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Enhanced reasoning with multilevel flow modeling based on time-to-detect and time-to-effect concepts

Authors :
Seung Geun Kim
Poong Hyun Seong
Source :
Nuclear Engineering and Technology, Vol 50, Iss 4, Pp 553-561 (2018)
Publication Year :
2018
Publisher :
Elsevier, 2018.

Abstract

To easily understand and systematically express the behaviors of the industrial systems, various system modeling techniques have been developed. Particularly, the importance of system modeling has been greatly emphasized in recent years since modern industrial systems have become larger and more complex.Multilevel flow modeling (MFM) is one of the qualitative modeling techniques, applied for the representation and reasoning of target system characteristics and phenomena. MFM can be applied to industrial systems without additional domain-specific assumptions or detailed knowledge, and qualitative reasoning regarding event causes and consequences can be conducted with high speed and fidelity.However, current MFM techniques have a limitation, i.e., the dynamic features of a target system are not considered because time-related concepts are not involved. The applicability of MFM has been restricted since time-related information is essential for the modeling of dynamic systems. Specifically, the results from the reasoning processes include relatively less information because they did not utilize time-related data.In this article, the concepts of time-to-detect and time-to-effect were adopted from the system failure model to incorporate time-related issues into MFM, and a methodology for enhancing MFM-based reasoning with time-series data was suggested. Keywords: Multilevel Flow Modeling, Time-series Data, Time-to-Detect, Time-to-Effect

Details

Language :
English
ISSN :
17385733
Volume :
50
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Nuclear Engineering and Technology
Publication Type :
Academic Journal
Accession number :
edsdoj.36931a8508340a1a6cea8cdfe3399cf
Document Type :
article
Full Text :
https://doi.org/10.1016/j.net.2018.03.008