

中文翻译：

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进入大气的烧蚀材料的随机介尺度表征


本研究从不确定性量化的角度，使用 PuMA 软件在介观水平上估计材料特性。 PuMA 的随机模拟主要与纤维的随机分布有关，这是不确定性的内在来源。此外，某些物理参数（例如纤维的导热率）的选择会带来更多的不确定性。这项研究的第一个贡献是提出了一种基于低成本替代方法的不等分配方案，首次应用于烧蚀材料的随机介观表征。第二个贡献是对材料特性的不确定性传播和敏感性分析的研究，为纤维和域的体素分辨率的选择提供了系统评估。具体来说，可以监视感兴趣的量的收敛，从而识别最小参考基本体积。