A. James Clark School of Engineering
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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Pyrolysis Model Development for a Multilayer Floor Covering(MDPI, 2015-09-14) McKinnon, Mark B.; Stoliarov, Stanislav I.Comprehensive pyrolysis models that are integral to computational fire codes have improved significantly over the past decade as the demand for improved predictive capabilities has increased. High fidelity pyrolysis models may improve the design of engineered materials for better fire response, the design of the built environment, and may be used in forensic investigations of fire events. A major limitation to widespread use of comprehensive pyrolysis models is the large number of parameters required to fully define a material and the lack of effective methodologies for measurement of these parameters, especially for complex materials. The work presented here details a methodology used to characterize the pyrolysis of a low-pile carpet tile, an engineered composite material that is common in commercial and institutional occupancies. The studied material includes three distinct layers of varying composition and physical structure. The methodology utilized a comprehensive pyrolysis model (ThermaKin) to conduct inverse analyses on data collected through several experimental techniques. Each layer of the composite was individually parameterized to identify its contribution to the overall response of the composite. The set of properties measured to define the carpet composite were validated against mass loss rate curves collected at conditions outside the range of calibration conditions to demonstrate the predictive capabilities of the model. The mean error between the predicted curve and the mean experimental mass loss rate curve was calculated as approximately 20% on average for heat fluxes ranging from 30 to 70 kW·m−2, which is within the mean experimental uncertainty.Item A Generalized Methodology to Characterize Composite Materials for Pyrolysis Models(2016) McKinnon, Mark; Stoliarov, Stanislav I; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The predictive capabilities of computational fire models have improved in recent years such that models have become an integral part of many research efforts. Models improve the understanding of the fire risk of materials and may decrease the number of expensive experiments required to assess the fire hazard of a specific material or designed space. A critical component of a predictive fire model is the pyrolysis sub-model that provides a mathematical representation of the rate of gaseous fuel production from condensed phase fuels given a heat flux incident to the material surface. The modern, comprehensive pyrolysis sub-models that are common today require the definition of many model parameters to accurately represent the physical description of materials that are ubiquitous in the built environment. Coupled with the increase in the number of parameters required to accurately represent the pyrolysis of materials is the increasing prevalence in the built environment of engineered composite materials that have never been measured or modeled. The motivation behind this project is to develop a systematic, generalized methodology to determine the requisite parameters to generate pyrolysis models with predictive capabilities for layered composite materials that are common in industrial and commercial applications. This methodology has been applied to four common composites in this work that exhibit a range of material structures and component materials. The methodology utilizes a multi-scale experimental approach in which each test is designed to isolate and determine a specific subset of the parameters required to define a material in the model. Data collected in simultaneous thermogravimetry and differential scanning calorimetry experiments were analyzed to determine the reaction kinetics, thermodynamic properties, and energetics of decomposition for each component of the composite. Data collected in microscale combustion calorimetry experiments were analyzed to determine the heats of complete combustion of the volatiles produced in each reaction. Inverse analyses were conducted on sample temperature data collected in bench-scale tests to determine the thermal transport parameters of each component through degradation. Simulations of quasi-one-dimensional bench-scale gasification tests generated from the resultant models using the ThermaKin modeling environment were compared to experimental data to independently validate the models.Item Gasification and Combustion of Large Char Particles and Tar(2015) Molintas, Henry; Gupta, Ashwani K; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Although diffusion is known to play an important role for gasification and combustion of large char particles, their effects on conversion rates, kinetic parameters and other relevant factors have not been thoroughly analyzed. Similarly, tar reduction is not yet well understood. Central to these challenges is the shortage of experimental data for reduction of tar and large char particles. Likewise, analytical models for reduction processes have not been systematically examined. In this study, large char particles between 1.5 to 7 mm are gasified and combusted non-isothermally with initial temperatures up to 1000 degree celcius using various oxidants. Tar is also reduced with steam and vitiated air continuously and non-isothermally. In the absence of mathematical tools for large particle reduction analysis, models are proposed and derived in this study. Carbon and large near-spherically or irregularly shaped particles are modeled as large disk-shaped and spherically-shaped particles, respectively. One-film ash segregated core and random pore models are explored to analyze char reduction data and these are found to provide consistent and inconsistent results, respectively. Thiele analysis is also used and it indicates that less porous particles are consumed more externally at the surface than internally. For C + O2⇒ CO2 reductions, disk-shaped particles ignite when reactor temperature reaches 584 degree and these processes are purely kinetic controlled for 1.5 mm thick samples. Reduction of spherically-shaped particles shows that O2 enrichment as compared to a 50 degree celcius rise in reactor temperature substantially improves conversion. Oxygen enrichment with steam also significantly increases conversion of 5.5 mm thick disk-shaped particle up to 600 % under identical reactor conditions. For C + CO2⇒2CO reductions, conversion rates increased five-fold when reactor temperature is increased from 850 to 1000 degree Celsius. Increasing initial reactor temperatures and O2 enrichment provide an increase in char reactivity, diffusional rate, conversion, reduction rate and surface temperature. Most of the large particle reductions investigated here operate near kinetic-diffusion controlled regime. Calculated total energy released during combustion is within the range of Dulong’s empirical formula. At higher tar concentrations, CO and H2 production moderately increase between 814 to 875 degree celsius.Item Design and Analysis of New Gasification Apparatus based on the Standard Cone Calorimeter(2012) Liu, Xuan; Stoliarov, Stanislav I; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A simple, inexpensive, safe version of pyrolysis apparatus is developed base on the standard cone calorimeter (ASTM E 1354). A controllable oxygen concentration (0% to 21% by volume) environment in the vicinity of 80 mm by 80 mm square sample positioned under the cone radiant heater is achieved by means of "Controlled Atmosphere Pyrolysis Apparatus". Valid gasification mass loss rate measurements have been obtained for both poly(methyl methacrylate) (PMMA) and polypropylene (PP) samples under external heat fluxes of 35kW/m^2 and 50kW/m^2. Reasonable value of thermal conductivity for PMMA is measured. With the thermal conductivity and parameters defined by Differential Scanning Calorimeter (DSC) of PMMA, the gasification mass loss rate is well simulated using Thermo-Kinetic Model of Burning (ThermaKin).