Sophisticated computational techniques for damage mechanics with mixed uncertain input fields

点击翻译按钮获取中文摘要

Goal of this research project is to provide efficient computational techniques for detailed damage mechanics finite element models with uncertain input variables. For the treatment of epistemic uncertainties, i.e. unknown input random field parameters, a Dempster-Shafer p-box approach will be utilized and implemented into an adaptive nested sampling strategy. Systematic studies on the discretization of pboxesin dependency on the input field modeling approach, alternatively via Karhunen-Loeve expansion (KLE) or Polynomial Chaos expansion (PCE) will be investigated. An adaptive multi-level Monte-Carlo scheme will be applied for an efficient sampling of the structural response surfaces. This scheme has to be extended for the nested epistemic-aleatory sampling defining some sophisticated error criteria. With emphasis to sensitivity or reliability analysis response surfaces for the quantities of interest, i.e. remaining load bearing capacity, will be generated. Here an adaptive generalized Polynomial Chaos(gPC) scheme will be implemented, where for the epistemic parameter space newer developments on elementwise gPC appears an attractive option. Systematic studies on the efficient and accurate construction of possibly element-wise orthogonal polynomials have to be performed. The applicability of the developed computational approach will be studied on our own 3-dimensional bench-mark problem on a concrete beam subjected to 4 point bending loads. This example serves for parametric studies of the overall computational approach.