Sophisticated computational techniques for damage mechanics with mixed uncertain input fields

具有混合不确定输入场的损伤力学的复杂计算技术

• 批准号: 341840349
• 负责人: Professor Dr.-Ing. Udo Nackenhorst
• 金额: --
• 依托单位: Institut für Baumechanik und Numerische Mechanik (IBNM)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/341840349?language=en
• 关键词: Sophisticated; computational; techniques; damage; mechanics

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.

该研究项目的目标是为具有不确定输入变量的详细损伤力学有限元模型提供有效的计算技术。为了处理认知不确定性，即未知的输入随机场参数，将利用 Dempster-Shafer p 盒方法并将其实施到自适应嵌套采样策略中。将研究 pboxesin 依赖于输入场建模方法的离散化，或者通过 Karhunen-Loeve 展开 (KLE) 或多项式混沌展开 (PCE)。将应用自适应多级蒙特卡罗方案来对结构响应面进行有效采样。该方案必须扩展到定义一些复杂的错误标准的嵌套认知随机抽样。重点关注灵敏度或可靠性分析，将生成感兴趣数量（即剩余承载能力）的响应面。这里将实施自适应广义多项式混沌（gPC）方案，其中对于认知参数空间，元素级 gPC 的最新发展似乎是一个有吸引力的选择。必须对可能的元素正交多项式的有效和准确构造进行系统研究。我们将在我们自己的 3 维基准问题上研究所开发的计算方法的适用性，该问题是在承受 4 点弯曲载荷的混凝土梁上进行的。该示例用于整体计算方法的参数研究。