Document Detail


Modeling Risk-Related Knowledge in Tunneling Projects.
MedLine Citation:
PMID:  23865765     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Knowledge on failure events and their associated factors, gained from past construction projects, is regarded as potentially extremely useful in risk management. However, a number of circumstances are constraining its wider use. Such knowledge is usually scarce, seldom documented, and even unavailable when it is required. Further, there exists a lack of proven methods to integrate and analyze it in a cost-effective way. This article addresses possible options to overcome these difficulties. Focusing on limited but critical potential failure events, the article demonstrates how knowledge on a number of important potential failure events in tunnel works can be integrated. The problem of unavailable or incomplete information was addressed by gathering judgments from a group of experts. The elicited expert knowledge consisted of failure scenarios and associated probabilistic information. This information was integrated using Bayesian belief-networks-based models that were first customized in order to deal with the expected divergence in judgments caused by epistemic uncertainty of risks. The work described in the article shows that the developed models that integrate risk-related knowledge provide guidance as to the use of specific remedial measures.
Authors:
Ibsen Chivatá Cárdenas; Saad S H Al-Jibouri; Johannes I M Halman; Frits A van Tol
Related Documents :
24223925 - A multilocus phylogeny of the world sycoecinae fig wasps (chalcidoidea: pteromalidae).
24011945 - Applying additive logistic regression to data derived from sensors monitoring behaviora...
24524735 - Qsar modeling of imbalanced high-throughput screening data in pubchem.
23985505 - A generic hydrological model for a green roof drainage layer.
19925645 - An experimental loop design for the detection of constitutional chromosomal aberrations...
3557115 - Use of the multinomial dirichlet model for analysis of subdivided genetic populations.
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-7-19
Journal Detail:
Title:  Risk analysis : an official publication of the Society for Risk Analysis     Volume:  -     ISSN:  1539-6924     ISO Abbreviation:  Risk Anal.     Publication Date:  2013 Jul 
Date Detail:
Created Date:  2013-7-19     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8109978     Medline TA:  Risk Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2013 Society for Risk Analysis.
Affiliation:
Department of Construction Management and Engineering, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Tonic GABA inhibition in hippocampal dentate granule cells: its regulation and function in temporal ...
Next Document:  Design and application of a novel PNA probe for the detection at single cell level of JAK2V617F muta...