Collaborative Research: EAGER - Managing Uncertainty by Integrating Information Economics and Robust Design

EAGER奖的研究目标是建立一种管理多级设计过程中不确定性的方法的基础。在设计复杂系统时，减少不确定性通常会导致计算成本的显著增加;减少计算工作量的努力需要使用更简单的模型，从而导致不确定性增加。因此，有必要研究和开发方法，以找到正确的平衡之间的不确定性和计算工作，同时作出良好的设计决策。中心假设是，可以通过平衡不确定性缓解的努力和系统性能方面获得的好处来管理多级设计过程网络中的不确定性及其传播的影响。成功完成后，这个项目将提供基础知识和方法来管理复杂系统的多级设计中的不确定性。如果成功，该奖项的成果将是：a）量化建模和计算工作的方法; B）在与不确定性缓解相关的工作和设计结果之间做出权衡决策的方法; c）整合信息经济学和鲁棒设计的框架;以及d）可用于对复杂工程系统的基于仿真的设计中的不确定性缓解进行系统研究的经验证的概念。拟议的研究是转型，因为它的重点是不确定性管理，通过努力和效益之间的权衡，而不是不确定性缓解方法，其特点是只需要增加模型的准确性在设计过程中的网络。概念验证的成功演示将为开展和提出更广泛的研究奠定基础。除了在学术文献中发表，这项工作的工业相关部分将在研讨会和贸易会议上提出。PI将通过其活动ASME和SWE学生分会，Pi Tau Sigma以及吸引代表性不足的少数民族的计划，积极招募和指导代表性不足的少数民族和妇女。

The research objective of this EAGER award is to establish the foundations of a method for managing uncertainty within multilevel design processes. Mitigation of uncertainty in designing complex systems typically results in a significant increase in computational cost; efforts to reduce computational effort necessitate the use of simpler models resulting in increased uncertainty. Hence, there is a need to research and develop methods to find the right balance between uncertainty and computational effort while making good design decisions. The central hypothesis is that the effect of uncertainty and its propagation in multilevel design process networks can be managed by balancing the effort of uncertainty mitigation and the benefit gained in terms of system performance. On successful completion this project will provide the foundational knowledge and approaches to managing uncertainty in the multilevel design of complex systems. If successful, the outcomes of this award will be: a) an approach for quantifying modeling and computational effort; b) an approach for making tradeoff decisions between the effort associated with uncertainty mitigation and design outcomes; c) a framework integrating information economics and robust design; and d) a validated concept that can be used to carry out systematic studies on uncertainty mitigation in simulation-based design of complex engineering systems. The proposed research is transformational because of its focus on uncertainty management through tradeoff between effort and benefit, as opposed to uncertainty mitigation approaches that are characterized solely by the need to increase the accuracy of models in a design process network. Successful demonstration of the proof of concept will result in a foundation upon which more extensive research will be performed and proposed. In addition to publishing in the scholarly literature, the industrially relevant portions of this work will be presented at workshops and trade meetings. The PIs will proactively recruit and mentor underrepresented minorities and women through their activities ASME and SWE student chapters, Pi Tau Sigma, and programs to attract under-represented minorities.