Development of a probabilistic mechanistic model for reliability assessment of gas cylinders in compressed natural gas vehicles

• Published in: Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability Vol. 223; no. 4; pp. 289 - 299
• Main Authors: Chamberlain, S, Chookah, M, Modarres, M
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.12.2009; SAGE PUBLICATIONS, INC
• Subjects: Accident data; Component reliability; Compressed gas; Compressed natural gas; Corrosion; Corrosion fatigue; Corrosion rate; Crack propagation; Diesel engines; Distribution functions; Failure mechanisms; Fatigue cracking; Fatigue failure; Fracture mechanics; Fuel systems; Gas cylinders; Gasoline engines; Inspection; Material properties; Mathematical models; Modelling; Natural gas; Natural gas vehicles; Physics; Pressure; Probability distribution functions; Reliability; Reliability analysis; Statistical analysis; Stress corrosion cracking; Support systems; reliability assessment; compressed natural gas (CNG); probabilistic physics-of-failure
• ISSN: 1748-006X; 1748-0078
• DOI: 10.1243/1748006XJRR231

Until now, there has been no probabilistic modelling or comprehensive risk analysis of the reliability of compressed natural gas (CNG) fuelled vehicles and support systems. This is due to sparse failure and accident data, which, in turn, is largely due to the small number of such vehicles in operation and the relatively new technology compared with diesel and gasoline engines. Direct estimation of the failure frequencies of system components requires a large quantity of data. However, estimation of reliability using probability physical models (i.e. the physics-of-failure approach) is another option that requires less data. This approach is used in this research and discussed in this paper. CNG fuel system components are subject to degradation caused by stress corrosion cracking and corrosion fatigue. A quick risk analysis shows that the storage cylinder is the most risk-significant component in CNG vehicles. The cylinder is a vulnerable component in the system, due to the presence of corrosive constituents in the stored CNG fuel and mechanical fatigue due to frequent fillings. Physics-of-failure modelling is used to estimate the frequency of leakages and ruptures of the CNG cylinders. The analytical model proposed in this paper is based on the probabilistic fracture mechanics of the associated corrosion-enhanced fatigue-failure mechanisms. The proposed model estimates the probability distribution function of the frequency of cylinder failure leading to particular CNG gas-release scenarios, while incorporating the impact of the manufacturing process, material properties, and inspection methodology. The estimated frequency of cylinder failure based on the physics of failure is used to update the overall risk associated with CNG bus systems, which has been the subject of research by the authors in the past.