论文标题
膜织物非线性动态多尺度建模的计算典型框架
A Computationally Tractable Framework for Nonlinear Dynamic Multiscale Modeling of Membrane Fabric
论文作者
论文摘要
提出了一种通用计算均质化框架,用于表现出复杂显微镜和/或中尺度异质性的膜的非线性动态分析,其平面周期性特征在于无法通过常规方法(例如Woven Fabrics)有效治疗的平面周期性。该框架是对“有限元平方”(或FE2)方法的概括,其中使用有限元元素对周期子量表结构的本地化部分进行建模。涉及该模型的位移驱动问题的数值解决方案可以通过klinkel-govindjee方法的变体[1]适应膜的上下文,该变体最初提出了用于使用有限菌株,光束和壳元素中的三维材料模型。这种方法依赖于平面应力约束的数值执行,并由框架不变性原理启用。通过引入基于回归的替代模型来实现计算障碍,该模型是由物理启发的训练方案告知的,其中Fe $^2 $用于模拟各种数值实验,包括单轴,双轴,双轴和剪切材料优惠券。评估了几种替代性替代模型,包括人工神经网络。该框架已被证明和验证,用于现实的火星着陆施用,涉及由机织织物制成的降落伞顶篷的超音速通胀。
A general-purpose computational homogenization framework is proposed for the nonlinear dynamic analysis of membranes exhibiting complex microscale and/or mesoscale heterogeneity characterized by in-plane periodicity that cannot be effectively treated by a conventional method, such as woven fabrics. The framework is a generalization of the "finite element squared" (or FE2) method in which a localized portion of the periodic subscale structure is modeled using finite elements. The numerical solution of displacement driven problems involving this model can be adapted to the context of membranes by a variant of the Klinkel-Govindjee method[1] originally proposed for using finite strain, three-dimensional material models in beam and shell elements. This approach relies on numerical enforcement of the plane stress constraint and is enabled by the principle of frame invariance. Computational tractability is achieved by introducing a regression-based surrogate model informed by a physics-inspired training regimen in which FE$^2$ is utilized to simulate a variety of numerical experiments including uniaxial, biaxial and shear straining of a material coupon. Several alternative surrogate models are evaluated including an artificial neural network. The framework is demonstrated and validated for a realistic Mars landing application involving supersonic inflation of a parachute canopy made of woven fabric.