Effect of Combustion Conditions on Species Production

Gottuk, Daniel T.; Lattimer, Brian Y.

doi:10.1007/978-1-4939-2565-0_16

Cited by 21 publications

(38 citation statements)

References 16 publications

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“…The reaction equation for polyurethane (Equation ) was formed with the general reaction equation in the following. The molecular formula for polyurethane is based on literature . Six reaction equations for polyurethane from the DIN‐tube and two reaction equations from the cone calorimeter measurements can be formed with the values from Table :

1 C_{6.3} H_{7.1} {NO}_{2.1} + x_{reac} O_{2} \to x_{reac} {normalC normalO}_{2} + x_{reac} normalC normalO + x_{reac} soot + x_{reac} normalH normalC normalN + x_{reac} H_{2} normalO

where C 6.3 H 7.1 NO 2.1 is the molecular formula for polyurethane and x reac is the reaction coefficient for every smoke product.…”

Section: Resultsmentioning

confidence: 99%

“…The reaction equation for polyurethane (Equation (12)) was formed with the general reaction equation in the following. The molecular formula for polyurethane is based on literature [27]. Six reaction equations for polyurethane from the DIN-tube and two reaction equations from the cone calorimeter measurements can be formed with the values from Table III:…”

Section: Resultsmentioning

confidence: 99%

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CFD modeling approach of smoke toxicity and opacity for flaming and non‐flaming combustion processes

et al. 2015

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Summary Current engineer's methods of fire safety design include various approaches to calculate the fire propagation and smoke spread in buildings by means of computational fluid dynamics (CFD). Because of the increased computational capacity, CFD is commonly used for prediction of time‐dependent safety parameters such as critical temperature, smoke layer height, rescue times, distributions of chemical products, and smoke toxicity and visibility. The analysis of smoke components with CFD is particularly complex, because the composition of the fire gases and also the smoke quantities depends on material properties and also on ambient and burning conditions. Oxygen concentrations and the temperature distribution in the compartment affect smoke production and smoke gas toxicity qualitatively and quantitatively. For safety designs, it can be necessary to take these influences into account. Current smoke models in CFD often use a constant smoke yield that does not vary with different fire conditions. If smoke gas toxicity is considered, a simple approach with the focus on carbon monoxide is often used. On the basis of a large set of experimental data, a numerical smoke model has been developed. The developed numerical smoke model includes optical properties, production, and toxic potential of smoke under different conditions. For the setup of the numerical model, experimental data were used for calculation of chemical components and evaluation of smoke toxicity under different combustion conditions. Therefore, averaged reaction equations were developed from experimental measurements and implemented in ANSYS CFX 14.0. Copyright © 2015 John Wiley & Sons, Ltd.

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1 C_{6.3} H_{7.1} {NO}_{2.1} + x_{reac} O_{2} \to x_{reac} {normalC normalO}_{2} + x_{reac} normalC normalO + x_{reac} soot + x_{reac} normalH normalC normalN + x_{reac} H_{2} normalO

where C 6.3 H 7.1 NO 2.1 is the molecular formula for polyurethane and x reac is the reaction coefficient for every smoke product.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

CFD modeling approach of smoke toxicity and opacity for flaming and non‐flaming combustion processes

et al. 2015

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“…After getting all the parameters, the global equivalence ratio can be calculated using Equ.(4.10). The global equivalence ratio represents the fuel-to-air mass ratio in the fire compartment normalized by the stoichiometric fuel-to-air ratio [107]. The stoichiometric fuel-to-air ratio of wood (spruce) is 0.258 [107].…”

Section: Global Equivalence Ratiomentioning

confidence: 99%

“…The global equivalence ratio represents the fuel-to-air mass ratio in the fire compartment normalized by the stoichiometric fuel-to-air ratio [107]. The stoichiometric fuel-to-air ratio of wood (spruce) is 0.258 [107]. The global equivalence ratio is a measure of the room air depletion conditions; it is ventilation controlled fire if  >1, and well ventilated fire if  <1.…”

Section: Global Equivalence Ratiomentioning

confidence: 99%

“…Actually this is a very approximate assumption. A related study [108] shows that oxygen concentration approaches zero in an under-ventilated ( >1) fire, especially in a high temperature environment, though a very limited yet unknown amount of oxygen might leave the room with the combustion products and burn outside [107]. The maximum possible heat release rate in the room can be calculated by Equ.…”

Section: Maximum Heat Release Rate Inside the Roommentioning

confidence: 99%

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Modeling of Barrier Failure and Fire Spread in CUrisk

Li¹

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CUrisk, a computer fire risk analysis model, has been under development at Carleton University for over a decade. To better evaluate failure of building elements and spread of fire beyond the room of fire origin, this thesis developed and integrated into CUrisk a barrier failure model and a fire spread model. A probabilistic fire spread model developed at Carleton University was incorporated into CUrisk system model. The role and position of the Fire Spread submodel were analyzed I would like to thank Dr. Xia Zhang whom I regarded as my co-supervisor. Dr. Zhang was always ready to help when I had questions with my research. He is my role model and one of the greatest scholars I have ever met. His positive attitude toward life and deep loves to his family are something I should also learn.

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A review on prediction models for full‐scale fire behaviour of building products

Lundström

Hees

Guillaume³

2016

Fire and Materials

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This study aims to give an overview over different reaction-to-fire prediction models developed over the last decades by finding similarities and differences between models, as well as identifying their robustness in scaling. The models have been divided into four categoriesempirical, thermal, polynomial and comprehensivedepending on how pyrolysis is modelled. Empirical models extrapolate bench-scale test results to larger scales. These models are pertinent to applications that they have been validated for, but surfacic parameters used may not be scalable. In thermal models, pyrolysis is represented by heat transfer rates. The models are feasible for materials with high activation energies and where little pyrolysis occur before ignition. Polynomial models are empirical models that also take the environment into account. The validity of scaling is yet to be established. The comprehensive methodology includes chemical kinetics in the condensed phase. It has the potential to be used for any application; however, many parameters are needed. This increases the degrees of freedom versus data available for the description of the problem. Consequently, possible errors are introduced, and uncertainty is increased. A comprehensive multi-scale methodology is a way forward, where many steps of validation are possible.

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Effect of Combustion Conditions on Species Production

Cited by 21 publications

References 16 publications

CFD modeling approach of smoke toxicity and opacity for flaming and non‐flaming combustion processes

CFD modeling approach of smoke toxicity and opacity for flaming and non‐flaming combustion processes

Modeling of Barrier Failure and Fire Spread in CUrisk

A review on prediction models for full‐scale fire behaviour of building products

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