contributor author | Arlitt, Ryan M. | |
contributor author | Van Bossuyt, Douglas L. | |
date accessioned | 2019-09-18T09:04:29Z | |
date available | 2019-09-18T09:04:29Z | |
date copyright | 3/18/2019 12:00:00 AM | |
date issued | 2019 | |
identifier issn | 1530-9827 | |
identifier other | jcise_019_03_031001.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4258549 | |
description abstract | A challenge systems engineers and designers face when applying system failure risk assessment methods such as probabilistic risk assessment (PRA) during conceptual design is their reliance on historical data and behavioral models. This paper presents a framework for exploring a space of functional models using graph rewriting rules and a qualitative failure simulation framework that presents information in an intuitive manner for human-in-the-loop decision-making and human-guided design. An example is presented wherein a functional model of an electrical power system testbed is iteratively perturbed to generate alternatives. The alternative functional models suggest different approaches to mitigating an emergent system failure vulnerability in the electrical power system's heat extraction capability. A preferred functional model configuration that has a desirable failure flow distribution can then be identified. The method presented here helps systems designers to better understand where failures propagate through systems and guides modification of systems functional models to adjust the way in which systems fail to have more desirable characteristics. | |
publisher | American Society of Mechanical Engineers (ASME) | |
title | A Generative Human-in-the-Loop Approach for Conceptual Design Exploration Using Flow Failure Frequency in Functional Models1 | |
type | Journal Paper | |
journal volume | 19 | |
journal issue | 3 | |
journal title | Journal of Computing and Information Science in Engineering | |
identifier doi | 10.1115/1.4042913 | |
journal fristpage | 31001 | |
journal lastpage | 031001-10 | |
tree | Journal of Computing and Information Science in Engineering:;2019:;volume( 019 ):;issue: 003 | |
contenttype | Fulltext | |