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Fire Safety Engineering is required at every stage in the life cycle of modern-day buildings. Fire safety design, detection and suppression, and emergency response are all vital components of Structural Fire Safety but are usually perceived as independent issues. Sensor deployment and exploitation is now common place in modern buildings for means such as temperature, air quality and security management. Despite the potential wealth of information these sensors could afford fire fighters, the design of sensor networks within buildings is entirely detached from procedures associated to emergency management. The experiences of Dalmarnock Fire Test Two showed that streams of raw data emerging from sensors lead to a rapid information overload and do little to improve the understanding of the complex phenomenon and likely future events during a real fire. Despite current sensor technology in other fields being far more advanced than that of fire, there is no justification for more complex and expensive sensors in this context. In isolation therefore, sensors are not sufficient to aid emergency response. Fire modelling follows a similar path. Two studies of Dalmarnock Fire Test One demonstrate clearly the current state of the art of fire modelling. A Priori studies by Rein et al. 2009 showed that blind prediction of the evolution of a compartment fire is currently beyond the state of the art of fire modelling practice. A Posteriori studies by Jahn et al. 2007 demonstrated that even with the provision of large quantities of sensor data, video footage, and prior knowledge of the fire; producing a CFD reconstruction was an incredibly difficult, laborious, intuitive and repetitive task. Fire fighting is therefore left as an isolated activity that does not benefit from sensor data or the potential of modelling the event. In isolation sensors and fire modelling are found lacking. Together though they appear to form the perfect compliment. Sensors provide a plethora of information which lacks interpretation. Models provide a method of interpretation but lack the necessary information to make this output robust. Thus a mechanism to achieve accurate, timely predictions by means of theoretical models steered by continuous calibration against sensor measurements is proposed. Issues of accuracy aside, these models demand heavy resources and computational time periods that are far greater than the time associated with the processes being simulated. To be of use to emergency responders, the output would need to be produced faster than the event itself with lead time to enable planning of an intervention strategy. Therefore in isolation, model output is not robust or fast enough to be implemented in an emergency response scenario. The concept of super-real time predictions steered by measurements is studied in the simple yet meaningful scenario of concurrent flow flame spread. Experiments have been conducted with PMMA slabs to feed sensor data into a simple analytical model. Numerous sensing techniques have been adapted to feed a simple algebraic expression from the literature linking flame spread, flame characteristics and pyrolysis evolution in order to model upward flame spread. The measurements are continuously fed to the computations so that projections of the flame spread velocity and flame characteristics can be established at each instant in time, ahead of the real flame. It was observed that as the input parameters in the analytical models were optimised to the scenario, rapid convergence between the evolving experiment and the predictions was attained.

This thesis describes the development and validation of a modified eddy viscosity model to take into account the misalignment between stress a_{ij} and strain S_{ij} fields for reacting flow. The stress-strain misalignment is quantified by introducing a C_{as}=-a_{ij}S_{ij} /\sqrt{2S_{ij}S_{ij}} parameter. A new transport equation for C_{as} was derived from a full Reynolds stress model (RSM). The C_{as} transport equation was coupled to a standard EVM model (e.g. k-\omega SST) to form three equations model. This model is a new version of the SST-C_{as} model introduced by Revell (Revell2006), to incorporate buoyancy and combustion effects for buoyant reacting flow (e.g. fire). The performance of the proposed model was initially investigated via non-reacting buoyant plumes with different level of unsteadiness. The buoyant plumes were also simulated using different turbulence models and the results were compared to proposed model and experimental data. The model shows significant improvements for velocity and scalar profiles in region closed to plume centreline compared to the original SST model. The SST-C_{as} model was then applied for a real fire test case (Steckler room), and the results were compared to experimental data and results of RSM models. The SST-C_{as} model generally yields better than classical EVM models and reduces the gap between the RSM and EVM prediction with 25-30\% additional computational expenses. This work is still under development and validation for reacting flows, further work is going on to include the turbulence combustion interaction and validate it with DNS data.

This study is designed to provide the composites industry as well as the fire engineering industry baseline data for pyrolysis modelling of common fiber reinforced polymer (FRP) systems. Four resin systems and three glass contents will be considered. This matrix of FRP systems has been carefully fabricated and documented so as to provide“transparency" as to the system compositions. An important and interesting aspect of these FRP systems is that all the resins used are listed by the manufacturers as Class 1 or Class A per ASTM E 84. The FRP systems are being evaluated in bench scale modern fire test apparatuses (FPA, ASTM E 2058, and Cone, ASTM E 1354); detailed information on the FPA is provided. These apparatuses provide a range of measurements such as heat release rate that can be used to calculate engineering“properties" of these FRP systems. The“properties", such as minimum heat flux for proper ignition (found to range from 20 to over 100 kW/m2) and the b flame spread parameter, can then be used to compare the fire performance (flashover potential) of these FRP systems according to resin type and glass content. Additional instrumentation has also been added to the specimens to allow surface and in-depth temperatures to be measured. The additional measurements are used to complete a set of data for pyrolysis modelling and for calculating thermal properties of the composites. The effect of environment oxygen concentration and flaming and non-flaming decomposition are investigated in terms of fundamental pyrolysis behavior of the FRP systems. A general conclusion is that the phenolic composite has better fire engineering“properties" than the polyester composite but the glass is the controlling component of the composite with regards to temperature profile and resulting thermal properties.

Many studies of the fire induced thermal and structural behaviour in large compartments, carried out over the past two decades, show a great deal of non-uniformity, unlike the homogeneous compartment temperature assumption in the current fire safety engineering practice. Furthermore, some large compartment fires may burn locally and they tend to move across entire floor plates over a period of time as the fuel is consumed. This kind of fire scenario is beginning to be idealized as 'travelling fires' in the context of performance‐based structural and fire safety engineering. However, the previous research of travelling fires still relies on highly simplified travelling fire models (i.e. Clifton's model and Rein's model); and no equivalent numerical tools can perform such simulations, which involves analysis of realistic fire, heat transfer and thermo-mechanical response in one single software package with an automatic coupled manner. Both of these hinder the advance of the research on performance‐based structural fire engineering. The author develops an extended travelling fire method (ETFM) framework and an integrated comprehensive tool with high computational expediency in this research, to address the above‐mentioned issues. The experiments conducted for characterizing travelling fires over the past two decades are reviewed, in conjunction with the current available travelling fire models. It is found that no performed travelling fire experiment records both the structural response and the mass loss rate of the fuel (to estimate the fire heat release rate) in a single test, which further implies closer collaboration between the structural and the fire engineers' teams are needed, especially for the travelling fire research topic. In addition, an overview of the development of OpenSees software framework for modelling structures in fire is presented, addressing its theoretical background, fundamental assumptions, and inherent limitations. After a decade of development, OpenSees has modules including fire, heat transfer, and thermo‐mechanical analysis. Meanwhile, it is one of the few structural fire modelling software which is open source and free to the entire community, allowing interested researchers to use and contribute with no expense. An OpenSees‐based integrated tool called SIFBuilder is developed by the author and co‐workers, which can perform fire modelling, heat transfer analysis, and thermo-mechanical analysis in one single software with an automatic coupled manner. This manner would facilitate structural engineers to apply fire loading on their design structures like other mechanical loading types (e.g. seismic loading, gravity loading, etc.), without transferring the fire and heat transfer modelling results to each structural element manually and further assemble them to the entire structure. This feature would largely free the structural engineers' efforts to focus on the structural response for performance-based design under different fire scenarios, without investigating the modelling details of fire and heat transfer analysis. Moreover, the efficiency due to this automatic coupled manner would become more superior, for modelling larger structures under more realistic fire scenarios (e.g. travelling fires). This advantage has been confirmed by the studies carried out in this research, including 29 travelling fire scenarios containing total number of 696 heat transfer analysis for the structural members, which were undertaken at very modest computational costs. In addition, a set of benchmark problems for verification and validation of OpenSees/SIFBuilder are investigated, which demonstrates good agreement against analytical solutions, ABAQUS, SAFIR, and the experimental data. These benchmark problems can also be used for interested researchers to verify their own numerical or analytical models for other purposes, and can be also used as an induction guide of OpenSees/SIFBuilder. Significantly, an extended travelling fire method (ETFM) framework is put forward in this research, which can predict the fire severity considering a travelling fire concept with an upper bound. This framework considers the energy and mass conservation, rather than simply forcing other independent models to 'travel' in the compartment (i.e. modified parametric fire curves in Clifton's model, 800°C‐1200°C temperature block and the Alpert's ceiling jet in Rein's model). It is developed based on combining Hasemi's localized fire model for the fire plume, and a simple smoke layer calculation by utilising the FIRM zone model for the areas of the compartment away from the fire. Different from mainly investigating the thermal impact due to various ratios of the fire size to the compartment size (e.g. 5%, 10%, 25%, 75%, etc.), as in Rein's model, this research investigates the travelling fire thermal impact through explicit representation of the various fire spread rates and fuel load densities, which are the key input parameters in the ETFM framework. To represent the far field thermal exposures, two zone models (i.e. ASET zone model & FIRM zone model) and the ETFM framework are implemented in SIFBuilder, in order to provide the community a 'vehicle' to try, test, and further improve this ETFM framework, and also the SIFBuilder itself. It is found that for 'slow' travelling fires (i.e. low fire spread rates), the near‐field fire plume brings more dominant thermal impact compared with the impact from far‐field smoke. In contrast, for 'fast' travelling fires (i.e. high fire spread rates), the far‐field smoke brings more dominant thermal impact. Furthermore, the through depth thermal gradients due to different travelling fire scenarios were explored, especially with regards to the 'thermal gradient reversal' due to the near‐field fire plume approaching and leaving the design structural member. This 'thermal gradient reversal' would fundamentally reverse the thermally‐induced bending moment from hogging to sagging. The modelling results suggest that the peak thermal gradient due to near‐field approaching is more sensitive to the fuel load density than fire spread rate, where larger peak values are captured with lower fuel load densities. Moreover, the reverse peak thermal gradient due to near‐field leaving is also sensitive to the fuel load density rather than the fire spread rate, but this reverse peak value is inversely proportional to the fuel load densities. Finally, the key assumptions of the ETFM framework are rationalised and its limitations are emphasized. Design instructions with relevant information which can be readily used by the structural fire engineers for the ETFM framework are also included. Hence more optimised and robust structural design under such fire threat can be generated and guaranteed, where we believe these efforts will advance the performance‐based structural and fire safety engineering.

Untersuchungen zur Rolle natürlicher Störungen in der Vegetation bzw. in Ökosystemen zeigen, dass natürliche Störungen ein essentielles und intrinsisches Element in Ökosystemen darstellen, substanziell zur Vitalität und strukturellen Diversität der Ökosysteme beitragen und Stoffkreisläufe sowohl auf dem lokalen als auch auf dem globalen Niveau beeinflussen. Feuer als Grasland-, Busch- oder Waldbrand ist ein besonderes Störungsagens, da es sowohl durch biotische als auch abiotische Umweltfaktoren verursacht wird. Es beeinflusst biogeochemische Kreisläufe und spielt für die chemische Zusammensetzung der Atmosphäre durch Freisetzung klimarelevanter Spurengase und Aerosole aus der Verbrennung von Biomasse eine bedeutende Rolle. Dies wird auch durch die Emission von ca. 3.9 Gt Kohlenstoff pro Jahr unterstrichen, was einen großen Anteil am globalen Gesamtaufkommen ausmacht.<br /> <br /> Ein kombiniertes Modell, das die Effekte und Rückkopplungen zwischen Feuer und Vegetation beschreibt, wurde erforderlich, als Änderungen in den Feuerregimes als Folge von Änderungen in der Landnutzung und dem Landmanagement festgestellt wurden. Diese Notwendigkeit wurde noch durch die Erkenntnis unterstrichen, daß die Menge verbrennender Biomasse als ein bedeutender Kohlenstoffluß sowohl die chemische Zusammensetzung der Atmosphäre und das Klima, aber auch die Vegetationsdynamik selbst beeinflusst. Die bereits existierenden Modellansätze reichen hier jedoch nicht aus, um entsprechende Untersuchungen durchzuführen. Als eine Schlussfolgerung daraus wurde eine optimale Menge von Faktoren gefunden, die das Auftreten und die Ausbreitung des Feuers, sowie deren ökosystemare Effekte ausreichend beschreiben. Ein solches Modell sollte die Merkmale beobachteter Feuerregime simulieren können und Analysen der Interaktionen zwischen Feuer und Vegetationsdynamik unterstützen, um auch Ursachen für bestimmte Änderungen in den Feuerregimes herausfinden zu können. Insbesondere die dynamischen Verknüpfungen zwischen Vegetation, Klima und Feuerprozessen sind von Bedeutung, um dynamische Rückkopplungen und Effekte einzelner, veränderter Umweltfaktoren zu analysieren. Dadurch ergab sich die Notwendigkeit, neue Feuermodelle zu entwickeln, die die genannten Untersuchungen erlauben und das Verständnis der Rolle des Feuer in der globalen Ökologie verbessern.<br /> <br /> Als Schlussfolgerung der Dissertation wird festgestellt, dass Feuchtebedingungen, ihre Andauer über die Zeit (Länge der Feuersaison) und die Streumenge die wichtigsten Komponenten darstellen, die die Verteilung der Feuerregime global beschreiben. Werden Zeitreihen einzelner Regionen simuliert, sollten besondere Entzündungsquellen, brandkritische Klimabedingungen und die Bestandesstruktur als zusätzliche Determinanten berücksichtigt werden. Die Bestandesstruktur verändert das Niveau des Auftretens und der Ausbreitung von Feuer, beeinflusst jedoch weniger dessen interannuelle Variabilität. Das es wichtig ist, die vollständige Wirkungskette wichtiger Feuerprozesse und deren Verknüpfungen mit der Vegetationsdynamik zu berücksichtigen, wird besonders unter Klimaänderungsbedingungen deutlich. Eine länger werdende, vom Klima abhängige Feuersaison bedeutet nicht automatisch eine im gleichen Maße anwachsende Menge verbrannter Biomasse. Sie kann durch Änderungen in der Produktivität der Vegetation gepuffert oder beschleunigt werden. Sowohl durch Änderungen der Bestandesstruktur als auch durch eine erhöhte Produktivität der Vegetation können Änderungen der Feuereigenschaften noch weiter intensiviert werden und zu noch höheren, feuerbezogenen Emissionen führen. / Studies of the role of disturbance in vegetation or ecosystems showed that disturbances are an essential and intrinsic element of ecosystems that contribute substantially to ecosystem health, to structural diversity of ecosystems and to nutrient cycling at the local as well as global level. Fire as a grassland, bush or forest fire is a special disturbance agent, since it is caused by biotic as well abiotic environmental factors. Fire affects biogeochemical cycles and plays an important role in atmospheric chemistry by releasing climate-sensitive trace gases and aerosols, and thus in the global carbon cycle by releasing approximately 3.9 Gt C p.a. through biomass burning. <br /> <br /> A combined model to describe effects and feedbacks between fire and vegetation became relevant as changes in fire regimes due to land use and land management were observed and the global dimension of biomass burnt as an important carbon flux to the atmosphere, its influence on atmospheric chemistry and climate as well as vegetation dynamics were emphasized. The existing modelling approaches would not allow these investigations. As a consequence, an optimal set of variables that best describes fire occurrence, fire spread and its effects in ecosystems had to be defined, which can simulate observed fire regimes and help to analyse interactions between fire and vegetation dynamics as well as to allude to the reasons behind changing fire regimes. Especially, dynamic links between vegetation, climate and fire processes are required to analyse dynamic feedbacks and effects of changes of single environmental factors. This led us to the point, where new fire models had to be developed that would allow the investigations, mentioned above, and could help to improve our understanding of the role of fire in global ecology. <br /> <br /> In conclusion of the thesis, one can state that moisture conditions, its persistence over time and fuel load are the important components that describe global fire pattern. If time series of a particular region are to be reproduced, specific ignition sources, fire-critical climate conditions and vegetation composition become additional determinants. Vegetation composition changes the level of fire occurrence and spread, but has limited impact on the inter-annual variability of fire. The importance to consider the full range of major fire processes and links to vegetation dynamics become apparent under climate change conditions. Increases in climate-dependent length of fire season does not automatically imply increases in biomass burnt, it can be buffered or accelerated by changes in vegetation productivity. Changes in vegetation composition as well as enhanced vegetation productivity can intensify changes in fire and lead to even more fire-related emissions. <br><br> ---<br> Anmerkung:<br> Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2002/2003.

Fuels management in eucalyptus plantations is essential to minimise the impact of wildfire. Prescribed burning has the potential to reduce the fuel hazard in plantations, but is not routinely conducted due to concerns relating to tree damage. Through a series of experimental burns, the issues of tree damage are addressed and minimum tree sizes are recommended that are capable of withstanding the effects of low to moderate intensity fires. Data was collected between 2005 and 2007 over six sites, two species, and three age classes. Tree response results came from multiple measurements of over 1700 individual trees. The fuel characteristics commonly found in sub-tropical eucalypt plantations from age four to eleven are described and quantified. These fuel characteristics are related to fire behaviour and new fire behaviour models, specific to young eucalypt plantations, are presented. The fuel characteristics that most influence fire behaviour in young eucalypt plantations are fuel load, fuel height, and fuel moisture content. These characteristics can be used to predict the rate of spread of a plantation fire under benign wind conditions. A novel technique for assessing the extent of stem damage in eucalypts is developed and described. This technique enables immediate assessment of stem damage following fire; previous assessment techniques recommend waiting a considerable period of time (up to 2 years) until dead bark dropped off and fire scars were evident. This new assessment technique is likely to be suitable for post-fire assessment of any eucalypt species and will provide forest managers with the capability of deciding whether to leave a stand to ???grow-on??? or commence recovery operations. Minimum stem sizes recommended to ensure no long-term damage are between 5 ??? 8 cm DBH (diameter at breast height, i.e. 1.3m above ground level) for Eucalyptus dunnii (Dunn???s white gum) and 5 ??? 13 cm DBH for Corymbia spp. (spotted gum) depending on the quantity of fuel around the stem. Stem sizes vary between species because of the variation in bark thickness between species. This thesis provides all the necessary information to conduct prescribed burning operations in young eucalypt plantations.

{This thesis deals with fire detection in video by colour analysis and machine learning, specifically deep convolutional neural networks, using Caffe framework. The aim is to create a vast set of data that could be used as the base element of machine learning detection and create a detector usable in real application. For the purposes of the project a set of tools for fire sequences creation, their segmentation and automatic labeling is proposed and created together with a large test set of short sequences with artificial modelled fire.