The Experts below are selected from a list of 5052 Experts worldwide ranked by ideXlab platform
Haukur Ingason - One of the best experts on this subject based on the ideXlab platform.
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Influence of Fire suppression on combustion products in Tunnel Fires
Fire Safety Journal, 2017Co-Authors: Ying Zhen Li, Haukur IngasonAbstract:Abstract A series of model scale Tunnel Fire tests was carried out to investigate effects of the Fire suppression system on production of key combustion products including CO and soot. The key parameters accounted for in the tests include fuel type, ventilation velocity and activation time. The results show that Fire suppression indeed has influence on production of combustion products especially for cellulose fuels. In case that the Fire is not effectively suppressed, e.g. when the water density is too low or activation is too late, the CO concentration and visibility could be worse than in the free-burn test. From the point of view of production of combustion products, only Fire suppression systems with sufficient capability and early activation are recommended to be used in Tunnels.
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A New Methodology of Design Fires for Train Carriages Based on Exponential Curve Method
Fire Technology, 2016Co-Authors: Ying Zhen Li, Haukur IngasonAbstract:Design Fires have great influences on the Fire safety concepts and safety measures, and are the basis for any assessment and calculation in Tunnel Fire safety design. A new methodology of design Fires for individual train carriages is proposed based on the exponential design Fire curve method and state-of-the-art Fire research. The three key parameters required for construction of a design Fire are the maximum heat release rate, time to maximum heat release rate, and energy content. An overview of the full scale train carriage Fire tests is given and the results show that the maximum heat release rate is in a range of 7 MW to 77 MW and the time to reach the maximum heat release rate varies from 7 min to 118 min. The method could be employed to one single train carriage or several carriages, and alternatively one carriage could be divided into several individual sections. To illustrate the use of the methodology, several engineering applications are presented, including design Fires for a metro train carriage with a maximum heat release rate of 77 MW, a double-deck railway train carriage with a maximum heat release rate of 60 MW and a tram carriage with a maximum heat release rate of 28 MW. The main objective is to provide practicing engineers with a flexible and reliable methodology to make design Fires for individual train carriages in performance-based Tunnel Fire safety design.
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Large Scale Tunnel Fire Tests with Large Droplet Water-Based Fixed Fire Fighting System
Fire Technology, 2016Co-Authors: Haukur Ingason, Ying Zhen Li, Glenn Appel, Ulf Lundström, Conny BeckerAbstract:This paper presents the main results of six large scale fixed Fire fighting system tests that were carried out in the Runehamar Tunnel in September 2013. It describes the background and the performance of the system. The main Fire load consisted of 420 standardized wood pallets and a target consisting of a pile of 21 wood pallets placed 5 m from the rear end of the main Fire load. The purpose was to investigate possible Fire spread. The water spray system is a deluge zone system delivering 10 mm/min in the activated zone. The detection system was simulated with use of thermocouple in the Tunnel ceiling. The alarm was registered when the ceiling gas temperature was 141°C. After alarm was obtained the system was activated manually after a given delay time that was varied in the tests. The heat release rates in tests with Fire suppression were reduced to 20–45 MW compared to 100 MW estimated for a free-burn test or 75 MW in test 6 with a failure of activation. Fire spread to the target was prevented after Fire suppression.
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Tunnel Fire dynamics
2015Co-Authors: Haukur Ingason, Anders LönnermarkAbstract:Introduction.- Fuel and ventilation controlled Fires.- Tunnel Fire tests.- Heat release rates in Tunnels.- Fire growth rates in Tunnels.- Design Fire curves.- Combustion products from Fires.- Gas temperatures.- Flame length.- Heat flux and thermal resistance.- Fire spread.- Smoke stratification.- Tunnel Fire ventilation.- Visibility.- Tenability.- Fire suppression and detection in Tunnels.- CFD modeling of Tunnel Fires.- Scaling technique.
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Tunnel Fire tests
2015Co-Authors: Haukur Ingason, Anders LönnermarkAbstract:This chapter gives a detailed overview of numerous large-scale Fire tests carried out in different types of Tunnels. Some important model scale Tunnel Fire tests are also included. The information given, sets the level of knowledge from this type of Tunnel Fire testing. The reason for doing tests is to obtain new knowledge about different phenomena. Although the focus is on large-scale testing, the fundamental knowledge is obtained both from large-scale and intermediate size Tunnel testing as well as laboratory testing (For example, scale models). The aim is usually to investigate some specific problems such as influence of different ventilation systems on smoke and temperature distribution along the Tunnel, the Fire development in different type of vehicles, and the effect of heat exposure on the integrity and strength of the Tunnel construction.
Fei Tang - One of the best experts on this subject based on the ideXlab platform.
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longitudinal distributions of co concentration and temperature in buoyant Tunnel Fire smoke flow in a reduced pressure atmosphere with lower air entrainment at high altitude
International Journal of Heat and Mass Transfer, 2014Co-Authors: Longhua Hu, Lizhong Yang, Fei Tang, Xiaochun ZhangAbstract:Abstract Smoke temperature and CO (carbon monoxide) concentration are two most important parameters concerning human safety in case of a Tunnel Fire. Their longitudinal distributions in the smoke flow along the Tunnel are both closely related to fresh air entrainment from the surroundings; meanwhile heat loss process also contributes to the temperature decay but not to the CO concentration dilution at the same time. However, previous researches are all considering in default the condition with normal pressure, which is needed to be extended for condition at reduced pressure atmosphere such as at high altitude (for example, Tibet). This paper reports new findings for the distributions of these two parameters in a reduced pressure atmosphere with lower air density and thus lower air entrainment. The longitudinal distributions of smoke flow temperature and CO concentration for a Tunnel Fire near sea level (1 atm) and at high altitude (0.64 atm) have been correspondingly computed and compared by Fire Dynamics Simulator (FDS). It is found that the longitudinal decay profiles of CO concentration are similar in these two pressures, as both the air entrainment mass flow rate during the smoke flow traveling (contributing to the dilution) and the air entrainment of the Fire plume (dominating the initial mass flow rate of the smoke flow) are proportional to ambient pressure thus their ratio is independent of pressure. However, the longitudinal decay of the smoke flow temperature is faster with distance along the Tunnel in the reduced pressure atmosphere, as the air entrainment of the Fire plume (dominating the initial mass flow rate of the smoke flow) is lower in the reduced pressure atmosphere, meanwhile the heat loss term is independent of pressure giving their ratio (heat loss to initial mass flow rate) is larger in the reduce pressure. Therefore, the difference between normalized longitudinal profiles of CO concentration and smoke temperature in a Tunnel Fire is larger, as indicated by a higher λ coefficient value, in the reduced pressure atmosphere at higher altitude than that in the normal pressure atmosphere, although their values of λ for both these two atmospheric pressure can be well correlated by a reciprocal function with longitudinal air flow speed.
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longitudinal distributions of co concentration and difference with temperature field in a Tunnel Fire smoke flow
International Journal of Heat and Mass Transfer, 2010Co-Authors: Fei Tang, Dong Yang, S Liu, R HuoAbstract:Abstract Longitudinal decay profiles of CO concentration and smoke temperature in a Tunnel Fire smoke flow are theoretical analyzed and compared, with their difference investigated, under different longitudinal ventilation velocities. Experimental data on longitudinal CO distribution achieved from a set of full scale road Tunnel Fire tests are presented to compare with the theoretical equation. CFD simulations are also carried out by Fire Dynamics Simulator (FDS). It is found that the longitudinal profile of CO concentration along the Tunnel yields a function of Cx/C0 = 1/(1 + bx), and its difference with that of the smoke temperature increases along the Tunnel by a function of C x / C 0 - Δ T x / Δ T 0 ≈ λ ( 1 - e - Kx ) . The smoke temperature decays much faster than the CO concentration along the Tunnel. Their longitudinal profile difference decreases as the longitudinal ventilation velocity increases, and increases along with the distance away from the Fire asymptotically to a quasi-steady value. The value of b decreases as the longitudinal ventilation velocity increases, which indicates that the CO concentration decays relatively slower along the Tunnel under a higher longitudinal ventilation velocity. And its value is shown to be less affected by the longitudinal ventilation velocity for a relative larger Fire. The increase in the longitudinal ventilation velocity leads to the enhancement of the air mass entrainment, thus results in the decrease of the longitudinal decay profile difference between the CO concentration and the smoke temperature. The value of λ is found to decrease with the increase of the longitudinal ventilation velocity, following a reciprocal function of λ ∼ 1 / ( ϕ + α u ) . Its value at zero longitudinal ventilation velocity is higher for a larger Fire, but decreases faster with the increase of the longitudinal ventilation velocity than a smaller Fire. The full scale experimental data and the CFD simulation results both agree well with the theoretical analysis and equations.
Paul Pauli - One of the best experts on this subject based on the ideXlab platform.
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social influence in a virtual Tunnel Fire influence of conflicting information on evacuation behavior
Applied Ergonomics, 2014Co-Authors: Max Kinateder, Mathias Muller, Michael Jost, Andreas Muhlberger, Paul PauliAbstract:Evacuation from a smoke filled Tunnel requires quick decision-making and swift action from the Tunnel occupants. Technical installations such as emergency signage aim to guide Tunnel occupants to the closest emergency exits. However, conflicting information may come from the behavior of other Tunnel occupants. We examined if and how conflicting social information may affect evacuation in terms of delayed and/or inadequate evacuation decisions and behaviors. To this end, forty participants were repeatedly situated in a virtual reality smoke filled Tunnel with an emergency exit visible to one side of the participants. Four social influence conditions were realized. In the control condition participants were alone in the Tunnel, while in the other three experimental conditions a virtual agent (VA) was present. In the no-conflict condition, the VA moved to the emergency exit. In the active conflict condition, the VA moved in the opposite direction of the emergency exit. In the passive conflict condition, the VA stayed passive. Participants were less likely to move to the emergency exit in the conflict conditions compared to the no-conflict condition. Pre-movement and movement times in the passive conflict condition were significantly delayed compared to all other conditions. Participants moved the longest distances in the passive conflict condition. These results support the hypothesis that social influence affects evacuation behavior, especially passive behavior of others can thwart an evacuation to safety.
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social influence on route choice in a virtual reality Tunnel Fire
Transportation Research Part F-traffic Psychology and Behaviour, 2014Co-Authors: Max Kinateder, Enrico Ronchi, Daniel Gromer, Mathias Muller, Michael Jost, Markus Nehfischer, Andreas Muhlberger, Paul PauliAbstract:Abstract Introduction Evacuation from Tunnel Fire emergencies requires quick decision-making and swift action from the Tunnel occupants. Social influence (SI) has been identified as an important factor in evacuation. Methods Two experimental groups were immersed into a virtual road Tunnel Fire. In the SI group participants saw a virtual agent moving on the shortest route to the nearest emergency exit. In the control group, participants were alone. Destination and exit choices were analyzed using functional analysis and inferential statistics. Results SI affected route choice during evacuation but not destination choice: There were no group differences regarding destination choice. Participants in the SI group were more likely to choose a route similar to the virtual agent. Participants in the control group were more likely to choose a longer route along the Tunnel walls. Discussion Social influence does not only affect behavior activation but also more subtle choices, such as route choice, during evacuation.
Anders Lönnermark - One of the best experts on this subject based on the ideXlab platform.
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Tunnel Fire dynamics
2015Co-Authors: Haukur Ingason, Anders LönnermarkAbstract:Introduction.- Fuel and ventilation controlled Fires.- Tunnel Fire tests.- Heat release rates in Tunnels.- Fire growth rates in Tunnels.- Design Fire curves.- Combustion products from Fires.- Gas temperatures.- Flame length.- Heat flux and thermal resistance.- Fire spread.- Smoke stratification.- Tunnel Fire ventilation.- Visibility.- Tenability.- Fire suppression and detection in Tunnels.- CFD modeling of Tunnel Fires.- Scaling technique.
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Tunnel Fire tests
2015Co-Authors: Haukur Ingason, Anders LönnermarkAbstract:This chapter gives a detailed overview of numerous large-scale Fire tests carried out in different types of Tunnels. Some important model scale Tunnel Fire tests are also included. The information given, sets the level of knowledge from this type of Tunnel Fire testing. The reason for doing tests is to obtain new knowledge about different phenomena. Although the focus is on large-scale testing, the fundamental knowledge is obtained both from large-scale and intermediate size Tunnel testing as well as laboratory testing (For example, scale models). The aim is usually to investigate some specific problems such as influence of different ventilation systems on smoke and temperature distribution along the Tunnel, the Fire development in different type of vehicles, and the effect of heat exposure on the integrity and strength of the Tunnel construction.
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runehamar Tunnel Fire tests
Fire Safety Journal, 2015Co-Authors: Haukur Ingason, Anders LönnermarkAbstract:Five large-scale Fire tests, including one pool Fire test and four HGV mock-up Fire tests, were carried out in the Runehamar Tunnel in Norway in year 2003. Detailed information about these tests is ...
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Fire Suppression and Detection in Tunnels
Tunnel Fire Dynamics, 2014Co-Authors: Haukur Ingason, Ying Zhen Li, Anders LönnermarkAbstract:The basic concepts of Fire suppression systems are depicted. There are mainly two water-based Fire suppression systems used in Tunnels, that is, water spray systems and water mist systems. The main differences are the water density, pressure, and droplet size. The extinguishment mechanisms are explored and the critical conditions at extinction are discussed. Further, suppression of realistic Fires is discussed considering both the water flow rate and the total water flow rate used for Fire suppression. A summary of Fire suppression tests carried out in Tunnels is presented followed by a short discussion of Tunnel Fire detection.
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performance based design of road Tunnel Fire safety proposal of new swedish framework
Case Studies in Fire Safety, 2014Co-Authors: Jonatan Gehandler, Anders Lönnermark, Haukur Ingason, Hakan Frantzich, Michael StromgrenAbstract:This paper contains a proposal of new Swedish framework for performance-based design of road Tunnel Fire safety derived from Swedish and European regulation. The overall purpose of the guideline is to protect life, health, property, environment, and key societal functions from Fire. The guideline is structured into five key groups of requirements: #1 Proper management and organisation, #2 to limit the generation and spread of Fire and smoke, #3 to provide means for safe self-evacuation, #4 to provide means and safety for the rescue service, and #5 to ensure load-bearing capacity of the construction. Each group contains a hybrid of prescriptive requirements, performance-based requirements, and acceptable solutions. Prescriptive requirements must be fulfilled, however, it is the choice of the design team to either adopt the proposed acceptable solutions, or to design alternative solutions by verifying that performance-based requirements are satisfied. For verification of performance-based requirements through risk analysis the operational, epistemic, and aleatory uncertainties are considerable. Therefore, a scenario-based risk analysis with several specified input variables and methods is recommended for verification of #3 and #5. Indispensable complements are scenario exercises, emergency exercises and similar methods that validate the design and highlight organisational aspects. The proposed design guide has been developed by the authors together with the advisory group established for the work.
Andreas Muhlberger - One of the best experts on this subject based on the ideXlab platform.
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social influence in a virtual Tunnel Fire influence of conflicting information on evacuation behavior
Applied Ergonomics, 2014Co-Authors: Max Kinateder, Mathias Muller, Michael Jost, Andreas Muhlberger, Paul PauliAbstract:Evacuation from a smoke filled Tunnel requires quick decision-making and swift action from the Tunnel occupants. Technical installations such as emergency signage aim to guide Tunnel occupants to the closest emergency exits. However, conflicting information may come from the behavior of other Tunnel occupants. We examined if and how conflicting social information may affect evacuation in terms of delayed and/or inadequate evacuation decisions and behaviors. To this end, forty participants were repeatedly situated in a virtual reality smoke filled Tunnel with an emergency exit visible to one side of the participants. Four social influence conditions were realized. In the control condition participants were alone in the Tunnel, while in the other three experimental conditions a virtual agent (VA) was present. In the no-conflict condition, the VA moved to the emergency exit. In the active conflict condition, the VA moved in the opposite direction of the emergency exit. In the passive conflict condition, the VA stayed passive. Participants were less likely to move to the emergency exit in the conflict conditions compared to the no-conflict condition. Pre-movement and movement times in the passive conflict condition were significantly delayed compared to all other conditions. Participants moved the longest distances in the passive conflict condition. These results support the hypothesis that social influence affects evacuation behavior, especially passive behavior of others can thwart an evacuation to safety.
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social influence on route choice in a virtual reality Tunnel Fire
Transportation Research Part F-traffic Psychology and Behaviour, 2014Co-Authors: Max Kinateder, Enrico Ronchi, Daniel Gromer, Mathias Muller, Michael Jost, Markus Nehfischer, Andreas Muhlberger, Paul PauliAbstract:Abstract Introduction Evacuation from Tunnel Fire emergencies requires quick decision-making and swift action from the Tunnel occupants. Social influence (SI) has been identified as an important factor in evacuation. Methods Two experimental groups were immersed into a virtual road Tunnel Fire. In the SI group participants saw a virtual agent moving on the shortest route to the nearest emergency exit. In the control group, participants were alone. Destination and exit choices were analyzed using functional analysis and inferential statistics. Results SI affected route choice during evacuation but not destination choice: There were no group differences regarding destination choice. Participants in the SI group were more likely to choose a route similar to the virtual agent. Participants in the control group were more likely to choose a longer route along the Tunnel walls. Discussion Social influence does not only affect behavior activation but also more subtle choices, such as route choice, during evacuation.
