CAREER: Higher-Order Methods for Nonlinear Stochastic Structural Dynamics

这项学院早期职业发展(Career)补助金是为了研究真实的、可观察的动态载荷对表现出复杂行为的结构的影响，这些载荷在性质上是随机变化的(例如风速和压力)。这项研究将实现更准确的结构建模，为高性能结构的改进设计实践提供信息，这些结构以更低的成本运行更长的使用寿命。这项研究将适用于效率至关重要、载荷高度不可预测的所有类型的结构，从民用结构到飞机、汽车、船舶和航天器。该奖项支持基础研究，以比以前更详细地模拟这些随机变化的负载的性质。利用这些研究，将调查不同类别的结构在这种环境下的反应，最终目的是优化性能。该奖项还将支持开发新的本科研究模块，这些模块将公开提供，旨在向学生介绍研究领域的职业，并教授学术以外有用的基本研究技能。许多物理现象都具有复杂的随机过程，表现出强烈的非高斯性和非线性特征。这个项目将建立新的方法来表征和综合这些高阶随机过程，这些过程将被用作各种非线性结构系统的激励。本文研究的非线性结构系统--包括超弹性、弹塑性和混沌系统--对随机激励的性质特别敏感，并且可能基于随机激励的看似微小的变化而表现出截然不同的结构行为。目前，非线性结构响应对随机激励的各种特征的敏感性还不是很清楚。本研究将广泛研究不同类型的非线性结构系统的这种敏感性，并开发新的拓扑优化模型以提高结构的性能。

This Faculty Early Career Development (CAREER) grant is to study the influence of real, observable dynamic loads that are randomly varying in nature (e.g. wind velocity and pressure) on structures that exhibit complex behavior. This study will enable more accurate structural modeling that will inform improved design practices for high performance structures that operate for longer service lives at lower cost. The research will be applicable to structures of all sorts where efficiency is critical and loads are highly unpredictable, ranging from civil structures to aircraft, automobiles, ships, and spacecraft. This award supports fundamental research to simulate the nature of these randomly varying loads in greater detail than has been previously possible. Leveraging these studies, the response of different classes of structures subjected to such environments will be investigated with the ultimate aim of optimizing performance. The award will also support the development of new undergraduate research modules, which will be made publicly available, designed to introduce students to careers in research and teach basic research skills that are useful beyond academia. Many physical phenomena are characterized by complex stochastic processes that exhibit strongly non-Gaussian and nonlinear features. This project will build new methods for characterizing and synthesizing these higher-order stochastic processes that will be used as excitation for various nonlinear structural systems. The nonlinear structural systems studied herein - including hyperelastic, elastic-plastic, and chaotic systems - are especially sensitive to the nature of the stochastic excitation and may exhibit drastically different structural behavior based on seemingly minor changes in the stochastic excitation. Currently, the sensitivity of nonlinear structural response to various features of the stochastic excitation is not well understood. This research will extensively study this sensitivity for different classes of nonlinear structural systems and develop new topology optimization model to enhance structural performance.