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害机械元件模型提供有效的计算技术。为了治疗认知不确定性，即未知的输入随机场参数，将使用Dempster-Shafer P-box方法，并将其实现为自适应的嵌套采样策略。通过Karhunen-Loeve膨胀（KLE）或多项式混乱扩展（PCE），对Pboxesin依赖对输入现场模型方法的离散化的系统研究将得到研究。将采用自适应多层蒙特卡洛方案，以进行结构响应表面的有效采样。必须扩展该方案的嵌套认识论真实性抽样，以定义一些复杂的误差标准。重点是敏感性或可靠性分析响应量的响应量，即将产生剩余的负载轴承能力。在这里，将实施一种自适应的广义多项式混乱（GPC）方案，在此，对于元素gpc上的认知参数空间的新开发似乎是一个有吸引力的选择。必须进行有关元素在正交多项式的有效和准确构建的系统研究。开发的计算方法的适用性将在我们自己的三维基准标记问题上进行研究，该问题受到4点弯曲载荷的混凝土梁。此示例用于整体计算方法的参数研究。