This article describes a bridge between POD-based model order reduction techniques and the classical Newton/Krylov solvers. This bridge is used to derive an efficient algorithm to correct, "on-the-fly", the reduced order modelling of highly nonlinear problems undergoing strong topological changes. Damage initiation problems are addressed and tackle via a corrected hyperreduction method. It is shown that the relevancy of reduced order model can be significantly improved with reasonable additional costs when using this algorithm, even when strong topological changes are involved.

中文翻译：

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桥接适当的正交分解方法和增强的 Newton-Krylov 算法：高度非线性机械问题的自适应模型降阶

本文描述了基于 POD 的模型降阶技术与经典的 Newton/Krylov 求解器之间的桥梁。该桥用于派生一种有效的算法，以“即时”纠正经历强拓扑变化的高度非线性问题的降阶建模。损伤引发问题通过修正的超减少方法得到解决和解决。结果表明，即使在涉及强拓扑变化的情况下，使用该算法也可以通过合理的额外成本显着提高降阶模型的相关性。