<p dir="ltr">Fires cause significant casualties and property damage. As critical component of indoor and building fires, fires along a surface (vertical or horizontal) contribute significantly to fire spreading and resulted damage. Accurately predicting the interactions between a wall surface and fire is crucial to minimizing losses. Computational methods, such as large-eddy simulations (LES), can result in errors in fire modeling along a surface due to various model and numerical errors among which the error in the convective wall heat transfer models is an important source. The convective heat transfer model error grows when the grid resolution near a thermal boundary layer along a wall surface decreases. Traditional wall-function based heat transfer models, mostly developed for forced convection heat transfer problems, tend to fail in the buoyancy-driven fire wall heat transfer. It is imperative to develop accurate and efficient convective wall heat transfer models for fire modeling.</p><p dir="ltr">In this study, machine learning is employed as an alternative to traditional physics-based modeling approach for wall heat transfer in fire modeling. A significant advantage of machine learning over physics-based modeling is that machine learning does not require thorough knowledge of fire wall heat transfer which is generally hard to acquire due to the complexity of the problem. A machine-learning assisted convective wall heat transfer model, aiming to enhance wall fire predictions, is developed in this work. The objective is to improve predictions of convective heat flux to a wall in under-resolved LES of wall fires. An amplification factor ($\beta$) is introduced to compensate the under-prediction of temperature gradients normal to a wall surface in coarse grid simulations. Machine learning is then employed to assist the construction of models for $\beta$ with the training data obtained directly from fine-resolution LES. Extensive studies are conducted to identify suitable machine learning architecture, input features, training data generation strategies, training procedure, and testing and validation approaches.</p><p dir="ltr">A vertical wall fire test case is considered first to develop a baseline machine learning model. The focus is on identifying suitable input features and training strategies for machine learning of convective wall fire heat transfer. A four-parameter (input) machine learning model for $\beta$ is constructed. Both \textit{a priori} and \textit{a posteriori} testing are developed in the vertical wall fire case to provide preliminary model performance assessment. The fully tested model is also examined in an intermediate-scale parallel-wall fire spreading case that was not seen in the model training to assess the applicability of the developed machine learning model. In general, excellent model performance is observed in the vertical wall fire case.</p><p dir="ltr">The established machine learning approach for the vertical wall case is then extended to horizontal surfaces like floor fires and ceiling fires to expand the training scope of the machine learning model. The unique challenges in these new fire scenarios are investigated separately to identify the need of additional input features and training strategies. It is found that a fifth input parameter, in addition to the four parameters identified in the vertical wall, is generally needed in order to correctly identify different fire scenarios. Data augmentation techniques are also found to be a useful technique to handle data sparsity during model training. Different machine learning architectures like random forest and deep neural network are also compared.</p><p dir="ltr">The above studies are finally integrated into a unified machine learning model suitable for both vertical and horizontal surfaces. Extensive testing shows that the unified model reproduces the model performance of the separately trained models. The work is significant in demonstrating the feasibility of using machine learning approaches to enhance fire simulations. The developed machine learning modeling techniques improve predictions in various fire scenarios by using relatively coarse grid to maintain low computational cost, a critical consideration when simulation approaches are employed in real fire simulations.</p>

Fire is an important disturbance mechanism in big sagebrush (Artemisia tridentata) communities, yet little is known about wildlife population dynamics during post-fire habitat succession. I estimated the abundance of small mammals and birds in relation to fire history in mountain big sagebrush (A.t. spp. vaseyana) communities on the Sheldon National Wildlife Refuge in the northwestern Great Basin, USA. I employed a chronosequence approach that took advantage of multiple wildfires that had occurred in similar plant communities between 7 to 20 years prior to sampling. Belding’s ground squirrel (Spermophilus beldingii) were approximately 10 times as abundant in burned areas relative to adjacent unburned habitat regardless of the number of years since a burn occurred. Deer mouse (Peromyscus maniculatus) was more abundant on more recently burned sites, but not at sites closer to full vegetation recovery. Great basin pocket mouse (Perognathus parvus), sagebrush vole (Lemmiscus curtatus), and least chipmunk (Tamius minimus) abundance did not vary as a function of fire history, but some variance was explained by habitat features such as rocky areas and the canopy characteristics of sagebrush. Bird diversity was higher in unburned habitats irrespective of the number of years of recovery out to 20 years. Nine of the 12 most widely occurring species of birds in the study have population densities influenced by fire or post-fire habitat succession to at least 13 to 20 years following a burn. Sage Sparrow (Amphispiza belli), Black-throated Sparrow (Amphispiza bilineata), and Spotted Towhee (Pipilo maculatus) occurred at relatively low densities and were nearly restricted to unburned habitats. Green-tailed Towhee (Pipilo Chlorurus), Gray Flycatcher (Empidonax wrightii), American Robin (Turdus migratorius), and Brown-headed Cowbird (Molothus ater) occurred at lower densities in burned areas than adjacent unburned areas although the relationship was not strong for the latter two species. The magnitude of the difference in density between burned and unburned sites within a landscape diminished with the number of years of vegetation recovery for Green-tailed Towhee. Brewer’s Sparrow (Spizella brewerii) occurred at lower densities relative to adjacent habitat in the most recent burn, but occurred at higher densities after 20 years of habitat succession, suggesting a positive response with a multiple decade lag period. Horned Lark (Eremophila alpestris) and Vesper Sparrow (Pooecetes gramineus) respond positively to fire, but densities were similar to unburned areas after 20 years of habitat succession. An ordination analysis captured 86% of the variation in 12 bird species with 3 orthogonal axes. My research demonstrates that strong community structure exists for birds associated with mountain big sagebrush habitats, and that fire influences community structure for multiple decades. / Graduation date: 2011 / Access restricted to the OSU Community at author's request from Dec. 22, 2010 - Dec. 22, 2011.

An understanding of compartment fire behaviour is important for fire protection engineers. For design purposes, whether to use a prescriptive code or performance based design, life safety and property protection issues are required to be assessed. The use of design fires in computer modelling is the general method to determine fire safety. However these computer models are generally limited to the input of one design fire, with consideration of the complex interaction between fuel packages and the compartment environment being simplified. Of particular interest is the Heat Release Rate, HRR, as this is the commonly prescribed design parameter for fire modelling. If the HRR is not accurate then it can be subsequently argued that the design scenario may be flawed. Therefore the selection of the most appropriate fire design scenario is critical, and an increased level of understanding of compartment behaviour is an invaluable aid to fire engineering assumptions. This thesis details an experimental study to enhance the understanding of the impact and interaction that the size and location of pool fires within an enclosure have upon the compartment fire behaviour. Thirty four experiments were conducted in a reduced scale compartment (½ height) with dimensions of 3.6m long by 2.4m wide by 1.2m high using five typical ventilation geometries (fully open, soffit, door, window and small window). Heptane pool fires were used, located in permutations of three evenly distributed locations within the compartment (rear, centre and front) as well as larger equivalent area pans located only in the centre. This thesis describes the experimental development, setup and results of the experimental study. To assist in the classification of compartment fire behaviour during the experiments, a ‘phi’ meter was developed to measure the time dependent equivalence ratio. The phi meter was developed and configured to measure O₂, CO₂ and CO. The background development, calibration, and experimental results are reported. A review of compartment fire modelling using Fire Dynamics Simulator, has also been completed and the results discussed. The results of this experimental study were found to have significant implications for Fire Safety Engineering in that the size of the fire is not as significant as the location of the fire. The effect of a fire near the vent opening was found to have a significant impact on compartment fire behaviour with the vent located fuel source increasing the total compartment heat release rate by a factor of 1.7 to that of a centrally placed pool fire of the same total fuel area. The assumption that a fire located in the centre of the room provides for the highest heat release rate is not valid for post-flashover compartment fires. The phi meter was found to provide good agreement with the equivalence ratio calculated from total compartment mass loss rates, and the results of FDS modelling indicate that the use of the model in its current form can not be applied to complex pool fire geometries.

This thesis presents the development and evaluation of a 2D simulation model designed to predict the spread and behavior of forest fires, with a specific focus on Swedish forest ecosystems. Despite the model's simplicity and inherent limitations due to assumptions such as homogeneity in fuel distribution and the exclusion of topographical influences, the simulations yield remarkably accurate predictions of fire spread and intensity. The model integrates basic meteorological data (wind speed and direction, temperature) and uses a discretized spatial approach to simulate the dynamics of forest fires. Initial results suggest that even with minimal input variables and broad assumptions, the model offers significant predictive capabilities, highlighting potential areas for future refinement. Key aspects such as the interaction between conduction and advection terms, the role of water vaporization in fire dynamics, and the influence of wind on fire propagation are discussed. The findings encourage further development of the model, aiming at incorporating more complex variables such as topography and more forest fuels, potentially enhancing its utility in real-time fire management and decision-making processes.

Thesis (DSc)--Stellenbosch University, 2008. / ENGLISH ABSTRACT: No abstract available / AFRIKAANSE OPSOMMING: Geen opsomming beskikbaar

The purpose of this study has been to test public perceptions of both scenic quality and recreational acceptability of southwestern ponderosa pine forests exibiting one-to-five years of recovery from both light and severe fire. Public fire-effects information documents were also constructed and tested. Appropriate ponderosa forest areas in Arizona were selected and randomly photographed. Population samples, drawn from Tucson, Arizona, first read fire-ecology or "control" information brochures and then rated forest scenes on 1-to-10 scales for scenic quality and for acceptability for selected forms of outdoor recreation. Respondents finally answered a short fire-knowledge, fire-attitude questionnaire. Ratings were subjected to SBE analysis (Daniel and Boster, 1976), and analysis of variance was applied to both ratings and questionnaire results. The clearest distinction drawn, for both scenic quality and recreational acceptability, is between light-fire and severe-fire effects. Light fire improves scenic quality for a 3-to-4 year period, while severe fire seriously detracts from scenic quality for an unknown length of time exceeding the 5-year period tested. Recreational acceptability is differentiated according to the recreational activity selected: camping is nearly twice as sensitive to severe fire effects as scenic quality, and is somewhat disrupted by light fire effects; picnicking is second-most impacted by severe fire effects; hiking or backpacking is affected by severe fire to about the same degree as scenic quality; nature study is least affected. Picnicking, hiking and nature study are not significantly affected by light fire. Provision of fire-effects information does not significantly affect scenic or recreational evaluation of forest burn areas. The fire-effects information brochures produced general "halo" effects on both fire knowledge and fire attitude in the groups sampled. Fire knowledge shifted toward the expert position that fire effects are less severe than generally believed. Fire attitude shifted toward the expert position of greater tolerance for fire in ponderosa ecosystems. Results show prescribed burning as generally acceptable. The results of this study demonstrate distinctions between affect (perceptual evaluations) and cognition (questionnaire response). Scenic and recreational evaluations emerge as clearly distinct entities.

An accurate fire model is a useful tool in predicting the behavior of a prescribed fire. Simulation of fire requires an extensive amount of data and can be accomplished best using GIS applications. This paper demonstrates integrative procedures of using of ArcGIS™, ERDAS Imagine™, GPS, and FARSITE© to predict prescribed fire behavior on the Kaibab-Paiute Reservation. ArcGIS was used to create a database incorporating all variables into a common spatial reference system and format for the FARSITE model. ArcGIS Spatial Analyst was then used to select optimal burn sites for simulation. Our predictions will be implemented in future interagency efforts towards vegetative restoration on the reservation.

Il est bien établi que l'exposition à court terme aux particules fines dans l’air ambiant en milieu urbain a des effets sur la santé. Toutefois, peu d'études épidémiologiques ont évalué la relation entre les particules fines (PM2.5) de sources spécifiques comme celles dérivées de feux de forêt et les effets sur la santé. Pour l’instant, les risques de mortalité et de morbidité associés aux PM2.5 résultant de la combustion de végétation semblent similaires à ceux des PM2.5 urbaines. Dans le présent mémoire, nous avons comparé deux méthodes pour quantifier les risques de mortalité et de morbidité associés à l'augmentation des niveaux de PM2.5 à Montréal, dérivées de deux épisodes des feux de forêts majeurs dans le Nord du Québec. La première approche consistait à comparer les décès et les visites aux urgences observées enregistrées au cours des deux épisodes à Montréal à leurs moyennes respectives attendues durant des jours de référence. Nous avons également calculé la surmortalité et la surmorbidité prédites attribuables aux PM2.5 lors des épisodes, en projetant les risques relatifs (RR) rapportés par l’Environmental Protection Agency (EPA) des États-Unis pour les PM2.5 urbaines, ainsi qu’en appliquant des fonctions de risque estimées à partir des données estivales spécifiques à Montréal. Suivant la première approche, nous avons estimé une surmortalité de +10% pendant les deux épisodes. Cependant, aucune tendance claire n'a été observée pour les visites à l'urgence. Et suivant la 2e approche, la surmortalité prédite attribuable aux niveaux des PM2.5 dérivées des feux de forêt étaient moins élevés que ceux observés, soit de 1 à 4 cas seulement. Une faible surmortalité attribuable aux niveaux élevés des PM2.5 issues de feux de la forêt boréale du Québec a été estimée par les fonctions de risque ainsi que par la méthode de comparaison des décès observés aux moyennes attendues, sur l’Île de Montréal, située à des centaines de km des sites de feux. / The association between adverse health effects and short term exposure to urban particulate matter in ambient air is well established. Few epidemiological studies have assessed the relation between fine particles (PM2.5) of specific sources like forest fires, and health effects. According to the published literature to date, risks of mortality and morbidity associated with PM2.5 from combustion sources appear similar to those of urban PM2.5. In the present thesis, we compared two methods to quantify mortality and morbidity risks associated with the increase in PM2.5 levels in Montreal, due to two major forest fire episodes in Northern Quebec. In the first approach we compared mortality and emergency room visits counts recorded during the episodes to their respective averages expected on “usual” days. We also calculated deaths and emergency room visits attributable to PM2.5 levels on episode days, using the range of relative risks (RRs) reported by the United-States Environmental Protection Agency (EPA) for urban PM2.5 levels, as well as specific risk functions developed with Montreal summer data. With the first method, increases of deaths of more than 10% were observed for both episodes. However no clear tendency was observed in emergency room visits. Estimated attributable deaths associated with the increase in PM2.5 levels were smaller than those observed and ranged between 1 to 4 cases. PM2.5 from Quebec boreal forest fires were associated with small increases in mortality estimated either with the risk function method or by contrasting observed deaths on “episode” days to“usual” days, on the Island of Montreal, hundreds of kilometers away from the fire sites.

The thesis deals with the legal regulation of air protection on the municipal level. It is focused on providing an overview of legal instruments which are available on the municipal level, as well as the evaluation of their sufficiency and efficiency and point out the most significant instruments and some shortcomings of recent legislation. Some chosen instruments embodied in Czech law are compared with relevant German regulation. Also some specific, arguable constitutional aspects are taken in consideration and evaluated. The thesis provides a comparison of the old and the new Act on the Protection of Air at the field of interest.

Thesis (Ph.D. (Mining Engineering))--University of the Witwatersrand, Faculty of Engineering,1992.