Fire Performance of Sandwich Panels in a Modified ISO 13784-1 Small Room Test: The Influence of Increased Fire Load for Different Insulation Materials

Crewe, Robert J.; Hidalgo, Juan P.; Sørensen, Martin X.; McLaggan, Martyn S.; Molyneux, Shirley; Welch, Stephen; Jomaas, Grunde; Torero, José L.; Stec, Anna A.; Hull, T. Richard

doi:10.1007/s10694-018-0703-5

Cited by 13 publications

(10 citation statements)

References 19 publications

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“…Crewe et al 30 In the case of a thermally thick protection such as the plasterboard, it is clearly shown that the peak MLR is below the limit of 2 g·m −2 ·s −1 . At this rate, it is unlikely that self-sustained burning would occur; however, flaming may be achieved under particular conditions as observed in these experiments.…”

Section: Figure 12mentioning

confidence: 99%

Fire performance of closed‐cell charring insulation materials in plasterboard‐insulation assemblies

2019

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Summary This paper presents an experimental study on the fire performance of two types of plastic charring insulation materials when covered by a plasterboard lining. The specific insulation materials correspond to rigid closed‐cell plastic foams, a type of polyisocyanurate (foam A) and a type of phenolic foam (foam B), whose thermal decomposition and flammability were characterised in previous studies. The assemblies were instrumented with thermocouples. The plasterboard facing was subjected to constant levels of irradiation of 15, 25, and 65 kW m−2 using the heat‐transfer rate inducing system. These experiments serve as (1) an assessment of the fire behaviour of these materials studied at the assembly scale and (2) an identification of the fire hazards that these systems pose in building construction. The manifestation of the hazards occurred via initial pyrolysis reactions and release of volatiles followed by various complex behaviours including char oxidation (smouldering), cracking, and expansion of the foam. Gas‐phase conditions may support ignition of the volatiles, sustained burning, and ultimately spread of the flame through the unexposed insulation face. The results presented herein are used to validate the insulation “critical temperature” concept used for a performance‐based methodology focused on the selection of suitable thermal barriers for flammable insulation.

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Section: Figure 12mentioning

confidence: 99%

Fire performance of closed‐cell charring insulation materials in plasterboard‐insulation assemblies

2019

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“…Their results showed that using additional reinforcement can remarkably enhance the ultimate stiffness and strength. Crewe et al (2018) conducted experimental tests on four sandwich panel walls which were made according to ISO 13784-1. The wall thickness was 100 mm with the dimension of 2.43.62.4 as width, length and height, in order.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Sandwich Panel Under High Temperature Loading Using Finite Element Analysis

Roudsari

Shalbaftabar

Abu-Lebdeh

et al. 2020

American Journal of Engineering and Applied Sciences

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Structural and nonstructural members are always encountered with extreme loading conditions. In case of nonstructural members, the failure happens much sooner due to lack of load capacity. The nonstructural elements are not designed for structural loading conditions. However, they might be impacted to other loading types such as fire. In recent years, the use of 3D panel is one of the most common partitions in the world. In this research, the effect of fire on 3D panel partitions is presented. To achieve this goal, ABAQUS finite element software is employed to simulate the 3D panel. The 3D panel is embedded inside steel frame. In order to have an accurate result, two validations are performed including steel frame and the steel frame with 3D panel. In the study, 5 different fire loadings 200, 400, 600, 800 and 1000°C are applied into the model. Results include loaddisplacement diagram and stiffness and ductility factors. The results indicated that as fire load increases, the stiffness and ductility factor are reduced.

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“…Here 17,18 showed that fires in commercial premises were often much higher than the prescribed 300 kW and had a longer duration than 30 minutes. Therefore, Leisted 15 added two gas burner regimes with a third burner intensity and two regimes with a continuous burner output to allow for more (severe) testing conditions.…”

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Testing for knowledge: Application of machine learning techniques for prediction of flashover in a 1/5 scale ISO 13784‐1 enclosure

et al. 2020

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A machine learning algorithm was applied to predict the onset of flashover in archival experiments in a 1/5 scale ISO 13784-1 enclosure constructed with sandwich panels.The experiments were performed to assess whether a small-scale model could provide a better full-scale correlation than the single burning item test. To predict the binary output, a regularized logistic regression model was chosen as ML environment, for which lasso-regression significantly reduced the amount of variance at a negligible increase in bias. With the regularized model, it was possible to discern the predictive variables and determine the decision boundary. In addition, a methodology was put forward on how to use the to update the learning algorithm iteratively. As a result, it was shown how a learning algorithm can be used to facilitate ongoing experimentation. At first as a crude guideline, and in later stages, as an accurate prediction algorithm. It is foreseen that, by iteratively updating the algorithm, by compiling existing and new experiments in databases, and by applying fire safety knowledge, the final learned algorithm will be able to make accurate predictions for unseen samples and test conditions.

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Fire Performance of Sandwich Panels in a Modified ISO 13784-1 Small Room Test: The Influence of Increased Fire Load for Different Insulation Materials

Cited by 13 publications

References 19 publications

Fire performance of closed‐cell charring insulation materials in plasterboard‐insulation assemblies

Fire performance of closed‐cell charring insulation materials in plasterboard‐insulation assemblies

Investigation of Sandwich Panel Under High Temperature Loading Using Finite Element Analysis

Testing for knowledge: Application of machine learning techniques for prediction of flashover in a 1/5 scale ISO 13784‐1 enclosure

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