Search
Filters
Close

51318-11412-Risk Based Inspection Utilizing Monte Carlo Simulation

This paper expands on this work by first reviewing the basis for utilizing Monte Carlo simulation to predict future corrosion in fixed equipment.

Product Number: 51318-11412-SG
Author: Chris Hurd / Joseph Nunez / Frank Sapienza
Publication Date: 2018
$0.00
$20.00
$20.00

Industry research over the last decade has demonstrated the potential for numerical simulation, such as Monte Carlo, to project future corrosion of fixed equipment in refineries and chemical plants. This research has shown the potential for numerical simulation to provide metallurgists and inspection engineers advanced tools in managing fixed equipment in refineries and chemical plants. This paper expands on this work by first reviewing the basis for utilizing Monte Carlo simulation to predict future corrosion in fixed equipment. This paper then explores implementing Monte Carlo simulation based on the quality of inspection data by proposing methods for high-quality, statistically-based inspection data as well as historic, non-statistically-based data. This paper proposes how to incorporate the simulation results into a risk based inspection plan aligned with the philosophy of industry risk based inspection practices.

Key words: Monte Carlo, simulation, RBI, POF

Industry research over the last decade has demonstrated the potential for numerical simulation, such as Monte Carlo, to project future corrosion of fixed equipment in refineries and chemical plants. This research has shown the potential for numerical simulation to provide metallurgists and inspection engineers advanced tools in managing fixed equipment in refineries and chemical plants. This paper expands on this work by first reviewing the basis for utilizing Monte Carlo simulation to predict future corrosion in fixed equipment. This paper then explores implementing Monte Carlo simulation based on the quality of inspection data by proposing methods for high-quality, statistically-based inspection data as well as historic, non-statistically-based data. This paper proposes how to incorporate the simulation results into a risk based inspection plan aligned with the philosophy of industry risk based inspection practices.

Key words: Monte Carlo, simulation, RBI, POF

Product tags
Also Purchased
Picture for 51318-11398- Modeling of Microbiologically Influenced Corrosion (MIC) in the Oil and Gas Industry - Past, Present and Future
Available for download

51318-11398- Modeling of Microbiologically Influenced Corrosion (MIC) in the Oil and Gas Industry - Past, Present and Future

Product Number: 51318-11398-SG
Author: John Wolodko / Tesfaalem Haile / Faisal Khan / Christopher Taylor / Richard Eckert / Seyed Javad Hashemi / Andrea Marciales Ramirez / Torben Lund Skovhus
Publication Date: 2018
$20.00
Picture for 99009 CORROSION RISK ASSESSMENT AND RISK
Available for download

99009 CORROSION RISK ASSESSMENT AND RISK BASED INSPECTION FOR SWEET OIL AND GAS CORROSION - PRACTICAL EXPERIENCE

Product Number: 51300-99009-SG
ISBN: 99009 1999 CP
Author: M. J. Pursell, C. Selman and M. F. Nielsen
$20.00