Robust Design
Issued by
University of Connecticut
Earners of this badge can create computational models for the simulation and mathematical optimization of cyber-physical systems subject to uncertainty, including the identification of performance/safety specifications and sources of uncertainty. They can verify system performance under uncertainty and reduce the impacts of uncertainty on performance/safety-critical systems. They can validate systems models subject to parametric uncertainty and conduct regression analysis of uncertain systems.
- Type Validation
- Level Advanced
- Time Weeks
- Cost Paid
Skills
Earning Criteria
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Badge earners complete SE 5102 Uncertainty Analysis, Robust Design, and Optimization course at the University of Connecticut, which is a hybrid-online graduate course that can be taken from anywhere in the world. Earners can take this graduate course as a matriculated UConn graduate student or as a non-degree graduate student, which does not require admission to the UConn graduate school. Badge holders complete a course-long project and must earn a B- or better on this project to earn the badge.
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Badge earners can apply systems engineering methods and principles for the design and operation of real-world cyber-physical systems and develop and update formal specifications and verification methods for cyber-physical systems designs. They can identify sources and model uncertainty to simulate and analyze system performance under uncertainty. See Standard [1] NAE-CPS below.
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Badge earners can perform formal optimization of systems models to design and verify systems that meet stakeholder requirements, use analysis techniques to support architectural design processes, can contribute and interpret designs, can assess design trade-offs and feasibility, and can develop computationally tractable models involving multi-physics and multiscale phenomena to predict the performance of complex systems. See Standard [2] DOE-SIAM below.
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Badge earners can use modeling and simulation tools and techniques to represent a system and can apply analysis techniques to derive information about a system. See Standard [3] INCOSE ISECF below.
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Badge earners complete a course-long project consisting of a proposal, weekly reports, and a final report. They develop a computational model of a system that accounts for sources of uncertainty using a scientific computing language. The model defines performance & safety specifications, simulated, and optimized with respect to an appropriate objective subject to imposed constraints to determine design and operational parameters that minimize the impacts of uncertainty on system performance.
Standards
A 21st Century Cyber-Physical Systems Education. Committee on 21st Century Cyber-Physical Systems Education; Computer Science and Telecommunications Board; Division on Engineering and Physical Sciences; National Academies of Sciences, Engineering, and Medicine. ISBN 978-0-309-45163-5 | DOI: 10.17226/23686
SIAM APPLIED MATHEMATICS AT THE U.S. DEPARTMENT OF ENERGY: Past, Present and a View to the Future. A Report by an Independent Panel from the Applied Mathematics Research Community May 2008.
INCOSE Systems Engineering Competency Framework. July 2018. INCOSE Technical Product Reference: INCOSE-TP-2018-002-01.0