Causal Graphical Models for Systems-Level Engineering Assessment
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 2
Abstract
Systems-level analysis of an engineered structure demands robust scientific and statistical protocols to assess model-driven conclusions that are often nontraditional and causal in their content. The formal mathematical, statistical, and philosophical foundations of causal inference on which such protocols are based are, nevertheless, not widely understood. The aims of this article are to (1) communicate the essentials of graph-based causal inference to the civil engineering community, (2) demonstrate how rigorous causal conclusions—and formal quantification of uncertainty regarding those conclusions—may be obtained in a typical engineered system application, and (3) discuss the value of this approach in the context of engineered system assessment. The concepts are illustrated via a river-weir ecosystem case study as an example of decision making for engineered systems in the built environment. In this setting, it is demonstrated how rigorous predictions can be made about the outcome of decisions that take a lack of prior knowledge about the system into account. The findings highlight to end users the value in applying this approach in providing quantitative probabilistic outputs that counter decision uncertainty at system level.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgements.
Acknowledgments
The authors are grateful to Charles Stevenson for access to the weir at Clerkington, as well as Anna Griffin and colleagues from the Scottish Environmental Protection Agency and Matthew O’Hare from the Centre for Ecology and Hydrology, for useful discussions related to the investigation. Katie Whitbread is thanked for assistance with the field GPS survey. The authors wish to thank Professor Jim Smith for detailed feedback on an earlier draft of the article. Data from the UK National River Flow Archive have been used with permission.
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© 2021 American Society of Civil Engineers.
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Received: Feb 26, 2020
Accepted: Nov 2, 2020
Published online: Feb 23, 2021
Published in print: Jun 1, 2021
Discussion open until: Jul 23, 2021
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