Investigating the effect of computational grid sizes on the predicted characteristics of thermal radiation for a fire

Lin, Ching Heng; Ferng, Yuh-Ming; Hsu, W. S.

doi:10.1016/j.applthermaleng.2008.11.010

Cited by 31 publications

(22 citation statements)

References 35 publications

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“…Values of 10 or more for the D * / x are required to obtain reliable predictions of the radiative heat flux [3]. Substituting the lowest considered value of HRR (25% of the nominal value 5600 kW) to Eq.…”

Section: Numericalmentioning

confidence: 99%

“…The test facility consists of a combustion chamber, facade specimen with side wall, opening and measurement devices. The combustion chamber has volume in range 20-100 m 3 , and it has a 2 m wide by 1.2 m high opening. The façade wall extends up to 4 m above the top edge of window, to the This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.…”

Section: Iso 13785-2 Standard Testmentioning

confidence: 99%

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Numerical simulations of the ISO 13785-2 façade fire tests

Hostikka

Bytskov

2016

MATEC Web of Conferences

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Abstract. In this work we created a numerical model of the ISO 13785-2 test setup for testing the fire behaviour of building façade systems, and used the model to simulate the thermal environment on the façade. The model, created using Fire Dynamics Simulatorsoftware, was first validated using the experimental data by Yoshioka et al. (2012). Next, the sensitivity of the façade heat fluxes on the geometrical and model parameters was studied, revealing for instance that the size of the combustion chamber window will influence the thermal exposure high above the window. Finally, the model was used to estimate the thickness of non-combustible insulation layer that is needed to protect combustible materials from melting or decomposition.

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Section: Numericalmentioning

confidence: 99%

Section: Iso 13785-2 Standard Testmentioning

confidence: 99%

Numerical simulations of the ISO 13785-2 façade fire tests

Hostikka

Bytskov

2016

MATEC Web of Conferences

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“…For surrounding fire tests, sensitivity studies shows that resolutions of 1/32, 1/23.5, 1/27.6 and 1/24.8 give best prediction of the heat fluxes for HRRs of 40.5 kW, 81 kW, 121.5 kW and 162 kW respectively (whilst using resolution of about 1/30 give acceptable prediction of heat fluxes for all cases). Those resolutions are finer than the expected values from literature (1/20 [13], 1 /13 [20]). As a result, it is recommended that the user should take special care of the grid size and sensitivity studies should be always conducted when performing simulations.…”

Section: Discussionmentioning

confidence: 41%

“…Resolution between 1/10 and 1/15 were chosen by Gutierrez-Montes et al [19] to successfully model atrium fires. Lin et al [20] suggested R*=1/13 is enough for CFD simulations to resolve the fire characteristics (flame height and thermal radiation).…”

Section: Grid Sizesmentioning

confidence: 99%

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Fire Dynamic Simulation on Thermal Actions in Localized Fires in Large Enclosure

Zhang

Li²

2012

Volume 8 Number 2

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ABSTRACT:Large enclosures commonly exist in many buildings like atria, open car parks and airport terminals. There is an international trend to prompt performance-based method (PBM) for fire resistance design. By PBM, the temperatures of structures in design fires should be determined. Localized fires are always adopted as design fires in large spaces. Currently, no agreed calculation method is available for the calculation of the heat flux from a localized fire to a vertical column. This paper aims at providing a feasible way of calculating the thermal actions in localized fires. Particularly, gas temperatures in localized fires and heat transfer from localized fires to steel vertical columns have been numerically investigated. The popular CFD code FDS is adopted as the numerical tool. A design fire scenario and four real localized fire tests are simulated in FDS. The effects of input parameters, including grid size and number of solid angles, on the accuracies of the numerical results have been investigated. Numerical results are compared with correlations and test data, which shows good agreement. INTRODUCTIONA compartment fire will generally undergo six stages which include ignition, growth, flashover, full fire development or steady burning, decay and extinguishment. Flashover is the rapid transition between the primary fire which is essentially localized around the item first ignited, and the general conflagration within the compartment when all fuel surfaces are burning [1]. Depending on whether flashover will happen or not, the real fires are usually divided into pre-and post-flashover fires. For small and middle scaled compartments with sufficient fuel and ventilation, the potential fires will develop to flashover and be characterized as post-flashover fires. For large scale enclosures or where sprinklers work effectively, flashover is unlikely to occur and the fires are characterized as pre-flashover fires. Post-flashover fires provide the worst case scenarios which are usually considered in fire resistance design. However, localized heating of key elements of structure in pre-flashover fires must be also considered.For post-flashover fires, the gas properties within the compartment are approximately uniform that temperature-time curves are usually adopted to represent the fire environments. Correspondingly, the temperature of exposed members can be easily determined by interpreting the homogenous gas temperature as the effective black body radiation temperature and as the same gas temperature for convection calculation. At present, various formulae are provided by fire codes in different countries for calculating the temperature of steel members in post-flashover fires [2][3][4]. However, for pre-flashover or localized fires, the distribution of gas temperature is spatially non-uniform.

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Numerical simulation of the fire behaviour of façade equipped with aluminium composite material‐based claddings—Model validation at intermediate scale

Dréan¹,

Girardin²,

Guillaume³

et al. 2019

Fire and Materials

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Summary Increasing the energy performance of buildings is a crucial sustainable development objective. However, building features, products, mounting, and fixing of façade components have a large impact on fire safety. Authors in previous study performed façade fire propagation tests according to ISO13785‐1 on different combinations of ACM claddings and insulants. In this paper, simulations are performed to reproduce three of these tests. The model is validated with the aforementioned experimental results, including details in terms of thermal conditions in the system. This allows better understanding of the fire propagation on the overall system. Additional information, such as the relative contribution of the cladding and the insulant, are investigated numerically. The fire behaviour of each component of the overall system is thus validated. Simulations and tests performed show that the ACM cladding is the most important element driving the global fire behaviour of façade types considered. In particular, ACM‐PE–based cladding systems show large fire propagation whatever the insulant. This series of simulations is a part of a larger study including several steps of increasing complexity. Once the model for the fire behaviour of façade system is validated at intermediate scale, larger façade systems will be investigated numerically to evaluate the influence of scaling.

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Investigating the effect of computational grid sizes on the predicted characteristics of thermal radiation for a fire

Cited by 31 publications

References 35 publications

Numerical simulations of the ISO 13785-2 façade fire tests

Numerical simulations of the ISO 13785-2 façade fire tests

Fire Dynamic Simulation on Thermal Actions in Localized Fires in Large Enclosure

Numerical simulation of the fire behaviour of façade equipped with aluminium composite material‐based claddings—Model validation at intermediate scale

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