Reliability-Based Multidisciplinary Systems Design Under Time-Dependent Uncertainty

该奖项的目标是探索在时间依赖不确定性下设计高可靠性多学科系统的最佳方法。随时间的随机变化，时间相关的不确定性是阻碍系统在其服务期内执行其预期功能的能力或可靠性的主要因素。本研究旨在最大限度地降低时变不确定性对系统可靠性的影响。为了最好地解决多学科系统设计中的挑战，开发的方法将特别考虑子系统之间的耦合、系统响应的非线性和昂贵的系统模拟等复杂性。本研究将整合多学科系统设计和先进的时变可靠性分析方法。集成将准确地预测给定设计变量集的故障时间分布，因此允许在设计变量和依赖时间的系统可靠性之间建立直接联系。然后利用多学科设计优化（MDO），自动识别出具有理想系统可靠性和降低成本的最优系统设计。如果成功，这项研究的结果将影响工程设计的广泛领域，并将适用于广泛的工程应用，从大型国防和民用系统到小型集成电路系统。除了工程设计之外，潜在的受益领域包括能源、系统工程、运运学、管理和可靠性工程，在这些领域，时间相关的概率方法起着至关重要的作用。本项目的知识将通过研讨会、会议报告和期刊文章传递。将研究成果引入课堂也将提高对不确定性的认识，更好地培养工科学生的概率技能。

The objective of this award is to explore optimal ways to design high reliability into multidisciplinary systems under time-dependent uncertainty. Varying randomly over time, time-dependent uncertainty is the major factor that hinders the ability or reliability of a system to perform its intended function over its service period. This research aims to optimally reduce the effect of time-dependent uncertainty on the system reliability. To best address the challenges in multidisciplinary systems design, the developed methodologies will specifically account for complexities such as coupling between subsystems, nonlinearity of system responses, and expensive system simulations. This research will integrate methodologies of both multidisciplinary systems design and advanced time-dependent reliability analysis. The integration will accurately predict the time-to-failure distribution for a given set of design variables, hence allowing for a direct link between design variables and time-dependent system reliability. Then with multidisciplinary design optimization (MDO), optimal system designs can be automatically identified with desired system reliability and reduced cost.If successful, the results of this research will impact broad areas of engineering design and will be applicable to wide engineering applications, ranging from large defense and civil systems to small integrated circuit systems. Beyond engineering design, potential areas that will benefit include energy, system engineering, operations research, management, and reliability engineering, where time-dependent probabilistic approaches play a vital role. The knowledge from this project will be transferred through seminars, conference presentations, and journal articles. The introduction of the research results into the classroom will also increase awareness of uncertainties and better foster engineering students' probabilistic skills.