Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Multilevel Flow Modelling has been used for modelling complex system such as nuclear power plants. The causal reasoning capability of the MFM models is explained in various literatures by the authors as well as other researchers. MFM is also used to represent control functions in relation with system objectives. This paper clarify the fulfilment of MFM objectives and extend the MFM causal reasoning rules to the control functions and use reasoning rules to generate explanations for understanding control actions. A case study based on a previous developed PWR model is used to illustrate the new reasoning rules. This work contribute to support human operators to understand system automation under abnormal situations
Original languageEnglish
Title of host publication2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants
Number of pages8
Publication date2017
Publication statusPublished - 2017
Event2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants - Gyeongju-si, Korea, Republic of
Duration: 26 Nov 201730 Nov 2017
http://www.isofic.org/

Conference

Conference2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants
CountryKorea, Republic of
CityGyeongju-si
Period26/11/201730/11/2017
Internet address

Keywords

  • Multilevel flow modelling
  • Causal reasoning
  • Automation awareness

Cite this

Zhang, X., & Lind, M. (2017). Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling. In 2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants
Zhang, Xinxin ; Lind, Morten. / Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling. 2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants. 2017.
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Zhang, X & Lind, M 2017, Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling. in 2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants. 2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants, Gyeongju-si, Korea, Republic of, 26/11/2017.

Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling. / Zhang, Xinxin; Lind, Morten.

2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants. 2017.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

TY - GEN

T1 - Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling

AU - Zhang, Xinxin

AU - Lind, Morten

PY - 2017

Y1 - 2017

N2 - Multilevel Flow Modelling has been used for modelling complex system such as nuclear power plants. The causal reasoning capability of the MFM models is explained in various literatures by the authors as well as other researchers. MFM is also used to represent control functions in relation with system objectives. This paper clarify the fulfilment of MFM objectives and extend the MFM causal reasoning rules to the control functions and use reasoning rules to generate explanations for understanding control actions. A case study based on a previous developed PWR model is used to illustrate the new reasoning rules. This work contribute to support human operators to understand system automation under abnormal situations

AB - Multilevel Flow Modelling has been used for modelling complex system such as nuclear power plants. The causal reasoning capability of the MFM models is explained in various literatures by the authors as well as other researchers. MFM is also used to represent control functions in relation with system objectives. This paper clarify the fulfilment of MFM objectives and extend the MFM causal reasoning rules to the control functions and use reasoning rules to generate explanations for understanding control actions. A case study based on a previous developed PWR model is used to illustrate the new reasoning rules. This work contribute to support human operators to understand system automation under abnormal situations

KW - Multilevel flow modelling

KW - Causal reasoning

KW - Automation awareness

M3 - Article in proceedings

BT - 2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants

ER -

Zhang X, Lind M. Reasoning about Cause-effect through Control Functions in Multilevel Flow Modelling. In 2017 International Symposium on Future Instrumentation and Control for Nuclear Power Plants. 2017