CAREER: Higher-Order Methods for Nonlinear Stochastic Structural Dynamics

这项教师早期职业发展（Career）资助是为了研究真实的、可观察的、随机变化的动态载荷（如风速和压力）对表现出复杂行为的结构的影响。这项研究将使更准确的结构建模成为可能，这将为高性能结构的改进设计实践提供信息，这些结构可以以更低的成本延长使用寿命。该研究将适用于从民用结构到飞机、汽车、船舶和航天器的各种结构，这些结构的效率至关重要，载荷高度不可预测。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载荷的性质。利用这些研究，不同类型的结构在这种环境下的响应将被研究，最终目的是优化性能。该奖项还将支持新的本科研究模块的开发，这些模块将向公众开放，旨在引导学生从事研究工作，并教授对学术以外有用的基本研究技能。许多物理现象的特点是复杂的随机过程，表现出强烈的非高斯和非线性特征。该项目将建立表征和综合这些高阶随机过程的新方法，这些过程将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，非线性结构响应对各种随机激励特征的敏感性还没有得到很好的认识。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.