Fire development and optimal emergency stopping strategy for high-altitude railway bridge-tunnel sections under ambient wind

With the rapid expansion of transport infrastructure into complex mountainous terrain, bridge-tunnel connecting sections (BTCSs) have emerged as a common yet distinct configuration characterized by high bridge-to-tunnel ratios. To address the challenge of determining emergency stopping positions for train fires within these semi-open environments subject to high-altitude variable wind fields, this study proposes an adaptive stopping decision-making method that accounts for real-time environmental changes. First, full-scale numerical simulations covering multiple scenarios were conducted to systematically investigate the mechanisms governing smoke propagation and temperature distribution under varying altitudes, natural wind speeds, and stopping positions. Subsequently, a triple evaluation criterion was established, encompassing the prevention of smoke intrusion, assurance of structural thermal safety, and compliance with evacuation environmental requirements. Based on these criteria, a decision-making workflow for train fire emergency stopping was formulated. Results reveal that the critical state of smoke intrusion is governed by the competing mechanisms of inward wind, which drives high-temperature backflow, and stopping distance, which facilitates smoke dilution through spatial expansion. Based on the quantified relationship between these variables, a universal stopping decision model applicable to diverse line configurations was derived. Furthermore, an automatic optimization algorithm integrating train braking kinematics was developed to generate real-time execution schemes. Validation via a typical engineering case confirms the algorithm's capability to pinpoint the optimal stopping position (DK 247 + 967) within 1 s, while accurately calculating precise braking deceleration (0.33–0.35 m/s2) and duration (127.62–135.86 s). This methodology provides a robust scientific basis for generating rapid, quantified stopping instructions that satisfy both personnel-evacuation and structural-safety constraints in complex BTCS environments.