Studies on buoyancy-driven back-layering flow in tunnel fires

Hu, L. H.; Huo, R.; Chow, Wan Ki

doi:10.1016/j.expthermflusci.2008.03.005

Cited by 264 publications

(81 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These full-scale tests include Memorial tunnel fire tests [5,19], Runehamar tunnel fire tests [20][21][22][23], Yuanjiang tunnel fire tests [24] and EUREKA program [9].…”

Section: Critical Velocitymentioning

confidence: 99%

Study of critical velocity and backlayering length in longitudinally ventilated tunnel fires

Lei

Ingason³

2010

Fire Safety Journal

419

240

View full text Add to dashboard Cite

“…These full-scale tests include Memorial tunnel fire tests [5,19], Runehamar tunnel fire tests [20][21][22][23], Yuanjiang tunnel fire tests [24] and EUREKA program [9].…”

Section: Critical Velocitymentioning

confidence: 99%

Study of critical velocity and backlayering length in longitudinally ventilated tunnel fires

Lei

Ingason³

2010

Fire Safety Journal

419

240

View full text Add to dashboard Cite

“…However, K2 increases with the increase of fire power. According to Hu's free smoke spreading decline formula (Hu and Chow 2008) …”

Section: Free-spreading Smoke Temperature Distributionmentioning

confidence: 99%

Maximum Smoke Temperature in Non-Smoke Model Evacuation Region for Semi-Transverse Tunnel Fire

Lou

Qiu

Long

2017

JAFM

View full text Add to dashboard Cite

Smoke temperature distribution in non-smoke evacuation under different mechanical smoke exhaust rates of semi-transverse tunnel fire were studied by FDS numerical simulation in this paper. The effect of fire heat release rate (10MW 20MW and 30MW) and exhaust rate (from 0 to 160m 3 /s) on the maximum smoke temperature in non-smoke evacuation region was discussed. Results show that the maximum smoke temperature in non-smoke evacuation region decreased with smoke exhaust rate. Plug-holing was observed below the smoke vent when smoke exhaust rate increased to a certain value. Smoke spreading distance can be divided into three stages according to changes of smoke exhaust rate. The maximum smoke temperature model concluded that the peak temperature rise at tunnel vault is proportional to 0.75 power of dimensionless fire power. The maximum temperature in non-smoke evacuation region decays exponentially with the increase of smoke exhaust rate. However smoke vent interval influences the dimensionless maximum temperature in nonsmoke evacuation region slightly. Smoke vent interval influences the dimensionless maximum temperature in non-smoke evacuation region slightly.

show abstract

“…Literature concerning underground environments CFD FEM modelling is not much extended. Many studies are design-oriented, evaluating the effects of specific technological solutions 17 or focused on modelling dynamics occurring in case of fire 18 . Other studies are more oriented on discussing a methodology for an effective CFD modelling of subway stations.…”

Section: Boundary and Specific Conditions Through Fem Modelsmentioning

confidence: 99%

Environmental Modeling for the Optimal Energy Control of Subway Stations

Giretti¹,

Lemma²,

Vaccarini³

et al. 2012

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

View full text Add to dashboard Cite

Purpose Underground transportation systems are big energy consumers and have a significant impact on energy consumption at regional level. One third of the networks' energy is required for operating the subsystems of metro stations and surroundings, such as ventilation, vertical transportation and lightning. Although a relatively small percentage of energy can be saved with optimal management of these subsystems, in absolute terms this means large energy savings are obtained. Furthermore, optimal management is a big opportunity for energy efficiency since it involves much smaller investments than those usually applied to transportation by providing new ways for sustainable energy saving solutions. In this perspective, the EU-funded R&D project SEAM4US (Sustainable Energy Management for Underground Stations) is aimed at defining a technological and methodological framework for optimized energy management in public underground spaces, which will be applied to the dynamic control of the energy consumption in Barcelona Passeig de Gracia subway station. Method The development of a new class of predictive control logics, behaving consistently in changing environments is at the core of the optimal energy management approach and it is one of the main objectives of this research. This class of control systems is based on advanced environmental models, directly coupled with an environment monitoring sensor network, that is capable of interpreting the sensed data (both indoor and environmental) and of forecasting future states. In order to achieve the necessary level of robustness these models must be able to learn from previous states so they can adapt to the varying environment. The development of this class of environmental models for large underground environments like subway stations involves the elaboration and the integration of different simulation models concerning natural and forced ventilation, passenger movement, lighting systems, and their integration in a unique formals statistical framework, which is able to manage the uncertainty affecting the sensed data and to learn from the data flow. Results & Discussion We will outline the methodological approach to the development of the Passeig de Gracia environmental models for the optimal control of its energy consumption. The adopted hybrid modeling solutions, integrating different classes of simulation means in a unique Bayesian framework4, and a preliminary architecture of the overall control system will be presented.

show abstract

Studies on buoyancy-driven back-layering flow in tunnel fires

Cited by 264 publications

References 31 publications

Study of critical velocity and backlayering length in longitudinally ventilated tunnel fires

Study of critical velocity and backlayering length in longitudinally ventilated tunnel fires

Maximum Smoke Temperature in Non-Smoke Model Evacuation Region for Semi-Transverse Tunnel Fire

Environmental Modeling for the Optimal Energy Control of Subway Stations

Contact Info

Product

Resources

About