Computational Methods for Optimized Reliability and Efficiency in Smart Structural Systems

该研究的目标是开发新的计算技术，用于结构部件的无损评价（NDE），为结构性能的当前状态提供快速，可靠和高度准确的定量评估。算法将联合收割机结构响应的有效计算模型与优化方法相结合，以利用给定的一组传感器测量来识别结构的退化状态。 为了获得高水平的效率和准确性，新的模型简化技术将建立为NDE应用定制。 此外，算法将定义激励结构和测量结构响应的最佳方法，以提供对损伤的高分辨率局部描述。测试方法将被设计成最大限度地提高结构性能对测试参数的敏感性，并将适用于从核反应堆到桥梁结构的大量NDE应用。研究结果将使工程师能够更有效，更准确地预测当前的退化状态和结构的剩余寿命，从而更及时地对危险情况做出反应，减少误报和关闭。 该项目中开发的算法将免费传播给社区，以供广泛使用和未来发展。这项研究将为研究生和本科生提供高级培训，并与多样性办公室合作，为本科生和大学预科生建立一个夏季研究计划，以吸引来自传统上代表性不足的群体的学生参与工程。

The goal of the research is to develop new computational techniques for nondestructive evaluation (NDE) of structural components that will provide fast, reliable, and highly accurate quantitative evaluation of the current state of structural properties. Algorithms will combine efficient computational models of the structural response with optimization approaches to identify the structure's state of degradation with a given set sensor measurements. To obtain high level of efficiency and accuracy, novel model reduction techniques will be established that are tailored for NDE applications. In addition, the algorithms will define the optimal methods of exciting the structure and measuring the structural response to provide a high-resolution local description of the damage. The testing methods will be designed to maximize the sensitivity of the structural properties to the test parameters and will be applicable to a host of NDE applications from nuclear reactor to bridge structures. The research results will enable engineers to more efficiently and accurately predict the current state of degradation and the remaining life of a structure, leading to more timely response to hazardous conditions and fewer false alarms and closures. The algorithms developed in the project will be freely disseminated to the community for wide-spread use and future developments. The research will provide advanced training to graduate and undergraduate students and establish a summer research program for undergraduates and pre-college students in collaboration with the office of diversity to engage students from traditionally underrepresented groups in engineering.