Traffic-based methodology to develop peak Heat Release Rate probability distributions for sizing road tunnels ventilation systems when using a probabilistic approach
Year: 2025
Type: article
Abstract: Road tunnels are a crucial part of today’s transport infrastructures worldwide. Among the installed systems, the tunnel ventilation is key, as in the case of fire, it establishes and keeps appropriate conditions for self-evacuation and emergency services operations. Recent works propose using a probabilistic approach to assess road tunnels ventilation systems’ capacity for fire scenarios. Under this approach, key design variables are defined based on probability distributions. From these distributions, the analysis uses the different possible values of the variables, including lower and upper limits as well as mean and characteristic values. The results obtained with this proposed probabilistic approach allow not only designers, but also tunnel operators and administrations, to quantify the reliability of the capacity of the ventilation system, assess its probability of failure, and define safety levels. This paper illustrates a methodology to define the design fire as a probability distribution for sizing road tunnels ventilation systems when applying the above-mentioned probabilistic approach. The methodology uses traffic information (crucial in road tunnels) and correlates it to peak Heat Release Rate (HRR) values from published reports by PIARC to obtain the design fire variable in terms of peak HRR probability distributions. The methodology is applied to two case study tunnels with different characteristics. The obtained results for the two tunnels are then compared and analyzed to peak HRR values normally recommended and used when sizing road tunnels ventilation systems to understand the uncertainty and sensitivity of the results.
Source: Mechanical Engineering Advances
DOI: 10.59400/mea2145
Authors: Sonia Fernandez, Charles Fleischmann, Daniel Nilsson, Alberto Fraile
Institutions: University of Canterbury, Universidad Politécnica de Madrid
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409054470