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research-article

Quantifying the Resilience-Informed Scenario Cost Sum (RISCS): A Value-Driven Design Approach for Functional Hazard Assessment

[+] Author and Article Information
Daniel Hulse

Graduate Research Assistant, School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University Corvallis, Oregon 97330
hulsed@oregonstate.edu

Christopher Hoyle

Associate Professor, School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, Oregon 97330
hoylec@oregonstate.edu

Kai Goebel

Tech Area Lead, Discovery and Systems Health, Intelligent Systems Division, NASA Ames Research Center, Moffett Field, California 94035; Adjunct Professor, Luleå Technical University, Division of Operation and Maintenance Engineering Luleå, Sweden
kai.goebel@nasa.gov

Irem Tumer

Professor, School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University Corvallis, Oregon 97330
irem.tumer@oregonstate.edu

1Corresponding author.

ASME doi:10.1115/1.4041571 History: Received June 28, 2018; Revised September 10, 2018

Abstract

Complex engineered systems can carry risk of high failure consequences, and it is desirable for complex engineered systems to be resilient such that they can avoid or quickly recover from faults. Ideally, this should be done at the early design stage where designers are most able to explore a large space of concepts. Previous work has shown that functional models can be used to predict fault propagation behavior and motivate design work. However little has been done to formally optimize or compare designs based on these predictions, partially because the effects of these models have not been quantified into an objective function. This work closes this gap by introducing the resilience-informed scenario cost sum (RISCS), a scoring function which integrates with a fault scenario-based simulation, to enable the optimization and evaluation of functional model resilience. The scoring function accomplishes this by quantifying the expected cost of a design's fault response using probability information, and combining this cost with design and operational costs such that it may be parameterized in terms of designer-specified resilient features. The scoring function is applied to a monopropellant system design-to the optimization of resilient features and the evaluation of possible design variants. Using RISCS as an objective for optimization, the algorithm generates the design solution which provides the optimal trade-off between design cost and risk. For concept selection, RISCS may be used to judge whether resilient concepts justify their design costs and to make direct comparisons between different model structures.

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