984 resultados para Reaction-diffusion models


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The submerged entry nozzle (SEN) is used to transport the molten steel from a tundish to a mould. The main purpose of its usage is to prevent oxygen and nitrogen pick-up by molten steel from the gas. Furthermore, to achieve the desired flow conditions in the mould. Therefore, the SEN can be considered as a vital factor for a stable casting process and the steel quality. In addition, the steelmaking processes occur at high temperatures around 1873 K, so the interaction between the refractory materials of the SEN and molten steel is unavoidable. Therefore, the knowledge of the SEN behaviors during preheating and casting processes is necessary for the design of the steelmaking processes  The internal surfaces of modern SENs are coated with a glass/silicon powder layer to prevent the SEN graphite oxidation during preheating. The effects of the interaction between the coating layer and the SEN base refractory materials on clogging were studied. A large number of accretion samples formed inside alumina-graphite clogged SENs were examined using FEG-SEM-EDS and Feature analysis. The internal coated SENs were used for continuous casting of stainless steel grades alloyed with Rare Earth Metals (REM). The post-mortem study results clearly revealed the formation of a multi-layer accretion. A harmful effect of the SENs decarburization on the accretion thickness was also indicated. In addition, the results indicated a penetration of the formed alkaline-rich glaze into the alumina-graphite base refractory. More specifically, the alkaline-rich glaze reacts with graphite to form a carbon monoxide gas. Thereafter, dissociation of CO at the interface between SEN and molten metal takes place. This leads to reoxidation of dissolved alloying elements such as REM (Rare Earth Metal). This reoxidation forms the “In Situ” REM oxides at the interface between the SEN and the REM alloyed molten steel. Also, the interaction of the penetrated glaze with alumina in the SEN base refractory materials leads to the formation of a high-viscous alumina-rich glaze during the SEN preheating process. This, in turn, creates a very uneven surface at the SEN internal surface. Furthermore, these uneven areas react with dissolved REM in molten steel to form REM aluminates, REM silicates and REM alumina-silicates. The formation of the large “in-situ” REM oxides and the reaction of the REM alloying elements with the previously mentioned SEN´s uneven areas may provide a large REM-rich surface in contact with the primary inclusions in molten steel. This may facilitate the attraction and agglomeration of the primary REM oxide inclusions on the SEN internal surface and thereafter the clogging. The study revealed the disadvantages of the glass/silicon powder coating applications and the SEN decarburization. The decarburization behaviors of Al2O3-C, ZrO2-C and MgO-C refractory materials from a commercial Submerged Entry Nozzle (SEN), were also investigated for different gas atmospheres consisting of CO2, O2 and Ar. The gas ratio values were kept the same as it is in a propane combustion flue gas at different Air-Fuel-Ratio (AFR) values for both Air-Fuel and Oxygen-Fuel combustion systems. Laboratory experiments were carried out under nonisothermal conditions followed by isothermal heating. The decarburization ratio (α) values of all three refractory types were determined by measuring the real time weight losses of the samples. The results showed the higher decarburization ratio (α) values increasing for MgO-C refractory when changing the Air-Fuel combustion to Oxygen-Fuel combustion at the same AFR value. It substantiates the SEN preheating advantage at higher temperatures for shorter holding times compared to heating at lower temperatures during longer holding times for Al2O3-C samples. Diffusion models were proposed for estimation of the decarburization rate of an Al2O3-C refractory in the SEN. Two different methods were studied to prevent the SEN decarburization during preheating: The effect of an ZrSi2 antioxidant and the coexistence of an antioxidant additive and a (4B2O3 ·BaO) glass powder on carbon oxidation for non-isothermal and isothermal heating conditions in a controlled atmosphere. The coexistence of 8 wt% ZrSi2 and 15 wt% (4B2O3 ·BaO) glass powder of the total alumina-graphite refractory base materials, presented the most effective resistance to carbon oxidation. The 121% volume expansion due to the Zircon formation during heating and filling up the open pores by a (4B2O3 ·BaO) glaze during the green body sintering led to an excellent carbon oxidation resistance. The effects of the plasma spray-PVD coating of the Yttria Stabilized Zirconia (YSZ) powder on the carbon oxidation of the Al2O3-C coated samples were investigated. Trials were performed at non-isothermal heating conditions in a controlled atmosphere. Also, the applied temperature profile for the laboratory trials were defined based on the industrial preheating trials. The controlled atmospheres consisted of CO2, O2 and Ar. The thicknesses of the decarburized layers were measured and examined using light optic microscopy, FEG-SEM and EDS. A 250-290 μm YSZ coating is suggested to be an appropriate coating, as it provides both an even surface as well as prevention of the decarburization even during heating in air. In addition, the interactions between the YSZ coated alumina-graphite refractory base materials in contact with a cerium alloyed molten stainless steel were surveyed. The YSZ coating provided a total prevention of the alumina reduction by cerium. Therefore, the prevention of the first clogging product formed on the surface of the SEN refractory base materials. Therefore, the YSZ plasma-PVD coating can be recommended for coating of the hot surface of the commercial SENs.

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We construct exact solutions for a system of two coupled nonlinear partial differential equations describing the spatio-temporal dynamics of a predator-prey system where the prey per capita growth rate is subject to the Allee effect. Using the G'/G expansion method, we derive exact solutions to this model for two different wave speeds. For each wave velocity we report three different forms of solutions. We also discuss the biological relevance of the solutions obtained. © 2012 Elsevier B.V.

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How individual-level movement decisions in response to habitat edges influence population-level patterns of persistence and spread of a species is a major challenge in spatial ecology and conservation biology. Here, we integrate novel insights into edge behavior, based on habitat preference and movement rates, into spatially explicit growth-dispersal models. We demonstrate how crucial ecological quantities (e.g., minimal patch size, spread rate) depend critically on these individual-level decisions. In particular, we find that including edge behavior properly in these models gives qualitatively different and intuitively more reasonable results than those of some previous studies that did not consider this level of detail. Our results highlight the importance of new empirical work on individual movement response to habitat edges. © 2013 by The University of Chicago.

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Pós-graduação em Física - IFT

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.

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Usually we observe that Bio-physical systems or Bio-chemical systems are many a time based on nanoscale phenomenon in different host environments, which involve many particles can often not be solved explicitly. Instead a physicist, biologist or a chemist has to rely either on approximate or numerical methods. For a certain type of systems, called integrable in nature, there exist particular mathematical structures and symmetries which facilitate the exact and explicit description. Most integrable systems, we come across are low-dimensional, for instance, a one-dimensional chain of coupled atoms in DNA molecular system with a particular direction or exist as a vector in the environment. This theoretical research paper aims at bringing one of the pioneering ‘Reaction-Diffusion’ aspects of the DNA-plasma material system based on an integrable lattice model approach utilizing quantized functional algebras, to disseminate the new developments, initiate novel computational and design paradigms.

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We use the photosensitive chlorine dioxide-iodine-malonic acid reaction-diffusion system to study wavenumber locking of Turing patterns to two-dimensional "square" spatial forcing, implemented as orthogonal sets of bright bands projected onto the reaction medium. Various resonant structures emerge in a broad range of forcing wavelengths and amplitudes, including square lattices and superlattices, one-dimensional stripe patterns and oblique rectangular patterns. Numerical simulations using a model that incorporates additive two-dimensional spatially periodic forcing reproduce well the experimental observations.

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We consider stochastic individual-based models for social behaviour of groups of animals. In these models the trajectory of each animal is given by a stochastic differential equation with interaction. The social interaction is contained in the drift term of the SDE. We consider a global aggregation force and a short-range repulsion force. The repulsion range and strength gets rescaled with the number of animals N. We show that for N tending to infinity stochastic fluctuations disappear and a smoothed version of the empirical process converges uniformly towards the solution of a nonlinear, nonlocal partial differential equation of advection-reaction-diffusion type. The rescaling of the repulsion in the individual-based model implies that the corresponding term in the limit equation is local while the aggregation term is non-local. Moreover, we discuss the effect of a predator on the system and derive an analogous convergence result. The predator acts as an repulsive force. Different laws of motion for the predator are considered.

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Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

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The diffusion of radionuclides is an important safety aspect for nuclear waste disposal in argillaceous host rocks. A long-term diffusion experiment, termed DI-A, is being carried out at the Mont Terri Rock Laboratory in the Opalinus Clay formation. The aim of this experiment is the understanding of the migration and sorption behaviour of cationic and anionic species in consolidated clays. This study reports on the experimental layout and the first results obtained from the DI-A experiment, which include the investigation of HTO, Na-22(+), Cs+, and I- migration during a period of 1 year by analysing these tracers in the water circulating in the borehole. In addition, results obtained from through-diffusion experiments on small-sized samples with HTO, I-, and Cl-36(-) are presented. The decrease of tracer concentrations in the borehole is fastest for Cs+, followed by Na-22(+), HTO, and finally I-. The chemical composition of the artificial pore water in the borehole shows very little variation with time, thus indicating almost no chemical disturbance around the borehole. Through-diffusion experiments in the laboratory that were performed parallel to the bedding plane with two different methods yielded effective diffusion coefficients for HTO of 4-5 X 10(-11) m(2) s(-1) and significantly lower ones for anions Cl- and I- (0.7-1.6 X 10(-11) m(2) s(-1)). The results indicate the importance of anion exclusion effects arising from the negatively charged clay surfaces. Furthermore, they demonstrate the anisotropic diffusion properties of the clay formation with significantly increased diffusion rates parallel to bedding relative to the perpendicular direction. The tracer data of the in situ experiment were successfully described with 2D diffusion models using diffusion and sorption parameters obtained from the above mentioned and other laboratory studies. The modelling results indicate that HTO and I- diffused with no retardation. The retardation of Na+ and Cs+ could be described by empirical sorption expressions from previously derived batch sorption (Cs+) or diffusion (Na+) experiments. Overall, the obtained results demonstrate the feasibility of the technical concept to study the diffusion of nonsorbing and sorbing tracers in consolidated clays. (C) 2004 Elsevier B.V. All rights reserved.

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High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.

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Biodiesel is fast becoming one of the key transport fuels as the world endeavours to reduce its carbon footprint and find viable alternatives to oil derived fuels. Research in the field is currently focusing on more efficient ways to produce biodiesel, with the most promising avenue of research looking into the use of heterogeneous catalysis. This article presents a framework for kinetic reaction and diffusive transport modelling of the heterogeneously catalysed transesterification of triglycerides into fatty acid methyl esters (FAMEs), unveiled by a model system of tributyrin transesterification in the presence of MgO catalysts. In particular, the paper makes recommendations on multicomponent diffusion calculations such as the diffusion coefficients and molar fluxes from infinite dilution diffusion coefficients using the Wilke and Chang correlation, intrinsic reaction kinetic studies using the Eley-Rideal kinetic mechanism with methanol adsorption as the rate determining steps and multiscale reaction-diffusion process simulation between catalytic porous and bulk reactor scales. © 2013 The Royal Society of Chemistry.

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The research presented in this thesis was developed as part of DIBANET, an EC funded project aiming to develop an energetically self-sustainable process for the production of diesel miscible biofuels (i.e. ethyl levulinate) via acid hydrolysis of selected biomass feedstocks. Three thermal conversion technologies, pyrolysis, gasification and combustion, were evaluated in the present work with the aim of recovering the energy stored in the acid hydrolysis solid residue (AHR). Mainly consisting of lignin and humins, the AHR can contain up to 80% of the energy in the original feedstock. Pyrolysis of AHR proved unsatisfactory, so attention focussed on gasification and combustion with the aim of producing heat and/or power to supply the energy demanded by the ethyl levulinate production process. A thermal processing rig consisting on a Laminar Entrained Flow Reactor (LEFR) equipped with solid and liquid collection and online gas analysis systems was designed and built to explore pyrolysis, gasification and air-blown combustion of AHR. Maximum liquid yield for pyrolysis of AHR was 30wt% with volatile conversion of 80%. Gas yield for AHR gasification was 78wt%, with 8wt% tar yields and conversion of volatiles close to 100%. 90wt% of the AHR was transformed into gas by combustion, with volatile conversions above 90%. 5volO2%-95vol%N2 gasification resulted in a nitrogen diluted, low heating value gas (2MJ/m3). Steam and oxygen-blown gasification of AHR were additionally investigated in a batch gasifier at KTH in Sweden. Steam promoted the formation of hydrogen (25vol%) and methane (14vol%) improving the gas heating value to 10MJ/m3, below the typical for steam gasification due to equipment limitations. Arrhenius kinetic parameters were calculated using data collected with the LEFR to provide reaction rate information for process design and optimisation. Activation energy (EA) and pre-exponential factor (ko in s-1) for pyrolysis (EA=80kJ/mol, lnko=14), gasification (EA=69kJ/mol, lnko=13) and combustion (EA=42kJ/mol, lnko=8) were calculated after linearly fitting the data using the random pore model. Kinetic parameters for pyrolysis and combustion were also determined by dynamic thermogravimetric analysis (TGA), including studies of the original biomass feedstocks for comparison. Results obtained by differential and integral isoconversional methods for activation energy determination were compared. Activation energy calculated by the Vyazovkin method was 103-204kJ/mol for pyrolysis of untreated feedstocks and 185-387kJ/mol for AHRs. Combustion activation energy was 138-163kJ/mol for biomass and 119-158 for AHRs. The non-linear least squares method was used to determine reaction model and pre-exponential factor. Pyrolysis and combustion of biomass were best modelled by a combination of third order reaction and 3 dimensional diffusion models, while AHR decomposed following the third order reaction for pyrolysis and the 3 dimensional diffusion for combustion.