William D. Davis

Quantifying Fire Model Evaluation Using Functional Analysis

Comparisons of predictive fire models with each other or with experimental data have been largely qualitative. By treating these time series curves as infinite-dimensional vectors, a branch of mathematics called functional analysis defines geometrically meaningful operations on the curves. This allows lengths, angles, and distance between two arbitrary curves to be defined and quantified. An introduction to the theory and tools provided by functional analysis is presented. Examples of the application of these tools to fire model evaluation are presented.

A computer model for estimating the response of sprinkler links to compartment fires with draft curtains and fusible link-actuated ceiling vents

A computer program, LAVENT, is now available which computes the heating of fusible links due to the presence of a ceiling jet imbedded in an upper layer. An important new feature in this program is that the two-dimensional structure of the ceiling jet is taken into account such that the location of the link beneath the ceiling plays a role in the response of the link. The links can be used to activate ceiling vents such that the effect of venting the upper layer on the ceiling jet may be studied. Additional applications would include the study of upper layer containment through the use of a combination of draft curtains and ceiling vents. The geometry modeled by the program is that of a large compartment enclosed by a combination of walls and draft curtains.

Developing detector siting rules from computational experiments in spaces with complex geometries

Abstract The National Institute of Standards and Technology (NIST) is conducting a 4-year research project wherein a computational fluid dynamics (CFD) computer code is utilized to map temperature, flow velocities, and particle densities in spaces with complex ceiling geometries. Through parametric variation of independent variables for the fire and the space, the number and location of smoke or thermal sensors required to assure response prior to a critical fire size is determined. The first year addressed horizontal ceilings with open beams or joists, and the second year adds sloped ceilings. In addition to the geometric studies, several special studies have been conducted. These include detection of low energy fires (as low as 100 W), stratification of fire gases in spaces with a vertical thermocline which exceeds the plume temperature, and obstructions which do not come, completely to the ceiling. A unique method of relating the response of detectors to the predicted conditions has been developed which can be utilized with any CFD model or with experimental data. The data analysis is being used to produce siting rules for inclusion directly into existing codes. The paper will review the results of the first 2 years of the project and present some thoughts on the potential for these techniques to greatly improve the technical basis for the utilization of fire sensors in complex installations.

Comparison of Fire Model Predictions With Experiments Conducted in a Hangar With a 15 Meter Ceiling.

The purpose of this study is to examine the predictive capabilities of fire models using the results of a series of fire experiments conducted in an aircraft hangar with a ceiling height of about 15 m. This study is designed to investigate model applicability at a ceiling height where only a limited amount of experimental data is available. This analysis deals primarily with temperature comparisons as a function of distance from the fire center and depth beneath the ceiling. Only limited velocity measurements in the ceiling jet were available but these are also compared with those models with a velocity predictive capability.

Using Sensor Signals to Analyze Fires

Building fire sensors are capable of supplying substantially more information to the fire service than just the simple detection of a possible fire. Nelson, in 1984, recognized the importance of tying all the building sensors to a smart fire panel [1]. In order to accomplish a smart fire panel configuration such as envisioned by Nelson, algorithms must be developed that convert the analog/digital signals received from sensors to the heat release rate (HRR) of the fire. Once the HRR of the fire is known, a multiroom zone fire model can be used to determine smoke layers and temperatures in the other rooms of the building. This information can then be sent to the fire service providing it with an approximate overview of the fire scenario in the building.This paper will describe a ceiling jet algorithm that is being developed to predict the heat release rate (HRR) of a fire using signals from smoke and gas sensors. The prediction of this algorithm will be compared with experiments. In addition, an example of the predictions from a sensor-driven fire model, SDFM, using signals from heat sensors, will be compared with measurements from a full-scale, two-story, flashover townhouse fire.

Comparison of Algorithms to Calculate Plume Centerline Temperature and Ceiling Jet Temperature with Experiments

The predictive capability of two algorithms designed to calculate plume centerline temperature and maximum ceiling jet temperature in the presence of a hot upper layer are compared to measurements from experiments that developed a hot layer. In addition, comparisons are made using the ceiling jet algorithm in CFAST (Version 3.1). The experiments include ceiling heights of 0.58m to 22m and heat release rates (HRR) of 0.62kW to 33MW. With the combined uncertainty of the measurement and the calculation roughly equal to 20%, the algorithms of Evans and Davis consistently provided predictions either close to or within this uncertainty interval for all fire sizes and ceiling heights while the ceiling jet algorithm in CFAST consistently over-predicted the temperature.

Analyzing smoke alarm response to flaming fires using the fire model JET

An algorithm that calculates the time dependent smoke concentration in a fire-induced ceiling jet within a smoke layer and algorithms for predicting the response of photoelectric smoke alarms, both of which are part of the computer model JET, are examined using three different fires in a small room. The objectives of this analysis are to test the ceiling jet smoke algorithm and understand the limitations of analyzing signals from photoelectric smoke alarms located in the ceiling jet to estimate fire size and thereby support decision making by emergency responders. The analysis is restricted to flaming fires that produce turbulent plumes and can be represented by axisymmetric point sources. Two different smoke yields from the literature are used to obtain ceiling jet smoke density from JET. Depending on the value of the smoke yield used, the predictions of JET follow or do not follow the photoelectric smoke alarm signals. This suggests that additional information about how smoke yields are measured or that a better calibration technique is required in order to accurately model smoke alarm response.

Simulating the Effect of Sloped Beamed Ceilings on Detector and Sprinkler Response (NISTIR 5499)

This paper presents the first measurements of the burning rate of premixed flames inhibited by three fluorinated hydrocarbons who’s chemistry is similar to agents which may he used as replacements for CF3Br. Measurements were made of the reduction in the burning rate of premixed methane-air flames stabilized on a Mache-Hebra nozzle burner. The burning rate was determined with the total area method from Schlieren images of the flame. The inhibitors were tested over a range of concentrations and fuel-air equivalence ratios. The measured burning rate reductions are compared with those predicted by numerical solution of the species and energy conservation equations employing a detailed chemical kinetic mechanism recently developed at the National Institute of Standards and Technology (NIST). This paper presents initial efforts at testing and validation of the mechanism using burning rate data. The mode of inhibition of these chemicals is inferred through interpretation of the numerical results.