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Probing the multi-physical probabilistic dynamics of a novel functional class of hybrid composite shells

机译：探讨一种新型杂种复合壳体函数类的多物理概率动态

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摘要

Functionally graded materials, sandwich structures and composite laminates have been widely investigated individually in last few decades for their respective set of advantages over conventional monolithic structures. However, the tremendous recent advances in manufacturing processes have opened up new frontiers of research specifically to form hybrid structures for multifunctional applications, where the advantages of each of the constituting components could potentially be exploited in a single structure. Such complex hybrid structures are often susceptible to manufacturing uncertainties and different forms of variability. To characterize the stochastic dynamic behaviour of these hybrid structural forms in a comprehensive, practically-relevant, yet efficient framework, here we present a multi-physical probabilistic vibration analysis based on Gaussian Process Regression (GPR) assisted finite element (FE) approach coupled with Monte Carlo Simulation. Integration of the GPR based machine learning model with the physics based simulation model leads to a significant level of computational efficiency in the quantification of system uncertainty. In the stochastic approach for various hybrid structural configurations, the compound effects of source-uncertainties are considered in order to assess the effect of different critical multi-physical parameters systematically involving material, geometric and physical aspects. The numerical results categorically indicate that the source-uncertainty of hybrid shells with different geometries has a significant effect on dynamic behaviour of the structure, which makes it imperative to take into account such probabilistic deviations to ensure adequate operational safety and serviceability.
机译：在过去的几十年中，在过去的几十年中，在过去的几十年中，夹层结构和复合层压板已广泛研究了传统整体结构的各自优点。然而，制造过程的巨大巨大进步已经开辟了专门用于形成多功能应用的混合结构的新的研究前沿，其中每个构成部件的优点可能在单个结构中被利用。这种复杂的混合结构通常易于制造不确定性和不同形式的变异性。在综合，实际相关但有效的框架中表征这些混合结构形式的随机动态行为，这里我们提出了一种基于高斯过程回归（GPR）辅助有限元（FE）接近的多物理概率振动分析蒙特卡罗模拟。基于GPR基于GPR基于基于物理的仿真模型的集成导致系统不确定度的量化的显着计算效率。在各种混合结构配置的随机方法中，考虑了源 - 不确定性的复合效应，以评估系统地涉及材料，几何和物理方面的不同临界多物理参数的影响。数值结果小分析了具有不同几何形状的混合壳的源性 - 不确定对结构的动态行为有显着影响，这使得考虑了这种概率偏差以确保适当的操作安全性和可用性。

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