Abstract In the context of geotechnical and geological barriers, a thorough analysis of uncertainty and sensitivity is a crucial aspect of any physics-based performance assessment. While experimental data are scarce in actual waste repositories, large-scale experiments in underground research laboratories (URLs) provide such data that can be used to not only qualify THMC process models but also uncertainty assessment methodologies. In this paper, we adopt a Design of Experiments (DoE)-based history matching workflow – an approach popular in the oil and gas industry – and scrutinize its applicability for multiphysical analyses of nuclear waste disposal-related processes using synthetic experimental data. Based on an analytical solution of a coupled thermo-hydro-mechanical (THM) problem of a heat source embedded in a fluid-saturated porous medium mimicking a disposal cell in an argillaceous host formation, we discuss the adaptability of the workflow as a way to address parameter and model uncertainties for barrier integrity assessment. We thereby put particular focus on the relative importance of providing defined input parameter distributions for quantities generally afflicted with epistemic uncertainty and the constraints imposed by experimental (URL) or monitoring (repository) data. We found that once constraining data is available, the particular a priori distribution plays only a minor role for the outcome, such that we can conclude that the often unknown distributions can be substituted by uniform priors under such conditions. However, detailed knowledge of parameter distributions can increase the efficiency of the workflow significantly. We conclude that the presented workflow is particularly suitable for performing uncertainty quantification and sensitivity analysis for geotechnical applications where monitoring or other experimental data are available, as it allows us to deal with models of great complexity, epistemic uncertainty and it incorporates canonically to use of measured data in order to reduce uncertainty.

中文翻译：

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基于 DoE 的历史匹配用于粘土岩热源周围热-水-机械过程的概率不确定性量化

摘要 在岩土和地质障碍的背景下，对不确定性和敏感性的彻底分析是任何基于物理的性能评估的关键方面。虽然实际废物储存库中的实验数据很少，但地下研究实验室 (URL) 的大规模实验提供的此类数据不仅可用于验证 THMC 过程模型，还可用于不确定性评估方法。在本文中，我们采用了一种基于实验设计 (DoE) 的历史匹配工作流程——一种在石油和天然气行业中流行的方法——并使用合成实验数据仔细审查其对核废料处理相关过程的多物理分析的适用性。基于嵌入在流体饱和多孔介质中的热源耦合热水力机械 (THM) 问题的解析解，模拟泥质宿主地层中的处理室，我们讨论了工作流程的适应性，作为一种方法解决屏障完整性评估的参数和模型不确定性。因此，我们特别关注为通常受认知不确定性和实验（URL）或监控（存储库）数据强加的约束的数量提供定义的输入参数分布的相对重要性。我们发现，一旦约束数据可用，特定的先验分布对结果只起次要作用，因此我们可以得出结论，在这种情况下，通常未知的分布可以被统一的先验代替。然而，参数分布的详细知识可以显着提高工作流程的效率。我们得出的结论是，所提出的工作流程特别适用于对可获得监测或其他实验数据的岩土工程应用进行不确定性量化和敏感性分析，因为它使我们能够处理高度复杂、认知不确定性的模型，并且它规范地结合使用了测量数据。数据以减少不确定性。