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，研究了混合系统中纤维增强塑料 (FRP) 的制造以及随后在使用过程中的使用。在制造过程中，基体的固化是主要影响，因为它高度依赖于温度，并且强烈影响 FRP 的机械、热和化学性能。在使用期间，损坏和故障是主要影响，例如导致避免重复加载或崩溃。制造过程和服务期间的后续使用的建模可以在不同的规模上完成。从制造到使用时间的整个建模是使用三尺度模型实现的，该模型考虑了固化和损坏以及多态不确定性。该模型用于确定从一个尺度到下一个更高尺度的有效属性。不确定性是根据现有的实验数据进行量化的。合适的模糊随机均质化方法决定了固化后基体的多晶型不确定有效特性。结合纤维的特性，通过合适的模糊随机均化方法获得复合材料的宏观有效参数。将这些有效参数与复合材料的现有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测试，以研究复合材料各个参数的依赖性。为了充分表示使用期间的真实负载条件，考虑使用均质化方法的不确定失效机制。作为起点，现有的异构数据将用于量化损伤参数的不确定性。为了考虑模型验证的复杂结构，将所开发的模糊随机方法扩展到有限元公式。为了进行比较，现有的实验结果被用于高顶帽轮廓。