Citation

Caliendo C, Genovese G. Risk Anal. 2020; ePub(ePub): ePub.

Copyright

(Copyright © 2020, Society for Risk Analysis, Publisher John Wiley and Sons)

DOI

10.1111/risa.13653

PMID

33314268

Abstract

A quantitative risk analysis (QRA) concerning dangerous goods vehicles (DGVs), including also vehicles for the transport of liquid hydrogen (LH2 TVs), running through unidirectional motorway tunnels was performed. An event tree was built, and a wide parametric analysis based on different geometric and traffic characteristics of tunnels was carried out. The effects of the annual average daily traffic (AADT) per lane, the tunnel length (L), the percentage both of heavy goods vehicles (HGVs) and DGVs (for a given 7% of LH2 TVs) were investigated. The results in terms of social risk, as expressed by F/N curves and the expected value (EV), show an increased risk level with the presence of the hydrogen transported, and with certain F/N curves that might also lie above the acceptability limit. This means that additional safety measures should be implemented in order to reduce the risk level or that, alternatively, appropriate strategies of traffic control systems should be taken. A statistical modeling for developing a predictive method of the EV is also performed. The outcomes show that the regression coefficients have the signs expected. In particular, the EV increases with the tunnel length (L), the AADT, and the percentage both of HGVs and DGVs. However, the magnitude of estimated coefficients indicates that the expected value EV increases more with the traffic (AADT per lane, HVGs, or DGVs) than the tunnel length. The application of the approximate method might help the Tunnel Management Agencies (TMAs) in making quick decisions, at a preliminary stage, about temporarily allowing, forbidding or limiting the circulation of DGVs and/or LH2 TVs through tunnels; and subsequently investigating in greater depth the potential hazards due to the transport of hydrogen in the worst cases individualized.

Language: en

Keywords

Dangerous goods vehicles; predictive model; quantitative risk analysis; road tunnels; transport of hydrogen