Risk-Informed Decision-Making for Predisaster Risk Mitigation Planning of Interdependent Infrastructure Systems: Case Study of Jamaica

2021 ◽  
Vol 27 (4) ◽  
pp. 04021035
Author(s):  
Xian He ◽  
Eun Jeong Cha
Keyword(s):  
Decision Making ◽  
Risk Mitigation ◽  
Informed Decision ◽  
Informed Decision Making ◽  
Infrastructure Systems ◽  
Mitigation Planning ◽  
Interdependent Infrastructure

scholarly journals Convergent analytics and informed decision-making: A retrospective multimethod case study project in Kenya

2017 ◽  
Vol 6 (2) ◽  
pp. 214-225
Author(s):  
Irene Podolak ◽  
Anteneh Ayanso ◽  
Maureen Connolly ◽  
Madelyn Law ◽  
Jarold Cosby
Keyword(s):  
Decision Making ◽  
Informed Decision ◽  
Informed Decision Making

scholarly journals Organizational impact of evidence-informed decision making training initiatives: a case study comparison of two approaches

2014 ◽  
Vol 9 (1) ◽  
Author(s):  
François Champagne ◽  
Louise Lemieux-Charles ◽  
Marie-France Duranceau ◽  
Gail MacKean ◽  
Trish Reay
Keyword(s):  
Decision Making ◽  
Informed Decision ◽  
Informed Decision Making ◽  
Organizational Impact

System Risk Importance Analysis Using Bayesian Networks

2018 ◽  
Vol 25 (01) ◽  
pp. 1850004 ◽  
Author(s):  
Ali Noroozian ◽  
Reza Baradaran Kazemzadeh ◽  
Seyed Taghi Akhavan Niaki ◽  
Enrico Zio
Keyword(s):  
Decision Making ◽  
Bayesian Networks ◽  
Structural Characteristics ◽  
Informed Decision ◽  
Informed Decision Making ◽  
Risk Modeling ◽  
Modeling And Analysis ◽  
Importance Analysis ◽  
System Risk

Importance measures (IMs) are used for risk-informed decision making in system operations, safety, and maintenance. Traditionally, they are computed within fault tree (FT) analysis. Although FT analysis is a powerful tool to study the reliability and structural characteristics of systems, Bayesian networks (BNs) have shown explicit advantages in modeling and analytical capabilities. In this paper, the traditional definitions of IMs are extended to BNs in order to have more capability in terms of system risk modeling and analysis. Implementation results on a case study illustrate the capability of finding the most important components in a system.

Applying Best Practical Environmental Optioneering (BPEO) to a Complex Clean Up Programme: A Ponds and Silos Case Study

2009 ◽  
Author(s):  
Simon Candy
Keyword(s):  
Decision Making ◽  
Nuclear Waste ◽  
Informed Decision ◽  
Nuclear Industry ◽  
Waste Stream ◽  
Informed Decision Making ◽  
Nuclear Wastes ◽  
Waste Streams ◽  
Selection Of

The use of Best Practical Environmental Optioneering (BPEO) has long been part of informed decision making within the Nuclear Industry. However, BPEO has typically been applied to specific and discrete objectives, for example the selection of a technology to treat a particular nuclear waste stream. While this has sometimes been extended to cover a number of objectives, no one had applied BPEO to a programme of the size and complexity of that associated with Legacy Ponds & Silos at Sellafield. The programme, spanning more than 30 years, includes a range of different objectives covering ongoing management, recovery, conditioning, storage and ultimately disposal of nuclear wastes. This range of activities is applied across a number of facilities containing multiple, significant waste streams. This paper explains how BPEO was applied to the Legacy Ponds & Silos programme and discussed some of the learning resulting from that exercise.

Teaching sustainability-informed decision-making based on high-risk dam failure case study

CIM Journal ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 274-281
Author(s):  
D. Beneteau ◽  
K. Chovan ◽  
P. Hughes ◽  
S. Gauthier
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Informed Decision ◽  
Dam Failure ◽  
Informed Decision Making
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