No description available.

No description available.

"This study considers the flammability hazard associated with the pouring of gasoline from a portable gasoline container (PGC) in an area containing a potential ignition source. In this scenario a flame may propagate into the PGC and cause an explosion if a flammable environment exists along the length of the pour spout and into the PGC headspace. In order to quantify this hazard, experiments are conducted to measure the flammable vapor concentration within this area under various conditions of temperature, liquid volume, and container pour angle. It is found that liquid fuel volumes as high as 30 mL in a 5-gallon PGC are capable of producing a flammable vapors within the PGC headspace. Finally, a mathematical model is presented to predict the flammability hazard under various conditions."

Flammability limit is a significant safety issue for industrial processes. A certain amount of flammability limit data for pure hydrocarbons are available in the literature, but for industrial applications, there are conditions including different combinations of fuels at standard and non-standard conditions, in which the flammability limit data are scarce and sometimes unavailable. This research is two-fold: (i) Performing experimental measurements to estimate the lower flammability limits and upper flammability limits of binary hydrocarbon mixtures, conducting experimental data numerical analysis to quantitatively characterize the flammability limits of these mixtures with parameters, such as component compositions, flammability properties of pure hydrocarbons, and thermo-kinetic values; (ii) Estimating flammability limits of binary hydrocarbon mixtures through CFT-V modeling prediction (calculated flame temperature at constant volume), which is based on a comprehensive consideration of energy conservation. For the experimental part, thermal detection was used in this experiment. The experimental results indicate that the experimental results fit Le Chatelier’s Law within experimental uncertainty at the lower flammability limit condition. At the upper flammability limit condition, Le Chatelier’s Law roughly fits the saturated hydrocarbon mixture data, while with mixtures that contain one or more unsaturated components, a modification of Le Chatelier’s is preferred to fit the experimental data. The easy and efficient way to modify Le Chatelier’s Law is to power the molar percentage concentrations of hydrocarbon components. For modeling prediction part, the CFT-V modeling is an extended modification of CAFT modeling at constant volume and is significantly related to the reaction vessel configuration. This modeling prediction is consistent with experimental observation and Le Chatelier’s Law at the concentrations of lower flammability limits. When the quenching effect is negligible, this model can be simplified by ignoring heat loss from the reaction vessel to the external surroundings. Specifically, when the total mole changes in chemical reactions can be neglected and the quenching effect is small, CFTV modeling can be simplified to CAFT modeling.

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No description available.

The research focuses on the critical review and prediction of flash points of high molecular weight compounds used mainly in the specialty chemical area. Thus far this area of high molecular weight specialty chemicals has not been thoroughly reviewed for flash point prediction; therefore critical review for accuracy of experimental values is difficult. Without critical review, the chance of hazards occurring in the processing and handling of these compounds increases. A reliable method for making predictions is important to efficiently review experimental values since duplicate experimentation can be time consuming and costly. The flash point is strongly correlated to the normal boiling point (NBP) but experimental NBP is not feasible for chemicals of high molecular weight. The reliability of existing NBP prediction methods was found inadequate for our compounds of interest therefore a new NBP prediction method was developed first. This method is based on ten simple group contributions and the molecular weight of the molecule. The training set included 196 high molecular weight C, H, N and O compounds. It produced an average absolute error (AAE) of 13K, superior to any other model tested so far. An accurate NBP is essential for critical review and new method development for flash point. A preliminary data analysis based on chemical family analysis allowed for detection of erroneous data points. These compounds were re-tested at a Huntsman facility. With a predicted normal boiling point, a new FP method that differentiates strong and iv weak hydrogen bonding compounds was developed. This was done because of the differences in entropy of vaporization for hydrogen bonding compounds. The training set consisted of 191 diverse C, H, N, O compounds ranging from 100 to 4000 g/mol in molecular weight. The test set consisted of 97 compounds of similar diversity. Both data sets produced an AAE of 5K and maximum deviation of 17.5K. It was also found that no substantial decomposition was found for these compounds at flash point conditions. These compounds appear to follow the same physical trends as lower molecular weight compounds. With this new method it is possible to critically review this class of chemicals as well as update NBP and other physical property data. / PDF file replaced 4-20-2012 at request of Thesis Office.

Flammability limit is a most significant property of substances to ensure safety of chemical processes and fuel application. Although there are numerous flammability literature data available for pure substances, for fuel mixtures these are not always available. Especially, for fuel mixture storage, operation, and transportation, inert gas inerting and blanketing have been widely applied in chemical process industries while the related date are even more scarce. Lower and upper flammability limits of hydrocarbon mixtures in air with and without additional nitrogen were measured in this research. Typically, the fuel mixture lower flammability limit almost keeps constant at different contents of added nitrogen. The fuel mixture upper flammability limit approximately linearly varies with the added nitrogen except mixtures containing ethylene. The minimum added nitrogen concentration at which lower flammability limit and upper flammability limit merge together is the minimum inerting concentration for nitrogen, roughly falling into the range of 45 plus/minus 10 vol % for all the tested hydrocarbon mixtures. Numerical analysis of inert gas dilution effect on lower flammability limit and upper flammability limit was conducted by introducing the parameter of inert gas dilution coefficient. Fuel mixture flammability limit can be quantitatively characterized using inert gas dilution coefficient plus the original Le Chatelier's law or modified Le Chatelier's law. An extended application of calculated adiabatic flame temperature modeling was proposed to predict fuel mixture flammability limits at different inert gas loading. The modeling lower flammability limit results can represent experimental data well except the flammability nose zone close to minimum inerting concentration. Le Chatelier's law is a well-recognized mixing rule for fuel mixture flammability limit estimation. Its application, unfortunately, is limited to lower flammability limit for accurate purpose. Here, firstly a detailed derivation was conducted on lower flammability limit to shed a light on the inherent principle residing in this rule, and then its application was evaluated at non-ambient conditions, as well as fuel mixture diluted with inert gases and varied oxygen concentrations. Results showed that this law can be extended to all these conditions.

Recent outbreaks of mountain pine beetle (Dendroctonus ponderosae Hopkins) in lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forests and spruce beetle (Dendroctonus rufipennis Kirby) in Engelmann spruce (Picea engelmannii Parry ex Engelm.) forests have affected vast areas across western North America. The highlevels of tree mortality associated with these outbreaks have raised concerns amongst fire managers and wildland firefighters about the effects of the tree mortality on fire behavior, particularly crown fire behavior, as crown fires hinder the ability of firefighters to conduct safe and effective fire suppression operations. Current information regarding crown fire dynamics in recently attacked forests is limited to results obtained from simulations employing either inappropriate and/or unvalidated fire behavior models based on inadequate descriptions of crown fuel flammability. The purpose of this research was to measure and characterize the changes in crown fuel flammability caused y recent bark beetle attack and to describe the implications of these changes on crown fire potential in affected forests. Results indicated that bark beetle attack causes a significant decline in moisture content and change in chemical composition in lodgepole pine and Engelmann spruce tree foliage, which substantially increases foliage flammability. Additionally, it was found that conventional models used to predict the moisture content of fine, dead surface fuels were inappropriate for predicting the moisture content of foliage on mountain pine beetle-attacked lodgepole pine trees during the red stage. Therefore, calibrated operational models and models based on diffusion theory were developed and evaluated that could accurately predict hourly fluctuations in moisture content. The implications of these changes on crown fire potential are dependent upon a host of site specific factors including outbreak duration, severity, and the specific stand characteristics. Based on our results, we believe that current fire behavior models, including popular semi-empirical and physics-based models, are currently inadequate for accurately predicting crown fire potential in forests recently attacked by bark beetles. In order to make significant progress in our understanding of crown fire potential in recently attacked forests, a substantial effort to document wildfire behavior in the field and/or to conduct experimental fires is needed.

The Design Institute for Physical Properties (DIPPR) maintains the DIPPR 801 database for the American Institute of Chemical Engineers. Autoignition temperature (AIT) is one of the properties included in the database and is the focus of this work including improvement of the overall state of AIT in the database. Phenomena related to AIT as well as the relevant literature are reviewed. Likewise, the database is presented to respond to significant misuse of the DIPPR 801 database in the literature. The database is evaluated, respecting AIT, as a whole to show where improvement is needed. An experimental study of minimum autoignition temperatures reveals unexpected behavior of pure n-alkanes not predicted by current current phenomenological understanding of autoignition processes. Measurements show an increase at C16 and a dramatic and previously unexplained step increase between C25 and C26. Experimental modifications are presented to compensate the effect of altitude. Measured values for several n-alkanes are reported and compared to the literature. Other ignition experiments and decomposition measurements using differential scanning calorimetry are also reported and examined to elucidate the unexpected trends. Explanations for these trends are proposed. Finally, the implications of this for trends in other chemical families are discussed. A comprehensive examination of AIT family trends reveals variation from the n-alkane family trend. Measured AIT values are presented and discussed. Evaluated AIT values are recommended for several single-group chemical families. Phenomenological explanations for observed differences are proposed and discussed along with the broader implications for these trends. Methods for predicting autoignition temperatures (AIT) have been historically inaccurate and are rarely based on the underlying physical phenomena leading to observed AIT. An improved method for predicting AIT based on the method by the late Dr. William H. Seaton is presented and discussed. The method of Seaton is described in detail. An evaluated data set is used to regress new parameters for the Seaton method parameters. Improvements to Seaton's model and underlying principles are presented and discussed. Finally, an improved AIT prediction method is presented and recommended.