CAREER: Cooperative Human-Computer Model Updating Cognitive Systems (MUCogS)

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。这个早期职业发展（career）项目的研究目标是为协作式人机模型更新认知系统（MUCogS）开发一个框架。常用的数值模拟技术，如有限元或边界元，提供了简单结构的精确表示，但是，除非将数据和额外的观测纳入这些模型，否则它们往往无法以理想的精度水平表示复杂现有结构的物理参数。利用模型更新技术对这些基于实验数据的数值模型进行了改进。目前的模型更新技术通过最小化实验测量值与数值模型产生的数据之间的误差来获得与现有结构最匹配的模型。分析师仅限于选择初始模型，调整几个算法参数或“旋钮”。并且对算法本身执行的过程几乎没有控制。本研究通过设计先进的算法来检测模型更新问题的几种合理解决方案，从而改变了这种范式。一个训练有素的工程师可以用他/她的工程判断选择一个或几个合适的模型进行后续分析。通过该框架，MUCogS正式将分析人员纳入模型更新技术，创建了一个协作的人机系统。这项研究在结构工程的任何领域都有直接的应用，包括现有结构的数值模拟（例如，地震工程，风力工程和结构健康监测）。这项研究的成功完成将大大提高工程师的素质。验证创新设计，评估现有结构的性能和检测损坏的能力。这一进步直接影响到用于基础设施维护和更换的州、联邦和私人预算。本研究的教育内容包括透过在结构工程课程中实施探究式教学，培养大学生的批判性思维，以发展工程判断能力。外联活动的重点是让拥有大量少数民族学生的城市学校了解结构工程。此外，本科生研究助理也包括在项目期间的研究活动中。

This award is funded under the American recovery and Reinvestment Act of 2009 (Public Law 111-5)The research objective of this early career development (CAREER) project is to develop a framework for cooperative human-computer Model Updating Cognitive systems (MUCogS). Commonly used numerical modeling techniques, such as finite or boundary elements, provide accurate representations of simple structures, but until data and additional observations are incorporated into these models they often fail to represent the physical parameters of complex existing structures with desirable levels of accuracy. Model updating techniques are used to enhance these numerical models based on experimental data. Current model updating techniques obtain one model that best matches the existing structure by minimizing the error between experimental measurements and data produced by the numerical model. The analyst is limited to the selection of an initial model, adjusting few algorithm parameters or ?knobs? and has little control on the process performed by the algorithm itself. This research changes this paradigm by designing advances algorithms to detect several plausible solutions to the model updating problem. A trained engineer can use his/her engineering judgment to select one or several appropriated models for subsequent analysis. Through this framework MUCogS formally include the analyst on the model updating technique creating a cooperative human-computer system.This research has direct application in any field of structural engineering that incorporates numerical modeling of existing structures (e.g., earthquake engineering, wind engineering and structural health monitoring). The successful completion of this research will significantly enhance an engineer?s ability to validate innovative designs, evaluate the performance and detect damage of existing structures. This advancement directly impacts state, federal and private budgets dedicated to infrastructure maintenance and replacement. The educational component of this research includes the development of engineering judgment among undergraduate students by nurturing critical thinking through the implementation of inquiry-based teaching in structural engineering classes. The outreach activities focus on exposing urban schools, with a significant population of minority students, to structural engineering. In addition, undergraduate research assistants are included on the research activities during the duration of the project.