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The spectral absorptance of the 3.4-[[micro]meter] band of methane, ethane, propane, and butane has been measured with a Fourier transform infrared spectrometer over a range of temperatures from 296 to 900 K. The measurements were made at a 4-[cm.sup.-1] resolution and integrated over the entire band to give the total absorptance. The total absorptance is found to behave in such a way that it can be correlated by a combination of algebraic expressions that depend on the gas temperature and concentration. Average discrepancies between the correlations and the measurements are less than 4%, with maximum differences of no greater than 17%. In addition, the correlations presented here for methane are shown to be in good agreement with established models. Expressions given for the integrated intensity of each gas show an inverse dependence on temperature, reflecting the associated change in density. OCIS codes: 300.0300, 300.1030, 300.6300, 300.6340, 300.6390.

The major factors that impact residential fire losses and casualties are relatively well known both on the national level and for any given state. Interestingly, relatively little has been done in comparing fire loss data between states. If state fire loss data are compared, one should be able to identify contributing factors that influence differences in fire losses between states. As an example, it is known that construction standards, regulatory policy, socio-economic factors, etc. all influence the frequency and severity of fires. In this study, subsets of National Fire Incident Reporting System (NFIRS) data for the two largest US states by population are studied in order to identify how areas of origin, items first ignited, and heat sources contribute to the odds of casualties or fatalities occurring in fires, as well as to examine differences between the two states for these three factors. Data on residential home fires from 2006 to 2010 were gathered from the Texas and California NFIRS databases, Texas Fire Incident Reporting System and California All Incident Reporting System, respectively, for this purpose. Examination of the datasets separately using logistic regression models emphasized that fires started in the living room or den, fires in which the item first ignited was a flammable liquid, piping, or filter, and fires that were initiated from cigarettes, pipes, and cigars, all have significantly high odds of resulting in both casualties and fatalities for both states. Additionally, logistic regression modeling with interactions between state and area of origin, item first ignited, and heat source indicated that for many categories, the odds of a fire resulting in a casualty in Texas is roughly 1.5 times higher than the same fire in California. [ABSTRACT FROM PUBLISHER]

Accurate prediction of the radiative heat transfer is of great importance in simulations of combustion processes. To compute the total radiative transfer, it is necessary to integrate the radiative transfer equation (RTE) over the entire wavelength spectrum, a highly time consuming task that still demands the use of gas models. In this work, a finite volume code is used to simulate a steady-state methane-air diffusion flame. The code solves the equations for the conservation of mass, momentum, individual species and energy. The solution also includes a chemistry model for the formation of soot, which is of major importance in the computation of the radiation heat transfer. The radiation exchanges am computed by the discrete ordinates method, and using two different approaches: the gray gas model and the spectral-line based weighted-sum-of-grays-gases (SLW) model. The results for the temperature distribution, gas species concentration, and soot formation am examined with the two different radiation gas models used. [ABSTRACT FROM AUTHOR]

Stochastic simulations are becoming increasingly important in numerous engineering applications. The solution to the governing equations are complicated due to the high-dimensional spaces and the presence of randomness. In this paper we present (), a software library to solve various types of Stochastic Differential Equations (SDE) as well as estimate statistical distributions from the moments. The library provides a suite of tools to solve various SDEs using the method of moments (MoM) as well as estimate statistical distributions from the moments using moment matching algorithms. For a large class of problems, MoM provide efficient solutions compared with other stochastic simulation techniques such as Monte Carlo (MC). In the physical sciences, the moments of the distribution are usually the primary quantities of interest. The library enables the solution of moment equations derived from a variety of SDEs, with closure using non-standard Gaussian quadrature. In engineering risk assessment and decision making, statistical distributions are required. The library implements tools for fitting the Generalized Lambda Distribution (GLD) with the given moments. The objectives of this paper are (1) to briefly outline the theory behind moment methods for solving SDEs/estimation of statistical distributions; (2) describe the organization of the software and user interfaces; (3) discuss use of standard software engineering tools for regression testing, aid collaboration, distribution and further development. A number of representative examples of the use of in various engineering applications are presented and future areas of research are discussed. [ABSTRACT FROM AUTHOR]

Accurate measurement of surface temperature distribution is of concern in the semiconductor industries, particularly in rapid thermal processing. The International Technology Roadmap for Semiconductors 2004 has established requirements of uncertainties of ± 1.5 °C at a temperature of 1000 °C, with temperature calibration traceable to ITS-90 (International Temperature Scale-1990). Light-pipe radiation thermometers (LPRTs) are becoming increasingly important as an industrial tool for temperature measurement, especially in the semiconductor industry. However, achieving improved accuracy will be difficult without fully understanding several issues associated with LPRTs. In this paper, the "drawdown effect," the "shadow effect," and the "environmental effect" are investigated. The drawdown effect is caused by the physical mass of the light-pipe probe acting as a radiation heat sink for the measured object. The shadow effect is caused by distortion of the wafer radiosity distribution due to the presence of the light-pipe probe. The environmental effect is caused by nonspecular reflection due to surface imperfection or impurity of the light-pipe material. Monte Carlo simulation was conducted to better understand the underlying physics, and the simulation results are compared to the experiment results. The latter two effects were found to be very important in the present study. [ABSTRACT FROM AUTHOR]

The directional flame thermometer (DFT) is a device used to measure radiative heat flux in fire scenarios. In many DFT applications, radiation is the dominant mode of heat transfer and convection does not significantly affect radiative heat flux predictions. However, at higher air velocities, neglecting convection causes error in heat flux predictions. This study explores the error caused by ignoring forced convection in heat flux predictions and proposes a method to reduce it. To accomplish this, a forward heat transfer model is used to generate synthetic temperature data for the DFT given radiative and convective conditions. Using the forward model and an existing inverse model, this study shows that assuming natural convection is the only mode of convective heat transfer leads to significant error in the predicted radiative heat flux. To reduce this error, this work proposes a framework for recovering the heat transfer coefficient and radiative heat flux in forced convection conditions. The framework utilizes an additional thermocouple above the plate of the DFT. The framework performed poorly for simulations in which the temperature of the air stream and that of the thermocouple was lower than 15 ∘ C. Omitting simulations where this condition holds, on average, using the framework under constant heat flux and constant characteristic air velocity conditions reduces the error in the predicted heat flux by a factor of 12 compared to when the heat flux is predicted assuming that natural convection is the only mode of convection. A simple experimental test was conducted to validate the computational framework. [ABSTRACT FROM AUTHOR]

A compartment fire (a fire in a room or building) creates temperature gradients and inhomogeneous time-varying temperature, density, and flow fields. This work compared experimental measurements of the room acoustic impulse/frequency response in a room with a fire to numerically modeled responses. The fire is modeled using a Fire Dynamics Simulator (FDS). Acoustic modeling was performed using the temperature field computed by FDS. Room acoustics were modeled using two-dimensional ray and finite element modeling. A three-dimensional model was used to simulate an open flame. COMSOLTM Multiphysics was used for finite element acoustic modeling and BELLHOPTM for ray trace acoustics modeling. The results show that the fire causes wave-fronts to arrive earlier (due to the higher sound speed) and with more variation in the delay times (due to the sound speed perturbations). The resonance frequencies of low-frequency modes were shifted upwards. Model results are compared with data and show good agreement in observed trends. [ABSTRACT FROM AUTHOR]

In fire hazard calculations, knowledge of the heat-release rate (HRR) of a burning item is imperative. Typically, room-scale calorimetry is conducted to determine the HRRs of common combustible items. However, this process can be prohibitively expensive. In this work, a method is proposed to invert for the HRR of a single item burning in a room using transient heat flux measurements at the walls and ceiling near the item. The primary device used to measure heat flux is the directional flame thermometer (DFT). The utility of the inverse method is explored on both synthetically generated and experimental data using two so-called forward models in the inversion algorithm: fire dynamics simulator (FDS) and the consolidated model of fire and smoke transport (CFAST). The fires in this work have peak HRRs ranging from 200 kW to 400 kW. It was found that FDS outperformed CFAST as a forward model at the expense of increased computational cost and that the error in the inverse reconstruction of a 400 kW steady fire was on par with room-scale oxygen consumption calorimetry. [ABSTRACT FROM AUTHOR]

The Personal Alert Safety System (PASS) is an alarm signal device carried by firefighters to help rescuers locate and extricate downed firefighters. A fire creates temperature gradients and inhomogeneous time-varying temperature, density, and flow fields that modify the acoustic properties of a room. To understand the effect of the fire on an alarm signal, experimental measurements of head-related transfer functions (HRTF) in a room with fire are presented in time and frequency domains. The results show that low-frequency (<1000 Hz) modes in the HRTF increase in frequency and higher-frequency modal structure weakens and becomes unstable in time. In the time domain, the time difference of arrival between the ears changes and becomes unstable over time. Both of these effects could impact alarm signal detection and localization. The receive level of narrowband tones is presented that shows that the fire makes the receive level of a source vary by > 10 dB. All of these effects could impact the detection and localization of the PASS alarm and have life safety consequences. [ABSTRACT FROM AUTHOR]

This paper presents a model‐based study of the impact of implementing radiant (radiation‐dominated) concentric‐tube recuperators on fuel use in an indirectly‐fired industrial heat treating (austenitization/quench hardening) furnace. The recuperators recover some of the waste heat from the burner exhaust to preheat the inlet air to the burners, thus reducing the amount of fuel required for combustion. The novelty of this work consists of developing a physics‐based model of a recuperator, which captures local gas‐to‐surface convective heat transfer and long‐range surface‐to‐surface radiation interactions, and using the model to analyze and optimize the energy use of the furnace. An iterative algorithm is proposed to solve the poorly‐conditioned energy balance equations. The steady‐state system operation is optimized using surrogate models. Extensive simulation studies demonstrate that heat integration reduces fuel consumption significantly without affecting product quality. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16414 2019 [ABSTRACT FROM AUTHOR]

Fire forensic investigators are challenged to determine in what scenarios can lithium ion batteries initiate a fire, and what post-fire signatures exist to determine if the battery was more likely the cause of the fire or a victim of the fire. Towards this goal, this study experimentally characterizes the ignition characteristics of cylindrical format 18650 cells and the post-failure properties of the cells. First, failure tests of individual 18650 cell were used to quantify the temperature of vented gases and heat fluxes from these gases to cold objects for battery thermal failure at various states-of-charge (SOC) in either inert or normal oxygen environments. Experiments were then conducted with 18650 cells failed on composite cushion materials to evaluate how failures from different SOC cells ignite common fabric materials. Finally, laptop tests were conducted to investigate the effect of a common appliance package on the propagation of individual cell thermal runaway within the power bank of a common laptop configuration. The experimental results show that in the event of a thermal runaway, batteries can either explode or release a jet flame. The ignition behavior of fabric materials varies with varying SOCs with more vigorous ignition occurring at larger SOC. It was observed that the final mass of failed batteries is lower for higher SOC cells. Finally, propagation of thermal runaway inside a laptop power bank can be facilitated by having the failure take place at the center location of the power bank and can be hindered if the SOC is sufficiently low. [ABSTRACT FROM AUTHOR]

Characterizing propagation of a thermal runaway hazard in cell arrays and modules is critical to understanding fire hazards in energy storage systems. In this paper, the thermal runaway propagation of a pouch cell array has been examined by developing a 1D finite difference model. The results are compared with experimental data. First, the thermal runaway reactions found in the literature are reviewed. Using the insight of the literature review and premixed flame propagation theory, a global first order Arrhenius type reaction is characterized. While applying the multiple kinetic reactions, an "onset temperature" of the combustion reactions has been determined by performing an induction time analysis on ethylene. The propagation speeds are predicted with a 1D finite difference model by using both multi-reaction kinetics and one step reduced-order kinetics. These results are in a good agreement with experiments for both 10 Ah and 5 Ah cell arrays. [ABSTRACT FROM AUTHOR]

A room fire creates temperature gradients and inhomogeneous time varying temperature, density, and flow fields. Experimental measurements of the room acoustic impulse/frequency response are presented and compared with a ray traced model. The results show that the fire causes wave-fronts to arrive earlier (due to the higher sound speed) and with more variation in the delay times (due to the sound speed perturbations). The frequency response shows that the modes are shifted up in frequency and high frequency (>2500 Hz) modes are significantly attenuated. Model results are compared with data and show good agreement in observed trends. [ABSTRACT FROM AUTHOR]

Towards the development of a more rigorous approach for coupling collected fire scene data to computational tools, a Bayesian computational strategy is presented in this work. The Bayesian inversion technique is exercised on synthetic, time-integrated data to invert for the location, size, and time-to-peak of an unknown fire using two well-known forward models; Consolidated Model of Fire and Smoke Transport (CFAST) and Fire Dynamics Simulator (FDS). A Gaussian process surrogate model was fit to coarse FDS simulations to facilitate Markov Chain Monte Carlo sampling. The inversion framework was able to predict the total energy release by all fire cases except for one CFAST forward model, a 1000 kW steady fire. It was found that insufficient information was available in the time-integrated data to distinguish the temporal variations in peak times. FDS performed better than CFAST in predicting the maximum energy release rate with the posterior mean of the best configurations being 0.05% and 2.77% of the true values respectively. Both models performed equally well on locating the fire in a compartment. [ABSTRACT FROM AUTHOR]

• Multi-component reactants and products are considered to be close to real fires. • Multi-component pyrolysis and combustion model are built up in FireFOAM. • The experimental data of TG-FTIR are coupled directly to combustion. • The predicted results agree well with experimental data of cone calorimetry. The direct combustion of typical charring material, with wood as the main representative, has received extensive attention due to its potential as sustainable source of heat and power generation, and the substantial fraction of fuel load in many building fires. In real fire situations, multi-component condensed phase reactants and gas products are involved in the pyrolysis process and the subsequent combustion process. Interestingly, the numerical simulation of these multi-component reactions is relatively not yet well studied. To address this shortcoming, we consider how the reactants can be dealt with using a three-component parallel reaction mechanism and moisture model embedded into the pyrolysis model, wherein the reaction kinetic parameters are optimized by Shuffled Complex Evolution algorithm. The evolved gas products, measured by the TG-FTIR experiment, can be coupled with the extended EDC multi-component combustion model and soot model using FireFOAM. Most of the thermophysical parameters are measured directly by experiments as the input values of simulation. In this work, the predicted results of mass loss rate and heat release rate are compared with experimental data of cone calorimetry, and the good agreement between them validates the applicability of the current multi-component model. Moreover, the effects of three sub-models (three-component parallel reaction mechanism, multiple evolved gas products and the extended EDC multi-component combustion model) are further analyzed based upon the predicted results. [ABSTRACT FROM AUTHOR]