BRIGE: Multiscale Model-Data Fusion for Structural Health Monitoring of Fracture Critical Structures

项目意义的非技术描述这一扩大参与的研究启动拨款(Brige)提供资金，以开发结构健康监测、诊断和骨折关键结构的预后的框架。断裂临界结构是指单个部件的失效可能导致整个系统或很大一部分系统失效的结构。最近这些类型的结构，特别是桥梁的灾难性故障，突显了对这一问题采取新的变革性办法的必要性。该项目将开发必要的计算和数据分析工具，以持续监测断裂的关键结构，并帮助防止此类故障。项目技术说明多尺度模型-数据融合框架依赖于一系列模型，这些模型代表了结构在不同尺度上的力学行为，以及局部和全局结构响应的振动测量。该项目将开发能够将多尺度有限元模型的预测能力和传感器测量优化结合的算法，以实时重建结构的完整响应。重建的响应可以评估整个结构的累积疲劳损伤的当前状态，从而在达到临界水平之前预测潜在的损伤。估计的损伤条件及其相关的不确定性被投射到未来，并且可以获得结构可靠性的估计。这项研究涉及计算算法的开发、实验室实验和现场验证，使用的是佛蒙特州一座仪表化运营桥梁的真实数据。该项目开发的方法将帮助工程师对跨越土木、机械、生物医学和电气应用的大量传统和非传统结构系统进行更智能的早期诊断和预测性维护。该项目还将提供一个机会，促进研究想法在医疗诊断中的合作和潜在应用。扩大代表不足群体参与工程学的活动将使首席调查员能够将代表不足的少数群体招募到工程学教育、研究和指导中。它还将使他能够开展K-12活动，旨在教育学生关于工程、多样性及其在我们社会中的关键重要性的教育。该项目将促进与佛蒙特大学现有举措的合作，这些举措旨在招收本科生和研究生，特别是对从事工程工作感兴趣的女性和拉丁裔学生。PI将与不同的学生团体合作，如女性工程师协会和美国土木工程师协会的分会，这些组织自愿参与与K-12学生分享工程经验。这些团体将与国际和平协会一起访问当地学校，并在大学举办招聘和教育活动。该项目的教育部分包括开发一个动手结构工程实验室，旨在帮助学生欣赏模型和传感器在理解结构行为方面的作用。PI还将开发一门名为工程系统可靠性的多学科课程，面向所有工程学科的研究生。本课程将把研究项目中的数据和发现纳入课程学习目标。这项研究是通过工程教育和中心分部扩大工程参与计划的一部分-扩大工程招揽中的参与研究启动补助金-资助的。研究也通过国际和综合活动办公室的刺激竞争研究的实验计划(EPSCoR)资助。

Non-Technical Descripition of the Project's SignificanceThis Broadening Participation Research Initiation Grant (BRIGE) provides funding to develop a framework for structural health monitoring, diagnosis and prognosis of fracture critical structures. Fracture critical structures are those in which the failure of a single component can generate the failure of the complete system or a large portion of it. Recent catastrophic failures of these types of structures, especially bridges, have highlighted the need for a new and transformative approach to the problem. This project will develop the computational and data analysis tools necessary to continuously monitor fracture critical structures and help prevent such failures. Technical Description of the ProjectThe multiscale model-data fusion framework relies on a series of models, which represent the mechanical behavior of the structure at various scales of interest, and vibration measurements of local and global structural response. The project will develop algorithms capable of optimally combining the predictive capabilities of multiscale finite element models and sensor measurements, to reconstruct in real-time the complete response of the structure. The reconstructed response allows assessment of the current state of cumulative fatigue damage throughout the structure, thus anticipating potential damage before it reaches a critical level. The estimated damage condition, with its associated uncertainty is projected into the future and an estimate of the structural reliability can be obtained. The research involves development of computational algorithms, laboratory experiments and field validation using real data from an instrumented operational bridge in Vermont. The methods developed in this project will aide engineers to perform smarter early diagnosis and predictive maintenance of a multitude of conventional and non-conventional structural systems spanning civil, mechanical, biomedical and electrical applications. This project will also provide an opportunity to foster collaborations and potential applications of the research idea into medical diagnosis. Activities to Broaden the Participation of Underrepresented Groups in EngineeringFunding from this project will enable the principal investigator to recruit under-represented minorities into engineering education, research and mentoring. It will also allow him to undertake K-12 activities aimed at educating students about engineering, diversity and its critical importance in our society. This project will facilitate collaborations with existing initiatives at the University of Vermont aimed at recruiting undergraduate and graduate students, especially female and Latinos interested in pursuing careers in engineering. The PI will work with various student groups, such as the chapters of the Society of Women Engineers and American Society of Civil Engineers, which have volunteered to take part in sharing the engineering experience with K-12 students. These groups will join the PI in visiting local schools and hosting recruiting and educational activities at the university. The educational component of the project involves the development of a hands-on structural engineering lab designed to help students appreciate the role of models and sensors in understanding the behavior of structures. The PI will also develop a multidisciplinary course titled Reliability of Engineering System aimed at graduate students from all engineering disciplines. This course will incorporate data and findings from the research project into the course learning objectives.This research has been funded through the Broadening Participation Research Initiation Grants in Engineering solicitation, which is part of the Broadening Participation in Engineering Program of the Engineering Education and Centers Division.The research is also funded through the Experimental Program to Stimulate Competitive Research (EPSCoR), which is part of the Office of International and Integrative Activities.