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Design Space Covering for Uncertainty: Exploration of a New Methodology for Decision Making in Early Stage Design
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Design Space Covering for Uncertainty: Exploration of a New Methodology for Decision Making in Early Stage Design. |
| 개인저자 | Claus, Lauren Rose. |
| 단체저자명 | University of Michigan. Naval Architecture & Marine Engineering. |
| 발행사항 | [S.l.]: University of Michigan., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 90 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-04B. Dissertation Abstract International |
| ISBN | 9781687927538 |
| 학위논문주기 | Thesis (Ph.D.)--University of Michigan, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Advisor: Collette, Matthew David. |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | Decisions made in early-stage design are of vital importance as they significantly impact the quality of the final design. Despite recent developments in design theory for early-stage design, designers of large complex systems still lack sufficient tools to make robust and reliable preliminary design decisions that do not have a lasting negative impact on the final design. Much of the struggle stems from uncertainty in early-stage design due to loosely defined problems and unknown parameters. Existing methods to handle this uncertainty in point-based design provide feasible, but often suboptimal, solutions that cover the range of uncertainty. Robust Optimization and Reliability Based Design Optimization are examples of point-based design methods that handle uncertainty. To maintain feasibility over the range of uncertainty, these methods accept suboptimal designs resulting in a design margin. In set-based design, design decisions are delayed preventing suboptimal final designs but at the expense of computational efficiency. This work proposes a method that evaluates a compromise between these two methodologies by evaluating the trade off of the induced regret and computational cost of keeping a larger design space. The design space covering for uncertainty (DSC-U) problem defines the metrics regret, which measures suboptimality, and space remaining, which quantifies the design space size after it is reduced. Solution methods for the DSC-U problem explore the trade space between these two metrics. When there is uncertainty in a problem, and the design space is reduced, there is the possibility that the optimal solution for the realized values of the uncertainty parameters has been eliminated |
| 일반주제명 | Naval engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
