The storage of renewable hydrogen in salt caverns requires fast injection and production rates to cope with the imbalance between energy production and consumption. This raises concerns about the mechanical stability of salt caverns under such operational conditions. The use of appropriate constitutive models for salt mechanics is an important step in investigating this issue, therefore many constitutive models with several parameters have been presented in the literature. However, a robust calibration strategy to reliably determine which model and parameter set represents the given rock, based on stress–strain data sets, remains an unsolved challenge. In this paper, for the first time in the community, we present a multi-step strategy to determine a single parameter set based on many deformation data sets for salt rocks. Towards this end, we first develop a comprehensive constitutive model able to capture all relevant nonlinear deformation physics of transient, reverse, and steady-state creep. The determination of the single set of representative material parameters is then achieved by framing the calibration process as an optimization problem, for which the global Particle Swarm Optimization algorithm is employed. To allow for dynamic data integration, a multi-step calibration strategy is developed for a situation where experiments are included one at a time, as they become available. Additionally, due to the existing mild heterogeneity in the experimental rock samples, our optimization strategy is made flexible to allow for this slight heterogeneity. The devised optimization strategy, based on the multi-physics comprehensive constitutive modeling framework, results in a single set of representative material properties of all the deformation data sets. As a rigorous mathematical analysis for the presented method and the lack of relevant experimental data sets, we consider a wide range of synthetic experimental data sets, inspired by the existing sparse relevant data in the literature. The results of our performance analyses show that the proposed calibration strategy is robust. Moreover, the results become increasingly more accurate as more data sets become available.

中文翻译：

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用于可靠确定盐岩力学本构模型参数的多步骤校准策略


在盐穴中储存可再生氢需要快速注入和生产速度，以应对能源生产和消耗之间的不平衡。这引发了人们对盐穴在这种操作条件下的机械稳定性的担忧。为盐力学使用适当的本构模型是研究这个问题的重要步骤，因此文献中已经提出了许多具有多个参数的本构模型。然而，根据应力-应变数据集可靠地确定哪个模型和参数集代表给定岩石的稳健校准策略仍然是一个未解决的挑战。在本文中，我们首次在社区中提出了一种多步骤策略，用于根据盐岩的许多变形数据集确定单个参数集。为此，我们首先开发了一个全面的本构模型，能够捕获瞬态、反向和稳态蠕变的所有相关非线性变形物理场。然后，通过将校准过程构建为优化问题来确定单组代表性材料参数，为此采用了全局粒子群优化算法。为了实现动态数据集成，我们开发了一种多步骤校准策略，用于在实验可用时一次包含一个实验的情况。此外，由于实验岩石样品中存在轻微的异质性，我们的优化策略变得灵活，可以考虑这种轻微的异质性。基于多物理场综合本构建模框架设计的优化策略，可生成所有变形数据集的一组代表性材料属性。 作为对所提出的方法和缺乏相关实验数据集的严格数学分析，我们考虑了广泛的合成实验数据集，受到文献中现有的稀疏相关数据的启发。我们的性能分析结果表明，所提出的校准策略是稳健的。此外，随着更多数据集的出现，结果变得越来越准确。