Risk mitigation of pipeline assets through improved corrosion modeling

Infrastructure has to weather the elements and still function. Gas transmission and distribution piping at a utility are no exception. Atmospheric corrosion deteriorates the integrity of the natural gas system, and utilities need to respond with countermeasures in order to mitigate the risk. The ability to predict where atmospheric corrosion will cause leaks will allow for a better allocation of resources in mitigating the risk caused by corrosion. First a corrosion simulation model was developed to predict the number of leaks in each geographic area in PG&E's service area. Past meteorological data, past pollution data, 2014 atmospheric corrosion inspections on 2.27 million meters, leak data, and gas system asset information (meter age, type, etc.) were used. The qualitative observations and a quantitative model were then coupled in a simulation model to predict the number of leaks depending on the years between atmospheric corrosion inspections. Utilizing the output of the corrosion prediction model, an optimization model was developed to determine the atmospheric corrosion inspection frequency that will minimize the risk of leaks to the system. This model will allow PG&E to understand how reallocating inspection resources can reduce risk of leaks. The overall results indicate that data quality plays a very important role in coupling qualitative observations with a quantitative model. From the model developed and analyzed in this thesis, several opportunities for better data collection were identified. By collecting targeted data on localized corrosion and corrosion rates, qualitative inspections can contribute greatly to accurately model corrosion where quantitative models are lacking.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Mullen, Richard A. (Richard Almond)

Advisor dc:contributor.advisor

• Georgia Perakis and Alexander Slocum.

• Sloan School of Management.
• Mechanical Engineering.
• Leaders for Global Operations Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/99027

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/99027