CAREER: Higher-Order Methods for Nonlinear Stochastic Structural Dynamics

这个教师早期职业发展（CAREER）补助金是研究真实的，可观察到的动态负载是随机变化的性质（例如风速和压力）的结构，表现出复杂的行为的影响。这项研究将使更准确的结构建模，将通知高性能结构，以更低的成本运行更长的使用寿命改进的设计实践。该研究将适用于各种结构，其中效率至关重要，载荷高度不可预测，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，以更详细地模拟这些随机变化的负载的性质比以前可能的。利用这些研究，不同类别的结构受到这样的环境的响应将进行调查，以优化性能的最终目标。该奖项还将支持新的本科研究模块的开发，这些模块将公开提供，旨在向学生介绍研究职业，并教授学术界以外有用的基本研究技能。许多物理现象的特征是复杂的随机过程，表现出强烈的非高斯和非线性特征。本项目将建立新的方法来表征和合成这些高阶随机过程，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-是特别敏感的随机激励的性质，并可能表现出显着不同的结构行为的基础上看似微小的变化，随机激励。目前，非线性结构响应对随机激励的各种特征的敏感性还没有得到很好的理解。本研究将针对不同类别的非线性结构系统，广泛研究此敏感度，并发展新的拓扑优化模式，以提升结构性能。

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.