Processamento do alho negro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatial dynamics of a population with stage-dependent diffusion

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An introductory informatics theoretical framework, based on an integrable lattice model using quantized function algebras, for studying DNA-ionized gas interaction system

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.

Turing patterns in the chlorine dioxide-iodine-malonic acid reaction with square spatial periodic forcing

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.

Rotational diffusion membrane and fluorescence anisotropy.

Structural properties of model membranes, such as lipid vesicles, may be investigated through the addition of fluorescent probes. After incorporation, the fluorescent molecules are excited with linearly polarized light and the fluorescence emission is depolarized due to translational as well as rotational diffusion during the lifetime of the excited state. The monitoring of emitted light is undertaken through the technique of time-resolved fluorescence: the intensity of the emitted light informs on fluorescence decay times, and the decay of the components of the emitted light yield rotational correlation times which inform on the fluidity of the medium. The fluorescent molecule DPH, of uniaxial symmetry, is rather hydrophobic and has collinear transition and emission moments. It has been used frequently as a probe for the monitoring of the fluidity of the lipid bilayer along the phase transition of the chains. The interpretation of experimental data requires models for localization of fluorescent molecules as well as for possible restrictions on their movement. In this study, we develop calculations for two models for uniaxial diffusion of fluorescent molecules, such as DPH, suggested in several articles in the literature. A zeroth order test model consists of a free randomly rotating dipole in a homogeneous solution, and serves as the basis for the study of the diffusion of models in anisotropic media. In the second model, we consider random rotations of emitting dipoles distributed within cones with their axes perpendicular to the vesicle spherical geometry. In the third model, the dipole rotates in the plane of the of bilayer spherical geometry, within a movement that might occur between the monolayers forming the bilayer. For each of the models analysed, two methods are used by us in order to analyse the rotational diffusion: (I) solution of the corresponding rotational diffusion equation for a single molecule, taking into account the boundary conditions imposed by the models, for the probability of the fluorescent molecule to be found with a given configuration at time t. Considering the distribution of molecules in the geometry proposed, we obtain the analytical expression for the fluorescence anisotropy, except for the cone geometry, for which the solution is obtained numerically; (II) numerical simulations of a restricted rotational random walk in the two geometries corresponding to the two models. The latter method may be very useful in the cases of low-symmetry geometries or of composed geometries.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Numerical studies of colloidal systems

The interplay of hydrodynamic and electrostatic forces is of great importance for the understanding of colloidal dispersions. Theoretical descriptions are often based on the so called standard electrokinetic model. This Mean Field approach combines the Stokes equation for the hydrodynamic flow field, the Poisson equation for electrostatics and a continuity equation describing the evolution of the ion concentration fields. In the first part of this thesis a new lattice method is presented in order to efficiently solve the set of non-linear equations for a charge-stabilized colloidal dispersion in the presence of an external electric field. Within this framework, the research is mainly focused on the calculation of the electrophoretic mobility. Since this transport coefficient is independent of the electric field only for small driving, the algorithm is based upon a linearization of the governing equations. The zeroth order is the well known Poisson-Boltzmann theory and the first order is a coupled set of linear equations. Furthermore, this set of equations is divided into several subproblems. A specialized solver for each subproblem is developed, and various tests and applications are discussed for every particular method. Finally, all solvers are combined in an iterative procedure and applied to several interesting questions, for example, the effect of the screening mechanism on the electrophoretic mobility or the charge dependence of the field-induced dipole moment and ion clouds surrounding a weakly charged sphere. In the second part a quantitative data analysis method is developed for a new experimental approach, known as "Total Internal Reflection Fluorescence Cross-Correlation Spectroscopy" (TIR-FCCS). The TIR-FCCS setup is an optical method using fluorescent colloidal particles to analyze the flow field close to a solid-fluid interface. The interpretation of the experimental results requires a theoretical model, which is usually the solution of a convection-diffusion equation. Since an analytic solution is not available due to the form of the flow field and the boundary conditions, an alternative numerical approach is presented. It is based on stochastic methods, i. e. a combination of a Brownian Dynamics algorithm and Monte Carlo techniques. Finally, experimental measurements for a hydrophilic surface are analyzed using this new numerical approach.

Preconditioning strategies for the numerical solution of convection-diffusion partial differential equations

Il trattamento numerico dell'equazione di convezione-diffusione con le relative condizioni al bordo, comporta la risoluzione di sistemi lineari algebrici di grandi dimensioni in cui la matrice dei coefficienti è non simmetrica. Risolutori iterativi basati sul sottospazio di Krylov sono ampiamente utilizzati per questi sistemi lineari la cui risoluzione risulta particolarmente impegnativa nel caso di convezione dominante. In questa tesi vengono analizzate alcune strategie di precondizionamento, atte ad accelerare la convergenza di questi metodi iterativi. Vengono confrontati sperimentalmente precondizionatori molto noti come ILU e iterazioni di tipo inner-outer flessibile. Nel caso in cui i coefficienti del termine di convezione siano a variabili separabili, proponiamo una nuova strategia di precondizionamento basata sull'approssimazione, mediante equazione matriciale, dell'operatore differenziale di convezione-diffusione. L'azione di questo nuovo precondizionatore sfrutta in modo opportuno recenti risolutori efficienti per equazioni matriciali lineari. Vengono riportati numerosi esperimenti numerici per studiare la dipendenza della performance dei diversi risolutori dalla scelta del termine di convezione, e dai parametri di discretizzazione.

Dynamic development of hydrofractures

Natürliche hydraulische Bruchbildung ist in allen Bereichen der Erdkruste ein wichtiger und stark verbreiteter Prozess. Sie beeinflusst die effektive Permeabilität und Fluidtransport auf mehreren Größenordnungen, indem sie hydraulische Konnektivität bewirkt. Der Prozess der Bruchbildung ist sowohl sehr dynamisch als auch hoch komplex. Die Dynamik stammt von der starken Wechselwirkung tektonischer und hydraulischer Prozesse, während sich die Komplexität aus der potentiellen Abhängigkeit der poroelastischen Eigenschaften von Fluiddruck und Bruchbildung ergibt. Die Bildung hydraulischer Brüche besteht aus drei Phasen: 1) Nukleation, 2) zeitabhängiges quasi-statisches Wachstum so lange der Fluiddruck die Zugfestigkeit des Gesteins übersteigt, und 3) in heterogenen Gesteinen der Einfluss von Lagen unterschiedlicher mechanischer oder sedimentärer Eigenschaften auf die Bruchausbreitung. Auch die mechanische Heterogenität, die durch präexistierende Brüche und Gesteinsdeformation erzeugt wird, hat großen Einfluß auf den Wachstumsverlauf. Die Richtung der Bruchausbreitung wird entweder durch die Verbindung von Diskontinuitäten mit geringer Zugfestigkeit im Bereich vor der Bruchfront bestimmt, oder die Bruchausbreitung kann enden, wenn der Bruch auf Diskontinuitäten mit hoher Festigkeit trifft. Durch diese Wechselwirkungen entsteht ein Kluftnetzwerk mit komplexer Geometrie, das die lokale Deformationsgeschichte und die Dynamik der unterliegenden physikalischen Prozesse reflektiert. rnrnNatürliche hydraulische Bruchbildung hat wesentliche Implikationen für akademische und kommerzielle Fragestellungen in verschiedenen Feldern der Geowissenschaften. Seit den 50er Jahren wird hydraulisches Fracturing eingesetzt, um die Permeabilität von Gas und Öllagerstätten zu erhöhen. Geländebeobachtungen, Isotopenstudien, Laborexperimente und numerische Analysen bestätigen die entscheidende Rolle des Fluiddruckgefälles in Verbindung mit poroelastischen Effekten für den lokalen Spannungszustand und für die Bedingungen, unter denen sich hydraulische Brüche bilden und ausbreiten. Die meisten numerischen hydromechanischen Modelle nehmen für die Kopplung zwischen Fluid und propagierenden Brüchen vordefinierte Bruchgeometrien mit konstantem Fluiddruck an, um das Problem rechnerisch eingrenzen zu können. Da natürliche Gesteine kaum so einfach strukturiert sind, sind diese Modelle generell nicht sonderlich effektiv in der Analyse dieses komplexen Prozesses. Insbesondere unterschätzen sie die Rückkopplung von poroelastischen Effekten und gekoppelte Fluid-Festgestein Prozesse, d.h. die Entwicklung des Porendrucks in Abhängigkeit vom Gesteinsversagen und umgekehrt.rnrnIn dieser Arbeit wird ein zweidimensionales gekoppeltes poro-elasto-plastisches Computer-Model für die qualitative und zum Teil auch quantitativ Analyse der Rolle lokalisierter oder homogen verteilter Fluiddrücke auf die dynamische Ausbreitung von hydraulischen Brüchen und die zeitgleiche Evolution der effektiven Permeabilität entwickelt. Das Programm ist rechnerisch effizient, indem es die Fluiddynamik mittels einer Druckdiffusions-Gleichung nach Darcy ohne redundante Komponenten beschreibt. Es berücksichtigt auch die Biot-Kompressibilität poröser Gesteine, die implementiert wurde um die Kontrollparameter in der Mechanik hydraulischer Bruchbildung in verschiedenen geologischen Szenarien mit homogenen und heterogenen Sedimentären Abfolgen zu bestimmen. Als Resultat ergibt sich, dass der Fluiddruck-Gradient in geschlossenen Systemen lokal zu Störungen des homogenen Spannungsfeldes führen. Abhängig von den Randbedingungen können sich diese Störungen eine Neuausrichtung der Bruchausbreitung zur Folge haben kann. Durch den Effekt auf den lokalen Spannungszustand können hohe Druckgradienten auch schichtparallele Bruchbildung oder Schlupf in nicht-entwässerten heterogenen Medien erzeugen. Ein Beispiel von besonderer Bedeutung ist die Evolution von Akkretionskeilen, wo die große Dynamik der tektonischen Aktivität zusammen mit extremen Porendrücken lokal starke Störungen des Spannungsfeldes erzeugt, die eine hoch-komplexe strukturelle Entwicklung inklusive vertikaler und horizontaler hydraulischer Bruch-Netzwerke bewirkt. Die Transport-Eigenschaften der Gesteine werden stark durch die Dynamik in der Entwicklung lokaler Permeabilitäten durch Dehnungsbrüche und Störungen bestimmt. Möglicherweise besteht ein enger Zusammenhang zwischen der Bildung von Grabenstrukturen und großmaßstäblicher Fluid-Migration. rnrnDie Konsistenz zwischen den Resultaten der Simulationen und vorhergehender experimenteller Untersuchungen deutet darauf hin, dass das beschriebene numerische Verfahren zur qualitativen Analyse hydraulischer Brüche gut geeignet ist. Das Schema hat auch Nachteile wenn es um die quantitative Analyse des Fluidflusses durch induzierte Bruchflächen in deformierten Gesteinen geht. Es empfiehlt sich zudem, das vorgestellte numerische Schema um die Kopplung mit thermo-chemischen Prozessen zu erweitern, um dynamische Probleme im Zusammenhang mit dem Wachstum von Kluftfüllungen in hydraulischen Brüchen zu untersuchen.

Convergence results for stochastic particle systems with social interaction

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.

Critical Review of Coupled Flux Formulations for Clay Membranes Based on Nonequilibrium Thermodynamics

Extensive research conducted over the past several decades has indicated that semipermeable membrane behavior (i.e., the ability of a porous medium to restrict the passage of solutes) may have a significant influence on solute migration through a wide variety of clay-rich soils, including both natural clay formations (aquitards, aquicludes) and engineered clay barriers (e.g., landfill liners and vertical cutoff walls). Restricted solute migration through clay membranes generally has been described using coupled flux formulations based on nonequilibrium (irreversible) thermodynamics. However, these formulations have differed depending on the assumptions inherent in the theoretical development, resulting in some confusion regarding the applicability of the formulations. Accordingly, a critical review of coupled flux formulations for liquid, current, and solutes through a semipermeable clay membrane under isothermal conditions is undertaken with the goals of explicitly resolving differences among the formulations and illustrating the significance of the differences from theoretical and practical perspectives. Formulations based on single-solute systems (i.e., uncharged solute), single-salt systems, and general systems containing multiple cations or anions are presented. Also, expressions relating the phenomenological coefficients in the coupled flux equations to relevant soil properties (e.g., hydraulic conductivity and effective diffusion coefficient) are summarized for each system. A major difference in the formulations is shown to exist depending on whether counter diffusion or salt diffusion is assumed. This difference between counter and salt diffusion is shown to affect the interpretation of values for the effective diffusion coefficient in a clay membrane based on previously published experimental data. Solute transport theories based on both counter and salt diffusion then are used to re-evaluate previously published column test data for the same clay membrane. The results indicate that, despite the theoretical inconsistency between the counter-diffusion assumption and the salt-diffusion conditions of the experiments, the predictive ability of solute transport theory based on the assumption of counter diffusion is not significantly different from that based on the assumption of salt diffusion, provided that the input parameters used in each theory are derived under the same assumption inherent in the theory. Nonetheless, salt-diffusion theory is fundamentally correct and, therefore, is more appropriate for problems involving salt diffusion in clay membranes. Finally, the fact that solute diffusion cannot occur in an ideal or perfect membrane is not explicitly captured in any of the theoretical expressions for total solute flux in clay membranes, but rather is generally accounted for via inclusion of an effective porosity, ne, or a restrictive tortuosity factor, tr, in the formulation of Fick's first law for diffusion. Both ne and tr have been correlated as a linear function of membrane efficiency. This linear correlation is supported theoretically by pore-scale modeling of solid-liquid interactions, but experimental support is limited. Additional data are needed to bolster the validity of the linear correlation for clay membranes.

Diffusion-driven transport in clayrock formations

Clay mineral-rich sedimentary formations are currently under investigation to evaluate their potential use as host formations for installation of deep underground disposal facilities for radioactive waste (e.g. Boom Clay (BE), Opalinus Clay (CH), Callovo-Oxfordian argillite (FR)). The ultimate safety of the corresponding repository concepts depends largely on the capacity of the host formation to limit the flux towards the biosphere of radionuclides (RN) contained in the waste to acceptably low levels. Data for diffusion-driven transfer in these formations shows extreme differences in the measured or modelled behaviour for various radionuclides, e. g. between halogen RN (Cl-36, I-129) and actinides (U-238,U-235, Np-237, Th-232, etc.), which result from major differences between RN of the effects on transport of two phenomena: diffusion and sorption. This paper describes recent research aimed at improving understanding of these two phenomena, focusing on the results of studies carried out during the EC Funmig IP on clayrocks from the above three formations and from the Boda formation (HU). Project results regarding phenomena governing water, cation and anion distribution and mobility in the pore volumes influenced by the negatively-charged surfaces of clay minerals show a convergence of the modelling results for behaviour at the molecular scale and descriptions based on electrical double layer models. Transport models exist which couple ion distribution relative to the clay-solution interface and differentiated diffusive characteristics. These codes are able to reproduce the main trends in behaviour observed experimentally, e.g. D-e(anion) < D-e(HTO) < D-e(cation) and D-e(anion) variations as a function of ionic strength and material density. These trends are also well-explained by models of transport through ideal porous matrices made up of a charged surface material. Experimental validation of these models is good as regards monovalent alkaline cations, in progress for divalent electrostatically-interacting cations (e.g. Sr2+) and still relatively poor for 'strongly sorbing', high K-d cations. Funmig results have clarified understanding of how clayrock mineral composition, and the corresponding organisation of mineral grain assemblages and their associated porosity, can affect mobile solute (anions, HTO) diffusion at different scales (mm to geological formation). In particular, advances made in the capacity to map clayrock mineral grain-porosity organisation at high resolution provide additional elements for understanding diffusion anisotropy and for relating diffusion characteristics measured at different scales. On the other hand, the results of studies focusing on evaluating the potential effects of heterogeneity on mobile species diffusion at the formation scale tend to show that there is a minimal effect when compared to a homogeneous property model. Finally, the results of a natural tracer-based study carried out on the Opalinus Clay formation increase confidence in the use of diffusion parameters measured on laboratory scale samples for predicting diffusion over geological time-space scales. Much effort was placed on improving understanding of coupled sorption-diffusion phenomena for sorbing cations in clayrocks. Results regarding sorption equilibrium in dispersed and compacted materials for weakly to moderately sorbing cations (Sr2+, Cs+, Co2+) tend to show that the same sorption model probably holds in both systems. It was not possible to demonstrate this for highly sorbing elements such as Eu(III) because of the extremely long times needed to reach equilibrium conditions, but there does not seem to be any clear reason why such elements should not have similar behaviour. Diffusion experiments carried out with Sr2+, Cs+ and Eu(III) on all of the clayrocks gave mixed results and tend to show that coupled diffusion-sorption migration is much more complex than expected, leading generally to greater mobility than that predicted by coupling a batch-determined K-d and Ficks law based on the diffusion behaviour of HTO. If the K-d measured on equivalent dispersed systems holds as was shown to be the case for Sr, Cs (and probably Co) for Opalinus Clay, these results indicate that these cations have a D-e value higher than HTO (up to a factor of 10 for Cs+). Results are as yet very limited for very moderate to strongly sorbing species (e.g. Co(II), Eu(III), Cu(II)) because of their very slow transfer characteristics. (C) 2011 Elsevier Ltd. All rights reserved.

Maximum principle preserving high order schemes for convection-dominated diffusion equations

The maximum principle is an important property of solutions to PDE. Correspondingly, it's of great interest for people to design a high order numerical scheme solving PDE with this property maintained. In this thesis, our particular interest is solving convection-dominated diffusion equation. We first review a nonconventional maximum principle preserving(MPP) high order finite volume(FV) WENO scheme, and then propose a new parametrized MPP high order finite difference(FD) WENO framework, which is generalized from the one solving hyperbolic conservation laws. A formal analysis is presented to show that a third order finite difference scheme with this parametrized MPP flux limiters maintains the third order accuracy without extra CFL constraint when the low order monotone flux is chosen appropriately. Numerical tests in both one and two dimensional cases are performed on the simulation of the incompressible Navier-Stokes equations in vorticity stream-function formulation and several other problems to show the effectiveness of the proposed method.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

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.

A proposed parameterization of interface discontinuity factors depending on neighborhood for pin-by-pin diffusion computations for LWR

There exists an interest in performing full core pin-by-pin computations for present nuclear reactors. In such type of problems the use of a transport approximation like the diffusion equation requires the introduction of correction parameters. Interface discontinuity factors can improve the diffusion solution to nearly reproduce a transport solution. Nevertheless, calculating accurate pin-by-pin IDF requires the knowledge of the heterogeneous neutron flux distribution, which depends on the boundary conditions of the pin-cell as well as the local variables along the nuclear reactor operation. As a consequence, it is impractical to compute them for each possible configuration. An alternative to generate accurate pin-by-pin interface discontinuity factors is to calculate reference values using zero-net-current boundary conditions and to synthesize afterwards their dependencies on the main neighborhood variables. In such way the factors can be accurately computed during fine-mesh diffusion calculations by correcting the reference values as a function of the actual environment of the pin-cell in the core. In this paper we propose a parameterization of the pin-by-pin interface discontinuity factors allowing the implementation of a cross sections library able to treat the neighborhood effect. First results are presented for typical PWR configurations.