A model order reduction approach combining reduced basis (RB) projection and sub-structuring by domain decomposition is developed to tackle nonlinear elasto-plasticity in parametrized coupled thermo-hydro-mechanical (THM) systems. The region-specific occurrence of plasticity in the THM process is exploited in domain decomposition to facilitate the simplified construction of localized reduced subspaces in order to perform projection on a multi-domain basis. Traditional RB projection is leveraged in the elastic zone while the computationally expensive nonlinear iterative procedure is confined in the zone where plasticity is assumed to be restricted. The applicability of the approach to parametric problems is investigated through inverse identification of material parameters involving a nonlinear THM model system for nuclear waste repository applications. The model reduction strategy is observed to significantly reduce the computational effort involved with up to 12 times faster simulation compared to finite element (FE)-driven inverse identification procedure.

中文翻译：

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通过弹性和塑性域子结构减少非线性热-水-机械系统的模型阶数


开发了一种模型降阶方法，将降阶基础 (RB) 投影与域分解的子结构相结合，以解决参数化耦合热液机械 (THM) 系统中的非线性弹塑性问题。 THM 过程中特定区域出现的可塑性在域分解中被利用，以促进局部缩减子空间的简化构造，以便在多域基础上执行投影。传统的 RB 投影在弹性区域中利用，而计算量大的非线性迭代过程被限制在假设塑性受到限制的区域中。通过涉及核废料储存库应用的非线性 THM 模型系统的材料参数的逆向识别，研究了该方法对参数问题的适用性。据观察，与有限元 (FE) 驱动的逆向识别程序相比，模型简化策略可显着减少计算量，仿真速度提高了 12 倍。