Elizabeth J. Weckman

Experimental study of the flow field in and around a one meter diameter methane fire

Abstract Simultaneous temporally and spatially resolved, 2-D velocity fields are obtained using Particle Image Velocimetry (PIV) in a one-meter diameter methane fire. The flow rate of methane is 0.066 kg/m2-s, comparable to fuel burning rates in a large JP8 pool fire. Raw PIV images are recorded with 35 mm cinematography at 200 images/s. They are digitized and post-processed to obtain velocity data for a region ∼0.8 m high by 1 m wide centered on the centerline of the flame and extending from just above the surface of the burner to include the fuel core, near-field combusting zones, and surrounding air. The data cover 11 puff cycles of the fire. Instantaneous, phase-, and time-averaged 2-D velocity plots (103 × 82 vectors) are obtained for each of 1331 time-planes (121 time-planes per puff cycle) spaced 5 ms apart. Each vector represents a statistical estimate of the velocity in 2.1 cm by 2.1 cm by 0.8 cm volumes, which are overlapped by 50% in the vector plots. Time-averaged turbulent statistics ( u′ 2 , v′ 2 , & u′v′ ) are also presented. Boundary conditions have been carefully measured and the results are intended for validation of numerical simulations of the fire behavior. The results clearly show the dominant effect of puffing, measured at 1.65 cycles/s for this fire, on the temporal and spatial development of the velocity field.

Experimental study of a turbulent buoyant helium plume

An experimental study has been performed on the dynamics of a large turbulent buoyanthelium plume. Two-dimensional velocity fields were measured using particle image velocimetry (PIV) while helium mass fraction was determined by planar laser-induced fluorescence (PLIF). PIV and PLIF were performed simultaneously in order to obtain velocity and mass fraction data over a plane that encompassed the plume core, the near-field mixing zones and the surrounding air. The Rayleigh–Taylor instability at the base of the plume leads to the vortex that grows to dominate the flow. This process repeats in a cyclical manner. The temporally and spatially resolved data show a strong negative correlation between density and vertical velocity, as well as a strong 90° phase lag between peaks in the vertical and horizontal velocities throughout the flow field owing to large coherent structures associated with puffing of the turbulent plume. The joint velocity an mass fraction data are used to calculate Favre-averaged statistics in addition to Reynolds-(time) averaged statistics. Unexpectedly, the difference between both the Favre-averaged and Reynolds-averaged velocities and second-order turbulent statistics is less than the uncertainty in the data throughout the flow field. A simple analysis was performed to determine the expected differences between Favre and Reynolds statistics for flows with periodic fluctuations in which the density and velocity fields are perfectly correlated, but have the phase relations as suggested by the data. The analytical results agreewith the data, showing that the Favre and Reynolds statistics will be the same to lead order. The combination of observation and simple analysis suggests that for buoyancy-dominated flows in which it can be expected that density and velocity are strongly correlated,phase relations will result in only second-order differences between Favre- and Reynolds-averaged data in spite of strong fluctuations in both density and velocity.

A method to anchor displacement vectors to reduce uncertainty and improve particle image velocimetry results

When large fields of view are used with particle image velocimetry (PIV) in the study of complex fluid flows, extraneous effects linked to velocity gradients and non-uniformities in both image illumination and particle number density become more prevalent. These factors, coupled with the limiting requirement that large areas of interest (AOIs) must be employed to measure the full range of velocity, cause degradation of correlation results (i.e. broadening and/or splintering of the cross-correlation peaks). Advanced iterative and hierarchical PIV strategies provide improved results but these can break down in complex flows where velocity gradients are significant and particle dispersion does not remain uniformly random. One reason for this breakdown is that local displacement vectors obtained using the cross correlation method are not necessarily representative of the fluid motion where these vectors are typically anchored (namely, the geometric centre of the AOI). To address this issue a simple but effective technique is presented that enables individual displacement vectors to be anchored within an AOI at a location(s) where the actual fluid motion is more consistent with the measured displacement. The method involves a straightforward approach to extract the intensity features from within each AOI that most influence the calculation of the cross-correlation plane. To demonstrate the utility of the methodology, bounds of uncertainty are approximated, and results obtained from the analysis of high gradient synthetic flow fields are compared against results obtained using the conventional PIV approach.

Heat Flux Measurements and Their Uncertainty in a Large-Scale Fire Test

Heat flux data from a series of controlled experiments involving a 2 m diameter, wind-blown pool fire are examined to highlight the difficulties involved in conducting heat flux measurements in a realistic, large-scale, hydrocarbon-fueled fire. Data were taken at several locations along the ground near the fire. At each location, three different heat flux sensors were positioned together: a Gardon gage, a directional flame thermometer (DFT) and a Sandia heat flux gage (HFG). Methods were first developed to correct measured values of heat flux for the slight differences in gage location relative to the fire. The remaining discrepancies between the values of heat flux measured by the different gages were then used to highlight uncertainties in heat flux measurements due to differences in gage surface temperature, in gage thermal response to the inherent modes of heating involved in the large hydrocarbon fire environment, and in conduction losses from the gage sensor plates. The importance of these sources of discrepancy varied depending on the magnitude of the measured heat flux and on whether the gages were located in a radiation-dominated or mixed radiative-convective environment within the fire.

An Evaluation of Methodologies for Determining Delay Times in the Cone Calorimeter Fire Test

An important step in calibrating a cone calorimeter apparatus is the determination of gas delay times. Gas concentration measurements must be made simultaneously in time with the main combustion events and processes (i.e., ignition, changes in mass loss rate, smoke production, and observed phenomena) to produce accurate results from the test. The calibration methodology prescribed in ASTM E1354-14e1 does not specify direct measurement of the transit time of gases through the apparatus or the response time of the individual analyzers, instead estimating total delay time by relating the thermal lag in the stack thermocouple to the transient response of the gas analyzers. Other methods to account for gas delay times are used in practice, leading to varying opinions on the method that is most suitable for oxygen consumption calorimetry. Furthermore, studies have shown that analyzer delay times are not consistent test-to-test, but depend on both the characteristics of the gas analyzer and sampling system (gas transit time) and the rates of production or consumption of gaseous species during a particular test (analyzer response time). In the present work, a methodology was proposed for measuring analyzer delay times by injecting a gas mixture of known concentration into the cone calorimeter exhaust stream. Delay times were computed using various methods, including ASTM E1354 and gas injection, and were evaluated with a series of cone calorimeter tests on various materials. Gas delay times determined by the ASTM E1354 method were found to produce inconsistent results for the cone calorimeter used in this study; results were significantly improved when alternative criteria were applied to the method. The square wave method was found to produce very good results for specimens with heat release rates greater than 3 kW; however, delay times in carbon monoxide production were not well represented. The gas injection method was found to produce excellent results, closely tracking oxygen consumption, carbon monoxide production, and carbon dioxide production in time, and as a result, the derived heat release rate coincided with observed events.

Numerical Simulation of a Pool Fire and Large Object in a Cross-Wind

The present investigation is focused on assessing the capabilities of Large Eddy Simulations (LES) using simplified submodels for combustion and soot in a specific fire scenario. Fire development resulting from an aviation fuel spill close to a plane fuselage is considered. The computational domain and boundary conditions are defined according to the experimental configuration used in tests run by the Fire Research Group at the University of Waterloo. The present setup consists of a 2-m-diameter pool fueled with kerosene and located 1-m-upstream of a 2.7m-diameter culvert in a large enclosure. A cross-wind with a velocity of 13 m/s is imposed on the fire and culvert. The calculations are time-dependent and three-dimensional. Sensitivity to the grid refinement, size of the enclosure and wind profiles is first investigated. Comparison between measured temperatures and numerical results across the computational domain is made. Velocity profiles are also examined. Reasonable agreement with the experiments is found. In the light of the present results, directions for future work are also discussed. INTRODUCTION Accidental release of liquid fuels, either in industrial processes or in transportation systems, can pose a serious fire hazard. Once ignited, the flame spread will be rapid, smoke and toxic products will be released into the surroundings. The difficulties in understanding fire dynamics stem from the all correspondence to this author. 1 complex interactions between fluid motion, combustion, radiation and multiphase flow, which all take place in a turbulent buoyancy-driven environment. This results in a wide range of length scales, from the macroscopic to the molecular level. Fire growth is also strongly affected by external conditions such as wind and the presence of an enclosure for example. Systematic experimental investigations of spill fire scenarios are hindered by financial constraints, sensitivity to environmental conditions and detrimental effect on diagnostic equipment. Numerical simulations provide a promising tool to complement experimental studies and further develop understanding of fire safety and fire physics. At present, the wide range of length and time scales in large fires prohibits the use of three-dimensional direct numerical simulations where the governing equations are directly solved without any closure assumption. Consequently mathematical modelling of the major physical and chemical processes within the fire is still required and remains a challenging task. The present investigation is focused on Large Eddy Simulation (LES) applied to a pool fire in the vicinity of a large object in a crosswind. The experimental and computational configurations aim at reproducing the scenario of fire development from an aviation fuel spill close to a plane fuselage. In LES the large turbulent flow structures are fully resolved and only the dissipation scales require modelling. Flow in the plume region is associated with the large scale structures, and motion of the large eddies are expected to make the most significant contributions to the transport of heat, radiation, chemical species and soot [1]. Copyright c

Measurement of Heat Flux From Fires

Heat flux is an important parameter for characterization of the thermal impact of a fire on its surroundings. However, heat flux cannot be measured directly because it represents the rate of heat transfer to a unit area of surface. Therefore, most heat flux measurements are based on the measurement of temperature changes at or near the surface of interest [1,2]. Some instruments, such as the Gardon gauge [3] and the thermopile [2], measure the temperature difference between a surface and a heat sink. In radiation-dominated environments, this difference in temperature is often assumed to be linearly related to the incident heat flux. Other sensors measure a surface and/or interior temperature and inverse heat conduction methods frequently must be employed to calculate the corresponding heat flux [1,4]. Typical assumptions include one-dimensional conduction heat transfer and negligible heat loss from the surface. The thermal properties of the gauge materials must be known and, since these properties are functions of temperature, the problem often becomes non-linear.Copyright

The Effects of Wind on Liquid Fuelled Pool Fires

Macroscopic fire parameters such as fuel regression rate, flame height and flame tilt are critical to the development of detailed fire models and empirical tools for hazard analysis [1–3]. As a result, these characteristics have been investigated by many researchers using various measurement methods in studies of liquid fuelled pool fires of different diameters and fuel types, under a range of crosswind conditions. In investigations related to transportation accidents, fire scenarios have been complicated further through interactions between the fire and upwind or downwind objects [1,2]. Of particular interest is the determination of fuel regression rate, an important parameter but one that is generally difficult to characterize accurately. Many techniques have been reported for measurement of fuel regression rate. These include load cells [2,4,5], differential pressure systems [2,5–7], sight glass and float-type level meters [6–8] and thermocouple rakes [1]. In general, load cells have been employed most successfully for measurements in smaller scale fires [2,4], while researchers have turned to differential pressure and thermocouple type systems for measurements in fires above 5 m diameter [2,6,7]. All the techniques have been used with varying levels of success to measure fuel regression rate under quiescent conditions. Under crosswind conditions and in cases with an object present, however, inherent wandering of the fire plume and dynamic wind loading on the pool can be of additional concern as they affect the accuracy and repeatability of the measurements [1,2,6,7]. In several excellent reviews, available results have been summarized and used to derive empirical correlations relating overall fire characteristics to fire diameter, fuel type and/or wind velocity [3,9–11].Copyright

Vector Positioning for Cross Correlation PIV

Continuing advances in digital imaging technology stimulate greater interest in applying particle image velocimetry (PIV) over increasingly larger fields of view. Unfortunately when larger fields of view are analyzed, velocity gradients in the image become more localized. In addition, non-uniformities in image illumination and particle number density become more prevalent. These factors, coupled with the requirement that large areas of interest (AOIs) must be employed to measure the full range of velocity, cause degradation of correlation results (i.e. broadening and/or splintering of the cross correlation peak) which leads to positional bias errors in the measured velocity field. More advanced super resolution strategies that employ an iterative AOI reduction process inherently reduce positional bias in PIV results but these strategies can break down in complex flows where velocity gradients are steep and particle dispersion does not remain uniformly random. To mitigate these problems a simple but effective technique is presented that enables individual velocity vectors to be placed within an AOI at locations toward which the cross correlation plane is biased. The method involves analysis of the correlation plane to extract the dominant features that are matched in two successive AOIs. To demonstrate the utility of the methodology results obtained from synthetic images are compared against results obtained using the conventional PIV approach.© 2002 ASME

Assessment of the capabilities of FireFOAM to model large-scale fires in a well-confined and mechanically ventilated multi-compartment structure

This article presents a large eddy simulation study of a pool fire in a well-confined and mechanically ventilated multi-room configuration. The capabilities of FireFOAM are assessed by comparing the numerical results to a well-documented set of experimental data available from Propagation d’un Incendie pour des Scénarios Multi-locaux Elémentaires. The eddy dissipation concept, finite volume discrete ordinate method, and one k-equation model are used for combustion, thermal radiation, and sub-grid scale closure, respectively. The main boundary conditions are imposed based on the experimental profiles. A detailed comparison is made with available experimental data. Good agreement between the large eddy simulation results and experimental values is achieved for temperatures, velocity, CO2 volume concentrations, and pressures for most compartments. There are some noticeable underpredictions of temperature in the outlet room. Overall, FireFOAM is shown to have good predictive capabilities for the present confined large-scale fire scenario.