Bayesian updating in a fault tree model for shipwreck risk assessment

2017 ◽  
Vol 590-591 ◽  
pp. 80-91 ◽  
Author(s):  
H. Landquist ◽  
L. Rosén ◽  
A. Lindhe ◽  
T. Norberg ◽  
I.-M. Hassellöv
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Bayesian Updating ◽  
Tree Model

Fault-Tree Model for Risk Assessment of Bridge Failure: Case Study for Segmental Box Girder Bridges

2013 ◽  
Vol 19 (3) ◽  
pp. 326-334 ◽  
Author(s):  
Caitlyn Davis-McDaniel ◽  
Mashrur Chowdhury ◽  
Weichiang Pang ◽  
Kakan Dey
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Tree Model ◽  
Box Girder Bridges ◽  
Box Girder ◽  
Girder Bridges ◽  
Bridge Failure

A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models

2020 ◽  
Vol 234 (6) ◽  
pp. 748-763
Author(s):  
Tasneem Bani-Mustafa ◽  
Nicola Pedroni ◽  
Enrico Zio ◽  
Dominique Vasseur ◽  
Francois Beaudouin
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Nuclear Power ◽  
Fault Tree ◽  
Heat Removal ◽  
Quantitative Measure ◽  
Critical Systems ◽  
Tree Model ◽  
Hierarchical Tree ◽  
Risk Assessment Models

Risk assessment provides information to support decision-making. Then, the confidence that can be put in its outcomes is fundamental, and this depends on the accuracy, representativeness and completeness of the models used in the risk assessment. A quantitative measure is needed to assess the credibility and trustworthiness of the outcomes obtained from such models, for decision-making purposes. This article proposes a four-level, top-down, hierarchical tree to identify the main attributes and criteria that affect the level of trustworthiness of models used in risk assessment. The level of trustworthiness (Level 1) is broken down into two attributes (Level 2), three sub-attributes and one “leaf” attribute (Level 3), and seven basic “leaf” sub-attributes (Level 4). Based on this hierarchical decomposition, a bottom-up, quantitative approach is employed for the assessment of model trustworthiness, using tangible information and data available for the basic “leaf” sub-attributes (Level 4). Analytical hierarchical process is adopted for evaluating and aggregating the sub-attributes, and Dempster–Shafer theory is adopted to consider the uncertainty and the inconsistency in the experts’ judgments. The approach is applied to a case study concerning the modeling of the residual heat removal system of a nuclear power plant, to compute its failure probability. The relative trustworthiness of two mathematical models of different complexity is evaluated: a fault tree and a multi-states physics-based model. The trustworthiness of the multi-states physics-based model is found to outweigh that of the fault tree model, which can be explained by the fact that multi-states physics-based model takes into account the components failure dependency relations and degradation effects. The feasibility and reasonableness of the approach are, thus, demonstrated, paving the way for its potential applicability to inform decision-making on safety-critical systems.

Research on Risk Assessment Model of Open Press Blunt Hand Accident

2012 ◽  
Vol 220-223 ◽  
pp. 224-228
Author(s):  
Wen Ying Chen
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Assessment Model ◽  
Accident Risk ◽  
Event Tree ◽  
Tree Model ◽  
Common Cause ◽  
Common Cause Failure ◽  
Accident Probability ◽  
Set Up

Basic principle and inference algorithm of Bayesian network (BN) were emphasized. As to the Fault Tree with basic events of common cause failure, accident probability cannot be computed correctly. An open press blunt hand accident risk assessment BN model was set up, in addition, the BN nodes of common cause failure were illustrated and the accident probability of occurrence was obtained. The discussions about computed results indicate that regarding to system with unit events of common cause failure or interdependent events, result of accident probability computed from a BN model is higher than that computed from the Fault Tree/Event Tree model.

Assessing the Risk of Noncompliance in Wastewater Treatment

1992 ◽  
Vol 26 (5-6) ◽  
pp. 1411-1420 ◽  
Author(s):  
S. H. Choudhury ◽  
S. L. Yu ◽  
Y. Y. Haimes
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Fault Tree ◽  
Treatment Plant ◽  
Risk Identification ◽  
System Component ◽  
System Failure ◽  
Tree Model ◽  
Risk Quantification ◽  
Failure Probabilities

This paper presents an integrated methodology that allows determining the probability of noncompliance for a given wastewater treatment plant. The methodology applies fault-tree analysis, which uses failure probabilities of individual components, to predict the overall system failure probability. The methodology can be divided into two parts : risk identification and risk quantification. In risk identification, the key components in the system are determined by analyzing the contribution of individual component failures toward system failure (i.e., noncompliance). In risk quantification, a fault-tree model is constructed for the particular system, component failure probabilities are estimated, and the fault-tree model is evaluated to determine the probability of occurrence of the top event (i.e., noncompliance). A list can be developed that ranks critical events on the basis of their contributions to the probability of noncompliance. Such a ranking should assist managers to determine which components require most attention for a better performance of the entire system. A wastewater treatment plant for treating metal-bearing rinse water from an electroplating industry is used as an example to demonstrate the application of this methodology.

scholarly journals Risk assessment of ice dams for water diversion projects based on fuzzy fault trees

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Mengkai Liu ◽  
Xiaoxia Dong ◽  
Hui Guo
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Northern China ◽  
Indicator System ◽  
Water Diversion ◽  
Risk Indicators ◽  
Scoring Method ◽  
Study Results ◽  
Dam Risk

AbstractIce dams are among the important risks affecting the operational safety and water conveyance efficiency of water diversion projects in northern China. However, no evaluation indicator system for ice dam risk assessment of water diversion projects has been proposed. Therefore, in this paper, based on the formation mechanism of ice dams, the risk assessment indicator system and the possibility calculation model of ice dams were both proposed for water diversion projects based on the fuzzy fault tree analysis method. The ice dam risk fault tree constructed in this study mainly includes three aspects: ice production, ice transport, and ice submergence conditions. Eighteen basic risk indicators were identified, and 72 minimum cut sets were obtained by using the mountain climb method. Eight risk indicators were determined as the key risk indicators for ice dams, including meteorological conditions, narrowed cross section, sluice incident, erroneous scheduling judgment, ice cover influence, flat bed slope, control structures, and ice flow resistance of piers. Then, the canal from the Fenzhuanghe sluice to the Beijumahe sluice of the Middle Route of the South-to-North Water Diversion Project was taken as the research object. Combined with the expert scoring method, the ice dam risk probability of the canal was determined to be 0.2029 × 10−2, which was defined as a level III risk, which is an occasionally occurring risk. The study results can support ice dam risk prevention and canal system operation in winter for water diversion projects.

Chemical plant risk assessment using HAZOP and fault tree methods

1984 ◽  
Vol 3 (3) ◽  
pp. 179-184 ◽  
Author(s):  
Lisa M. Bendixen ◽  
J. Kevin O'Neill
Keyword(s):  
Risk Assessment ◽  
Fault Tree ◽  
Chemical Plant ◽  
Tree Methods
Sign in / Sign up

Export Citation Format

Share Document