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.
