Oil and Gas Processing Equipment (e-bog) af Unnikrishnan, G.
Unnikrishnan, G. (forfatter)

Oil and Gas Processing Equipment e-bog

403,64 DKK (inkl. moms 504,55 DKK)
Oil and gas industries apply several techniques for assessing and mitigating the risks that are inherent in its operations. In this context, the application of Bayesian Networks (BNs) to risk assessment offers a different probabilistic version of causal reasoning. Introducing probabilistic nature of hazards, conditional probability and Bayesian thinking, it discusses how cause and effect of pro...
E-bog 403,64 DKK
Forfattere Unnikrishnan, G. (forfatter)
Forlag CRC Press
Udgivet 14 september 2020
Længde 138 sider
Genrer KCHS
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781000174212
Oil and gas industries apply several techniques for assessing and mitigating the risks that are inherent in its operations. In this context, the application of Bayesian Networks (BNs) to risk assessment offers a different probabilistic version of causal reasoning. Introducing probabilistic nature of hazards, conditional probability and Bayesian thinking, it discusses how cause and effect of process hazards can be modelled using BNs and development of large BNs from basic building blocks. Focus is on development of BNs for typical equipment in industry including accident case studies and its usage along with other conventional risk assessment methods. Aimed at professionals in oil and gas industry, safety engineering, risk assessment, this bookBrings together basics of Bayesian theory, Bayesian Networks and applications of the same to process safety hazards and risk assessment in the oil and gas industrya a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a Presents sequence of steps for setting up the model, populating the model with data and simulating the model for practical cases in a systematic mannera a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a Includes a comprehensive list on sources of failure data and tips on modelling and simulation of large and complex networksa a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a Presents modelling and simulation of loss of containment of actual equipment in oil and gas industry such as Separator, Storage tanks, Pipeline, Compressor and risk assessmentsa a a a a a a a a Discusses case studies to demonstrate the practicability of use of Bayesian Network in routine risk assessments