Zobrazeno 1 - 10
of 1 863
pro vyhledávání: '"Tunnel fire"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Ceiling beams at the top of tunnels are more common in actual projects. Under the influence of thermal buoyancy, the ceiling structure significantly affects the diffusion characteristics of fire smoke within the tunnel. This study performed
Externí odkaz:
https://doaj.org/article/ccea53c84c884738ae3b04517a5b1aee
Publikováno v:
Case Studies in Thermal Engineering, Vol 63, Iss , Pp 105268- (2024)
Accurate predictions of HRR will improve preparedness and response strategies, enhance safety, and minimise damage in tunnel fires. In this study, a deep learning prediction model for HRR under multimodal data fusion is proposed. A multimodal dataset
Externí odkaz:
https://doaj.org/article/b85177b54608414f959bade15fe039b5
Publikováno v:
Case Studies in Thermal Engineering, Vol 62, Iss , Pp 105186- (2024)
An improved understanding of tunnel fire dynamics is crucial for fire and life safety. This work highlights the significance of Computational Fluid Dynamics (CFD) techniques in addressing the interaction between tunnel fires and rainfall. The discret
Externí odkaz:
https://doaj.org/article/72436b81308341e4a127563dce6ed19c
Publikováno v:
Case Studies in Thermal Engineering, Vol 62, Iss , Pp 105170- (2024)
In this study, a Genetic Algorithm-Backpropagation Neural Network (GA-BPNN) model was developed to predict critical exhaust volumetric flow rate in tunnel fires with two-point extraction ventilation system. Seven influencing factors served as inputs
Externí odkaz:
https://doaj.org/article/879ee3c85fe54b8bab2b01f79c7b09d9
Publikováno v:
Case Studies in Thermal Engineering, Vol 62, Iss , Pp 105205- (2024)
Inclined tunnels are commonly seen in modern society. Compared with horizontal tunnel fires, smoke movement in inclined tunnel fires exhibits noticeable asymmetry. In this study, a series of numerical simulations are conducted to investigate the asym
Externí odkaz:
https://doaj.org/article/46a7c3d6439e443aa560a78c29a944c7
Publikováno v:
Case Studies in Thermal Engineering, Vol 61, Iss , Pp 105132- (2024)
Previous research has commonly assumed that tunnel fire blockage occurs at the central longitudinal axis of tunnels. However, fires may arise at different points within tunnels, each with various distances from the tunnel sidewall. The study aimed to
Externí odkaz:
https://doaj.org/article/ee854c81dcea48de975d91088c28a99a
Publikováno v:
Case Studies in Thermal Engineering, Vol 60, Iss , Pp 104795- (2024)
Asphalt could suffer hydrothermal ageing in underwater tunnels, which varies its combustion characteristics significantly. The hydrothermally aged asphalt (HA) was comparatively studied with base asphalt (BA) and thermal-oxidatively aged asphalt (TA)
Externí odkaz:
https://doaj.org/article/c4f66f2f569947edbdc28a19e47ffc12
Publikováno v:
Case Studies in Thermal Engineering, Vol 60, Iss , Pp 104761- (2024)
The smoke temperature profile beneath the ceiling of tunnel is one of the most important parameters to evaluate the tunnel fire risk and guide the early fire detection. This paper investigates experimentally the temperature profile induced by the tun
Externí odkaz:
https://doaj.org/article/248919ceeb1b46bd8601a59c1969f1ab
Publikováno v:
Case Studies in Thermal Engineering, Vol 60, Iss , Pp 104768- (2024)
The high temperatures and non-uniform temperature fields caused by fires can lead to the rapid failure of linings, severely affecting tunnel safety. To obtain the temperature distribution of the lining under different fire conditions, simulation rese
Externí odkaz:
https://doaj.org/article/9a2499290c424ce08c36ecb198acbb0a
Publikováno v:
Case Studies in Thermal Engineering, Vol 60, Iss , Pp 104723- (2024)
This research focuses on the specific uniclinal V-shaped tunnel during a fire, studying the air supplement triggered by the thermal stack effect and further examining the control mechanism of upstream smoke. It revealed how the air supplement velocit
Externí odkaz:
https://doaj.org/article/ee8c1481923e4ef4a73b74d87e6e93d5