Reliability-Based Multidisciplinary Systems Design Under Time-Dependent Uncertainty

该奖项的目标是探索在依赖时间的不确定性下将高可靠性设计到多学科系统中的最佳方法。随着时间的推移，随机变化的时间依赖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。为了更好地应对多学科系统设计中的挑战，所开发的方法将专门考虑诸如子系统之间的耦合、系统响应的非线性以及昂贵的系统模拟等复杂性。这项研究将结合多学科系统设计和高级时间相关可靠性分析的方法。该集成将准确地预测给定设计变量集的失效时间分布，从而允许设计变量与依赖时间的系统可靠性之间的直接联系。然后利用多学科设计优化(MDO)，可以自动识别出期望的系统可靠性和降低成本的最优系统设计。如果成功，本研究的结果将影响工程设计的广泛领域，并将适用于从大型国防和民用系统到小型集成电路系统的广泛工程应用。除了工程设计，将受益的潜在领域包括能源、系统工程、运营研究、管理和可靠性工程，在这些领域，依赖时间的概率方法发挥着至关重要的作用。这个项目的知识将通过研讨会、会议报告和期刊文章来传递。将研究成果引入课堂也将提高对不确定性的认识，并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.