Fuzzy-stochastic three-scale modeling for polymorphic uncertainty in lightweight structures

轻质结构多态不确定性的模糊随机三尺度建模

• 批准号: 311889577
• 负责人: Dr.-Ing. Ismail Caylak, since 3/2024
• 金额: --
• 依托单位: Lehrstuhl für Technische Mechanik (LTM)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/311889577?language=en
• 关键词: Fuzzy; stochastic; three; scale; modeling

The overall aim of the research project is to transfer the polymorphic uncertainty models developed in the first funding period into the life cycle of hybrid lightweight structures. In particular, the manufacturing as well as the subsequent use during service time of fiber reinforced plastics (FRPs) in hybrid systems are investigated.During the manufacturing process curing of the matrix is a dominant effect as it is highly temperature dependent and influences strongly the mechanical, thermal and chemical properties of FRPs. During the service time damage and failure are dominant effects, resulting e.g. from repeated loading or crash. The modeling of both, the manufacturing process and the subsequent use during service time can be done on different scales. The entire modeling from manufacturing to service time is implemented using a three-scale model that takes into account curing and damage combined to polymorphic uncertainty. This model is applied to determine effective properties from one scale to the next higher. Uncertainties are quantified from already existing experimental data. Suitable fuzzy-stochastic homogenization methods determine the polymorphic uncertain effective properties of the matrix after curing. In combination with the properties of the fibers macro scale effective parameters are obtained for the composite by suitable fuzzy-stochastic homogenization methods. These effective parameters are compared with existing experimental data of the composite. In order to investigate not only the uncertainty of the composite, additional biaxial tests will be performed in order to investigate dependencies of individual parameters of the composite.In order to adequately represent real loading conditions during the service time, uncertain failure mechanisms by use of homogenization methods are taken into account. As a starting point, existing heterogeneous data will be used to quantify uncertainty in damage parameters. In order to consider complex structures for the validation of the model, the developed fuzzy-stochastic methods are extended to a finite element formulation. For comparison already existing experimental results are used for a top hat profile.

该研究项目的总体目标是将第一个资助期开发的多态不确定性模型转移到混合轻质结构的生命周期中。特别是，制造以及随后的使用过程中的服务时间的纤维增强塑料（FRP）在混杂系统中进行了调查。在制造过程中，固化的基质是一个占主导地位的作用，因为它是高度依赖于温度和强烈影响的机械，热和化学性能的FRP。在使用期间，损坏和故障是主要影响，例如由重复加载或碰撞引起。制造过程和服务期间的后续使用的建模可以在不同的尺度上进行。从制造到服务时间的整个建模是使用三尺度模型，考虑到固化和损坏相结合的多态性的不确定性。该模型适用于确定从一个尺度到下一个更高尺度的有效属性。从现有的实验数据中定量分析了非线性。合适的模糊随机均匀化方法确定固化后的矩阵的多态不确定有效属性。结合纤维的特性，采用模糊随机均匀化方法，得到了复合材料宏观有效参数。这些有效参数与现有的复合材料的实验数据进行了比较。为了不仅研究复合材料的不确定性，还将进行额外的双轴试验，以研究复合材料各个参数的相关性。为了充分代表使用期间的真实的载荷条件，考虑使用均匀化方法的不确定失效机制。作为一个起点，现有的异构数据将被用来量化损伤参数的不确定性。为了考虑复杂的结构模型的验证，开发的模糊随机方法扩展到有限元制剂。为了比较，已经存在的实验结果被用于顶帽轮廓。