THE USE OF SENSITIVITY ANALYSES FOR OPTIMUM DATA GATHERING IN RISK AND THREATS ASSESSMENTS

被引:0
|
作者
Ayello, Francois [1 ]
Chen, Hao [1 ]
Sridhar, Narasi [1 ]
Ruiz, Lydia [2 ]
Sera, Travis [2 ]
Shironishi, Mad [2 ]
机构
[1] DNV GL, Dublin, OH 43017 USA
[2] SoCalGas, Los Angeles, CA USA
关键词
Bayesian networks; data gathering; data uncertainty; cost-benefit analysis; risk assessment; threat identification; OIL; FAILURE;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Pipeline engineers routinely perform risk assessments using a linear approach that begins with data collection, progresses through threat identification, and concludes with risk assessment. This linear risk assessment process leads to some inefficiencies. For example, since all data is gathered in the first step, inconsequential data might be collected during the data gathering process that diverts resources from other pipelines. This paper presents a different approach, where data is gathered iteratively based on its risk reduction value derived from a sensitivity analysis and data collection cost. Each time data is gathered; future risk predictions become more certain. This process is stopped when the cost of data gathering activities outweighs the benefit to risk predictions.
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页数:13
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