An Integrated Platform for Validated Prediction of Collapse of Structures

本研究旨在建立一个可靠的程序，以准确评估钢框架结构的倒塌。了解结构倒塌的原因和影响对于制定国家建筑规范、区域应急响应计划和风险管理战略等关键文件至关重要。本项目将开发一种用于结构倒塌详细评估的黏聚区方法，以及一种用于完整框架结构整体倒塌评估的基于紧致塑性的宏观梁单元方法。这两种方法将共同为包括强度退化和拓扑变化在内的坍塌演化提供系统的方法。该方法将使用具有代表性的测试平台实例进行验证。然后将开发随机算法，包括贝叶斯参数估计方法和模式分类方法，以验证目前用于预测崩溃的一些简单非线性方法。该研究将有助于确定控制结构倒塌能力的关键参数和损伤措施。本项目开发的数值和分析工具将有助于制定更好的建筑规范条款，以防止不成比例的倒塌，并有助于依赖于对一个区域建筑物倒塌的准确评估的区域损失评估。这项研究将确定新的抗倒塌结构设计，以提高极端载荷下的公共安全。研究结果将被纳入研究生水平的极端载荷和风险评估的结构设计主题课程。将积极利用已建立的机构奖学金计划，从科学技术领域代表性不足的群体中招收学生。通过参与研究项目，两名研究生和两名本科生研究助理将获得高级培训，加入国家训练有素的劳动力队伍。

This research aims to establish a robust procedure for accurate assessment of the collapse of steel frame structures. Understanding the causes and effects of structural collapse is critical to develop key documents such as national building codes, regional emergency response plans, and risk management strategies. This project will develop a cohesive-zone method for detailed assessment of structural collapse, and a compact plasticity-based macro beam element method for global collapse assessment of a complete frame structure. Together, these two methods will provide a systematic approach for evolution of collapse, including strength degradation and topology changes. The approach will be validated using representative testbed examples. Stochastic algorithms including Bayesian parameter estimation methods and pattern classification methods will then be developed for validating some simple nonlinear methods that are currently used to predict collapse. The research will help in identifying the key parameters and damage measures that govern the collapse capacity of a structure.The numerical and analytical tools developed in this project will help in the development of better building code provisions that seek to prevent disproportionate collapse and in regional loss assessments that rely on accurate assessment of building collapse in a region. The research will identify new collapse resistant structural designs to enhance public safety under extreme loads. The research results will be incorporated in the graduate level courses on the topics of structural designs for extreme loads and risk assessment. Active efforts will be made to recruit students from the groups that are underrepresented in science and technology fields using the well-established institutional fellowship programs. Through their involvement in the research project, two graduate students and two undergraduate research assistants will be provided advanced training to join the Nation's highly trained workforce.