Reconstructed Tunnel-Fire Service-Retention Data and Code for Input-Domain Resilience Morphology and Threshold-Functional Assessment
Description
This dataset contains 666 numerical records reconstructed from Figs. 15–19 of Zhu et al. (2025), derived result tables, and Python scripts supporting an input-domain resilience-morphology and threshold-functional analysis of service retention in urban road tunnel fire scenarios. The files support grouped response-function fitting, calculation of service-retention thresholds, cross-function comparison, digitization sensitivity analysis, held-out input tests, and reproduction of the main evidence figures. The package contains no original simulation output or source figure images from Zhu et al. The reconstructed values are intended for secondary analysis and within-case comparison. Engineering calibration requires original simulation tables or new data with suitable input-domain coverage. Source publication: Zhu, R., Zhang, D., Huang, Z., Guo, X., Gan, B., and Zhou, W. (2025). Traffic-based resilience assessment on urban road tunnel affected by fire accident. Tunnelling and Underground Space Technology, 161, 106543. https://doi.org/10.1016/j.tust.2025.106543
Files
Steps to reproduce
Install the packages listed in requirements.txt. From the extracted package root, run the scripts in the order given in README.md. The fixed perturbation seed is 20260620. The perturbation analysis performs 9,600 nonlinear group fits and takes longer than the other steps. Generated figures are written to the package-local figures directory. The submitted artwork was manually refined, so reproduced typography and spacing may differ while the plotted data remain unchanged.
Institutions
- Tongji UniversityShanghai, Shanghai