Estimating Probability of Improvement in Next Cycle of Surrogate Based Design Optimization

该奖项的研究目标是提供对在下一个基于代理的设计优化周期中实现目标改进水平的可能性的准确估计，从而提高整个设计过程的成本效益。在复杂工程系统的设计优化中，如汽车(例如耐撞性)、航空航天(例如液体火箭喷射器)、石油(例如化学注水)和生物机械(例如膝盖植入物)行业中的那些系统，考虑到工业环境中存在的时间限制，如何满足提高性能、降低成本和增强安全性的相互冲突的目标是一个主要挑战。基于代理的设计优化(SBDO)分阶段或循环进行，已被证明是解决这一挑战的有效方法。它指的是依赖于在每个周期收集的计算昂贵/高保真模拟的减少样本上构建/更新的替代物或元模型(计算成本较低)的设计优化。每个周期都是昂贵的，尽管取得了进展，但目前关于SBDO的知识状况缺乏基于统计的停止标准，无法评估投资于另一个优化周期与接受目前最佳解决方案的好处。如果成功，这项研究将通过使用替代替代模型估计和评估信息来解决目前工业实践中的缺陷，为SBDO提供严格的停止标准。这项研究将在生物力学工程中最重要的问题之一：人工膝关节的设计中得到验证，以最大限度地减少磨损，从而避免第二次替换的需要。人工膝关节的磨损分析在计算上非常昂贵，而且模拟次数的限制使其成为SBDO的理想应用。预计将通过互联网免费提供的计算工具、会议报告、期刊出版物和工程设计优化课程来传播这些成果。这项研究将受益于与巴西、委内瑞拉和法国研究人员的持续合作。

The research objective of this award is to provide accurate estimates of the probability of achieving a target level of improvement in the next surrogate based design optimization cycle, hence increasing the cost-effectiveness of the overall design process. A major challenge in the design optimization of complex engineering systems such as those found in the automotive (e.g., crashwordiness), aerospace (e.g., liquid rocket injector), oil (e.g., chemical flooding) and biomechanical (e.g., knee implants) industries is how to meet the conflicting objectives of improved performance, reduced costs and enhanced safety considering the time constraints present in industrial environments. Surrogate-based design optimization (SBDO), which proceeds in stages or cycles, has shown to be an effective approach to address this challenge. It refers to design optimization that relies on the use of surrogates or metamodels (computationally inexpensive) built/updated on reduced samples of computationally expensive/high fidelity simulations collected at each of the cycles. Each cycle is costly, and in spite of the progress, the current state-of-knowledge regarding SBDO lacks statistics-based stopping criteria for assessing the merit of investing in another cycle of optimization versus accepting the present best solution. If successful, the research will address the shortcomings of present industrial practice through the use of alternative surrogate model estimation and appraisal information to provide a rigorous stopping criterion for SBDO. The research will be validated addressing one of the most significant problems in biomechanical engineering: the design of artificial knees for minimizing wear and hence avoiding the need for a second replacement. Wear analysis of artificial knees is computationally very costly and the limit on number of simulations makes it an ideal application of SBDO. The results are expected to be disseminated through computational tools which will be freely available via the internet, and conference presentations, journal publications and engineering design optimization courses. The research will benefit from an ongoing collaboration with Brazilian, Venezuelan, and French researchers.