Variability of sprinkler response time index and conduction factor using the plunge test

Tsui, Albert K.; Spearpoint, Michael

doi:10.1177/0143624410363064

Cited by 7 publications

(8 citation statements)

References 11 publications

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“…For a capped fire, shown in Figure 8, all sprinkler heads are actuated in the simulations and therefore includes the missing actuations not determined in the uncapped simulations. However, it can be seen that in cases of a corner fire with the door closed (Experiments [16][17][18][19][20][21][22], the model is less accurate in its prediction, where in some cases it overpredicts the actuation time by as much as 108 s.…”

Section: Modelling Resultsmentioning

confidence: 99%

“…The sprinkler offset below the ceiling has been selected based on an approximate 20 mm glass bulb length and a C-factor of 0.4 (m/s) ½ selected based on sensitivity analyses undertaken in the original studies and the subsequent work of Tsui and colleagues. 17,18 Additional sensitivity analyses for the C-factor have been undertaken using FDS and are discussed later. Table 2 shows a summary of the results of the experiments, indicating the fire location, experiment number, sprinkler head type for each sprinkler, as well as the recorded sprinkler actuation time.…”

Section: Sprinkler Characteristicsmentioning

confidence: 99%

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Using experimental sprinkler actuation times to assess the performance of Fire Dynamics Simulator

Hopkin¹,

Spearpoint²,

Bittern

2018

Journal of Fire Sciences

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This article considers the predictive capabilities of Fire Dynamics Simulator for sprinkler actuation time when benchmarked against data from a series of 22 enclosure experiments. Sensitivity analyses have been undertaken for grid size, conductivity factor, radiative fraction and enclosure leakage areas. 'Goodness of fit' calculations indicate that Fire Dynamics Simulator is able to provide an average prediction of sprinkler actuation time within a Euclidean relative difference of 0.18. Comparisons to results determined in previous studies, using different modelling methods and Fire Dynamics Simulator versions, have also been made. The sensitivity analyses and comparisons indicate the importance of the decisions made by the modeller in representing fire scenarios, even when modelling 'simple' experiments where data for inputs such as the heat release rate, geometry and sprinkler characteristics are available. The comparisons therefore indicate that with the reduced degrees of freedom compared to other modelling studies, there is still potential for a range of assumptions and simulation results.

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Section: Modelling Resultsmentioning

confidence: 99%

Section: Sprinkler Characteristicsmentioning

confidence: 99%

Using experimental sprinkler actuation times to assess the performance of Fire Dynamics Simulator

Hopkin¹,

Spearpoint²,

Bittern

2018

Journal of Fire Sciences

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“…The sprinklers are assumed to have a nominal operating temperature of 68°C. 7 For the C factor of residential heads, Tsui and Spearpoint 17 identified a range of 0.33 to 0.45 m ½ s −½ . Therefore, a value of 0.4 m ½ s −½ has been adopted, consistent with prior sprinkler modelling studies by Hopkin et al.…”

Section: Modelling Methodologymentioning

confidence: 99%

Numerical simulations of concealed residential sprinkler head activation time in a standard thermal response room test

Hopkin

Spearpoint²

2020

Building Services Engineering Research and Technology

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It is common for sprinkler heads in residential buildings to be of the concealed type. Key parameters for the thermal sensitivity of sprinkler heads are the response time index (m½s½) and conductivity factor (C factor, m½s−½). BS 9252:2011 and BS EN 12259-14:2020 outline test methods to determine whether sprinkler heads achieve adequate thermal sensitivity, stipulating that a room test be undertaken for concealed heads. In carrying out this test, neither the response time index nor C factor is defined. This paper uses computational modelling tools Fire Dynamics Simulator and B-RISK to simulate the room test. In running these simulations, maximum values for the ‘effective’ response time index and C factor needed to pass the room test can be estimated, assuming concealed heads can be represented as equivalent pendent heads. Initial deterministic simulations are used to calibrate results between Fire Dynamics Simulator and B-RISK. Monte Carlo modelling is then utilised within B-RISK, with variable parameters for the response time index and C factor (C), to estimate the relationship between the two parameters necessary to pass the room test. As a result, it is proposed that this relationship can be represented using a simple, empirical power law equation of response time index = 100 (5.4–C)2/3, where C < 5.4. Practical application: The results indicate that the minimum RTI and C factor values needed to pass the room test are greater than those needed to pass wind tunnel testing methods. In observing that equivalency is not demonstrated by the room test, and by defining the RTI/C factor relationship needed to pass the test, this paper provides fire safety engineers with amended values for concealed heads to be adopted in future assessments. In the absence of any detailed specification for sprinkler heads, it is recommended that an RTI of 290 m½s½ and a C factor of 0.5 m½s−½ may be applied.

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“…The sprinklers used for the experimental data were also used in a study to characterise the uncertainty in the response time index (RTI) and conduction (C) sprinkler parameters [24]. The sprinkler parameter study used the plunge test method under a range of wind tunnel temperature and velocity conditions in both parallel and perpendicular flow orientations.…”

Section: Sprinkler Parametersmentioning

confidence: 99%

A Comparison of Sources of Uncertainty for Calculating Sprinkler Activation

Frank¹,

Spearpoint²,

Fleischmann³

et al. 2011

Fire Safety Science - Proceedings of the 10th International Sym

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Treatment of uncertainty is an important consideration when performing a quantitative risk assessment (QRA) for the purpose of performance-based fire safety design. It has been noted in New Zealand that the outcome for fire QRAs is sensitive to uncertainty in the effectiveness of fire safety systems, including sprinkler systems. This paper considers the uncertainty in sprinkler activation time and the heat release rate (HRR) at the time of sprinkler activation for two scenarios; one where a set of sprinkler experiments in a room is modelled and the second which considers a more general design case for the same room. The relative importance of aleatoric (natural) and epistemic (model) uncertainties is shown to depend on the scenario being modelled. Twelve sources of uncertainty were quantified based on literature data and ranked for the scenarios considered. A new probabilistic-deterministic design tool for making risk-informed fire safety decisions is used to calculate output distributions for the two parameters considered and the sources of uncertainty are ranked in terms of sensitivity for output uncertainty. It is found that fire growth rate tends to be more important than the model uncertainty associated with the deterministic zone model engine for the scenarios considered, and uncertainty in the fire location becomes more important than the model uncertainty in design cases where there is greater uncertainty. Uncertainty in sprinkler response parameters and the ambient interior temperature provided the least contribution to the output uncertainties.

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Variability of sprinkler response time index and conduction factor using the plunge test

Cited by 7 publications

References 11 publications

Using experimental sprinkler actuation times to assess the performance of Fire Dynamics Simulator

Using experimental sprinkler actuation times to assess the performance of Fire Dynamics Simulator

Numerical simulations of concealed residential sprinkler head activation time in a standard thermal response room test

A Comparison of Sources of Uncertainty for Calculating Sprinkler Activation

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