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

这个EAGER奖项的研究目标是建立管理多层次设计过程中不确定性的方法的基础。在设计复杂系统时，降低不确定性通常会导致计算成本的显著增加；为了减少计算工作量，必须使用更简单的模型，从而增加不确定性。因此，有必要研究和开发方法，在做出良好设计决策的同时，在不确定性和计算工作量之间找到适当的平衡。中心假设是不确定性的影响及其在多层次设计过程网络中的传播可以通过平衡不确定性缓解的努力和在系统性能方面获得的利益来管理。本课题的成功完成将为管理复杂系统多层次设计中的不确定性提供基础知识和方法。如果成功，该奖项的结果将是：a)一种量化建模和计算工作的方法；B)在与不确定性缓解相关的努力与设计结果之间做出权衡决策的方法；C)整合信息经济学和稳健设计的框架；d)一个经过验证的概念，可用于开展基于仿真的复杂工程系统设计中不确定性缓解的系统研究。拟议的研究是变革性的，因为它侧重于通过努力和利益之间的权衡来管理不确定性，而不是仅仅以需要增加设计过程网络中模型的准确性为特征的不确定性缓解方法。概念验证的成功演示将为进行和提出更广泛的研究奠定基础。除了在学术文献中发表外，这项工作与工业有关的部分将在讲习班和贸易会议上提出。Pi将积极招募和指导代表性不足的少数民族和妇女，通过他们的活动ASME和SWE学生分会，Pi Tau Sigma和项目，以吸引代表性不足的少数民族。

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.