Thesis (Ph. D.)--University of Maryland, College Park, 2006. / Facsimile, authorized copy, from UMI/Proquest; UMI number 3222497. Includes bibliographical references. Also available on the internet.

Due to the complexity, multi-scale, and multi-physics nature of the mathematical models for fires, current numerical models require too much computational effort to be useful in design and real-time decision making, especially when dealing with fires over large domains. To reduce the computational time while retaining the complexity of the domain and physics, our research has focused on several reduced-order modeling techniques. Our contributions are improving wildland fire reduced-order models (ROMs), creating new ROM techniques for nonlinear systems, and preserving optimality when discretizing a continuous-time ROM. Currently, proper orthogonal decomposition (POD) is being used to reduce wildland fire-spread models with limited success. We use a technique known as the discrete empirical interpolation method (DEIM) to address the slowness due to the nonlinearity. We create new methods to reduce nonlinear models, such as the Burgers' equation, that perform better than POD over a wider range of input conditions. Further, these ROMs can often be constructed without needing to capture full-order solutions a priori. This significantly reduces the off-line costs associated with creating the ROM. Finally, we investigate methods of time-discretization that preserve the optimality conditions in a certain norm associated with the input to output mapping of a dynamical system. In particular, we are able to show that the Crank-Nicholson method preserves the optimality conditions, but other single-step methods do not. We further clarify the need for these discrete-time ROMs to match at infinity in order to ensure local optimality. / Ph. D.

A material study was conducted on two types of cored composite materials used in shipbuilding: a GRP/Balsa Cored sandwich and a GRP/PVC Foam Cored sandwich. The two materials were tested in the Cone Calorimeter and the LIFT Apparatus to obtain data on ignitability, heat release rate, mass loss rate, and smoke production. The observed phenomena of delamination, melting and charring of the core materials, and edge effects are discussed in the context of how they affect test results. The ignition data analysis method specified in ASTM E 1321 "Standard Test Method for Determining Material Ignition and Flame Spread Properties" and Janssens' "improved" method of analysis were both used to derive effective material properties of the test materials. These two analysis methods are shown to produce different material property values for critical irradiance for ignition, ignition temperature, and the effective thermal property, $k ho c$. Material properties derived using Janssens' method are shown to be more consistent between the two test materials and the two different test methods; they were also shown to be better predictors of time to ignition when compared to actual test data. Material properties are used as input to Quintiere's fire growth model in order to evaluate their affect on time to flashover predictions in the ISO 9705 Room/Corner test scenario. Recommendations are made for future testing of cored composite materials, ignition data analysis methods, predictive fire growth models, and other work with composite materials. ** This copy contains no figures or appendices **

The current design methods used to determine fire progression and temperature-time development in fire compartments today are being questioned to not give accurate results in large and complex enclosures (larger than 500 m2). The established design methods proposed by Eurocode and used by fire safety engineers today are primarily the standard temperature-time curve and the parametric temperature-time curves. The parametric temperature-time curves are based on the heat and mass balance equations and both methods assume homogenous temperatures and uniform burning. These assumptions are being questioned for use in large enclosures such as open-plan compartments and compartments with multiple floors connected which are typically modern and common building types in today’s society. Today there are no established design methods developed to determine fire progression in large enclosures, but the Improved Travelling Fire Method (iTFM) and the New MT model II are new, alternative design methods which are prospects to become established engineering tools in the future. The iTFM is developed at the University of Edinburgh for travelling fires in large size compartments and the New MT model II is developed by RISE, Research Institutes of Sweden, for large tunnel fires. These two new design methods have been investigated and compared to established methods in a case study. Also localised fires from Eurocode with proposed interpretations by Ulf Wickström has been investigated and compared to the standard temperature-time curve and the parametric temperature-time curves. The new interpretation suggests that the given heat flux boundary conditions in Eurocode are interpreted as adiabatic surface temperatures based on given emissivities and convection heat transfer coefficients according to Eurocode. Through a case study the different methods were compared throughout reference buildings with constant material properties and fire loads, but with varying floor area and height. The result focused on if the new methods have more bearing on reality than the standard fire curve and the parametric temperature-time curves methods when determining fire progression and temperature-time development. Desired benefits with the new methods are to better predict and describe fire development in large enclosures. The referenceIIIbuildings were considered as occupancy class 2 (Vk2) and Br2 buildings with a load bearing fire resistance capacity demand of 30 minutes. This report is an early stage in the process of developing new fire models to improve the fire designing process when working with large compartments. The aim with the new, alternative methods and localised fires with proposed interpretation is to enable them to become engineering tools used by fire safety engineers in the future to create a more efficient and adapted design process. The results differ significantly depending on used method and reference building. The maximum temperatures conducted by the iTFM are in general higher than the standard fire curve and the parametric temperature-time curves. When applying the method to the reference building with high ceiling height and low spread rate the resulting temperatures were lower than the standard fire curve. The fire progression of the New MT model II is highly dependent on opening factor and time until temperature increase starts. In comparison to the parametric fire curves with the same opening factors the New MT model II resulted in considerably faster temperature development and higher temperatures. Localised fires with the new proposed interpretations resulted in adiabatic surface temperatures which were compared to the standard temperature-time curve after 30 minutes of fire and the maximum temperature of the parametric temperature-time curves. The comparison resulted in slightly lower temperatures for the localised fires with the new proposed interpretations compared to the standard temperature-time curve and similar temperatures compared to the parametric temperature-time curves in the case study. The results of the iTFM and the New MT model II differs significantly depending on physical parameters used in the calculation processes. The models are customizable and vary depending on fire scenarios and compartments and could possibly be future alternative methods when designing for fires in large compartments. Further studies and development together with real fire tests would provide the models with better accuracy and continuity. Localised fires with proposed new interpretations are a future prospect to become a future standard method for determination of maximum temperature of member surfaces in fire safety design.

Die vorliegende Arbeit beschäftigt sich mit Mechanismen, die in Einzelzellmodellen zu einer frequenzabhängigen Informationsübertragung führen können. Um dies zu untersuchen, werden Methoden aus der theoretischen Physik (Statistische Physik) und der Informationstheorie angewandt. Die Informationsfilterung in mehreren stochastischen Neuronmodellen, in denen unterschiedliche Mechanismen zur Informationsfilterung führen können, werden numerisch und, falls möglich, analytisch untersucht. Die Bandbreite der betrachteten Modelle erstreckt sich von reduzierten strombasierten ’Integrate-and-Fire’ (IF) Modellen bis zu biophysikalisch realistischeren leitfähigkeitsbasierten Modellen. Anhand numerischer Untersuchungen wird aufgezeigt, dass viele Varianten der IF-Neuronenmodelle vorzugsweise Information über langsame Anteile eines zeitabhängigen Eingangssignals übertragen. Der einfachste Vertreter der oben genannten Klasse der IF-Neuronmodelle wird dahingehend erweitert, dass ein Konzept von neuronalem ’Gedächtnis’, vermittelst positiver Korrelationen zwischen benachbarten Intervallen aufeinander- folgender Spikes, integriert wird. Dieses Model erlaubt eine analytische störungstheoretische Untersuchung der Auswirkungen positiver Korrelationen auf die Informationsfilterung. Um zu untersuchen, wie sich sogenannte ’unterschwelligen Resonanzen’ auf die Signalübertragung auswirken, werden Neuronenmodelle mit verschiedenen Nichtlinearitäten anhand numerischer Computersimulationen analysiert. Abschließend wird die Signalübertragung in einem neuronalen Kaskadensystem, bestehend aus linearen und nichtlinearen Elementen, betrachtet. Neuronale Nichtlinearitäten bewirken eine gegenläufige Abhängigkeit (engl. "trade-off") zwischen qualitativer, d.h. frequenzselektiver, und quantitativer Informations-übertragung, welche in allen von mir untersuchten Modellen diskutiert wird. Diese Arbeit hebt die Gewichtigkeit von Nichtlinearitäten in der neuronalen Informationsfilterung hervor. / Neurons transmit information about time-dependent input signals via highly non-linear responses, so-called action potentials or spikes. This type of information transmission can be frequency-dependent and allows for preferences for certain stimulus components. A single neuron can transmit either slow components (low pass filter), fast components (high pass filter), or intermediate components (band pass filter) of a time-dependent input signal. Using methods developed in theoretical physics (statistical physics) within the framework of information theory, in this thesis, cell-intrinsic mechanisms are being investigated that can lead to frequency selectivity on the level of information transmission. Various stochastic single neuron models are examined numerically and, if tractable analytically. Ranging from simple spiking models to complex conductance-based models with and without nonlinearities, these models include integrator as well as resonator dynamics. First, spectral information filtering characteristics of different types of stochastic current-based integrator neuron models are being studied. Subsequently, the simple deterministic PIF model is being extended with a stochastic spiking rule, leading to positive correlations between successive interspike intervals (ISIs). Thereafter, models are being examined which show subthreshold resonances (so-called resonator models) and their effects on the spectral information filtering characteristics are being investigated. Finally, the spectral information filtering properties of stochastic linearnonlinear cascade neuron models are being researched by employing different static nonlinearities (SNLs). The trade-off between frequency-dependent signal transmission and the total amount of transmitted information will be demonstrated in all models and constitutes a direct consequence of the nonlinear formulation of the models.

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.