995 resultados para Generalized Solution


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The main feature of partition of unity methods such as the generalized or extended finite element method is their ability of utilizing a priori knowledge about the solution of a problem in the form of enrichment functions. However, analytical derivation of enrichment functions with good approximation properties is mostly limited to two-dimensional linear problems. This paper presents a procedure to numerically generate proper enrichment functions for three-dimensional problems with confined plasticity where plastic evolution is gradual. This procedure involves the solution of boundary value problems around local regions exhibiting nonlinear behavior and the enrichment of the global solution space with the local solutions through the partition of unity method framework. This approach can produce accurate nonlinear solutions with a reduced computational cost compared to standard finite element methods since computationally intensive nonlinear iterations can be performed on coarse global meshes after the creation of enrichment functions properly describing localized nonlinear behavior. Several three-dimensional nonlinear problems based on the rate-independent J (2) plasticity theory with isotropic hardening are solved using the proposed procedure to demonstrate its robustness, accuracy and computational efficiency.

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The topographical character of conical intersections (CIs)-either sloped or peaked-has played a fundamental and important role in the discussion of the efficiency of CIs as photochemical "funnels." Here this perspective is employed in connection with a recent study of a model protonated Schiff base (PSB) cis to trans photoisomerization in solution [Malhado et al., J. Phys. Chem. A 115, 3720 (2011)]. In that study, the calculated reduced photochemical quantum yield for the successful production of trans product versus cis reactant in acetonitrile solvent compared to water was interpreted in terms of a dynamical solvent effect related to the dominance, for the acetonitrile case, of S-1 to S-0 nonadiabatic transitions prior to the reaching the seam of CIs. The solvent influence on the quantum yield is here re-examined in the sloped/peaked CI topographical perspective via conversion of the model's two PSB internal coordinates and a nonequilibrium solvent coordinate into an effective branching space description, which is then used to re-analyze the generalized Langevin equation/surface hopping results. The present study supports the original interpretation and enriches it in terms of topographical detail. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4754505]

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Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).

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Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

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Non-parametric belief propagation (NBP) is a well-known message passing method for cooperative localization in wireless networks. However, due to the over-counting problem in the networks with loops, NBP’s convergence is not guaranteed, and its estimates are typically less accurate. One solution for this problem is non-parametric generalized belief propagation based on junction tree. However, this method is intractable in large-scale networks due to the high-complexity of the junction tree formation, and the high-dimensionality of the particles. Therefore, in this article, we propose the non-parametric generalized belief propagation based on pseudo-junction tree (NGBP-PJT). The main difference comparing with the standard method is the formation of pseudo-junction tree, which represents the approximated junction tree based on thin graph. In addition, in order to decrease the number of high-dimensional particles, we use more informative importance density function, and reduce the dimensionality of the messages. As by-product, we also propose NBP based on thin graph (NBP-TG), a cheaper variant of NBP, which runs on the same graph as NGBP-PJT. According to our simulation and experimental results, NGBP-PJT method outperforms NBP and NBP-TG in terms of accuracy, computational, and communication cost in reasonably sized networks.

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A generalized Lévêque solution is presented for the conjugate fluid–fluid problem that arises in the thermal entrance region of laminar counterflow heat exchangers. The analysis, carried out for constant property fluids, assumes that the Prandtl and Peclet numbers are both large compared to unity, and neglects axial conduction both in the fluids and in the plate, assumed to be thermally thin. Under these conditions, the thermal entrance region admits an asymptotic self-similar description where the temperature varies as a power ϳ of the axial distance, with the particularity that the self-similarity exponent must be determined as an eigenvalue by solving a transcendental equation arising from the requirement of continuity of heat fluxes at the heat conducting wall. Specifically, the analysis reveals that j depends only on the lumped parameter ƙ = (A2/A1)1/3 (α1/α2)1/3(k2/k1), defined in terms of the ratios of the wall velocity gradients, A, thermal diffusivities, α i, and thermal conductivities,k i, of the fluids entering, 1, and exiting, 2, the heat exchanger. Moreover, it is shown that for large (small) values of K solution reduces to the classical first (second) Lévêque solution. Closed-form analytical expressions for the asymptotic temperature distributions and local heat-transfer rate in the thermal entrance region are given and compared with numerical results in the counterflow parallel-plate configuration, showing very good agreement in all cases.

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In this paper we address the new reduction method called Proper Generalized Decomposition (PGD) which is a discretization technique based on the use of separated representation of the unknown fields, specially well suited for solving multidimensional parametric equations. In this case, it is applied to the solution of dynamics problems. We will focus on the dynamic analysis of an one-dimensional rod with a unit harmonic load of frequency (ω) applied at a point of interest. In what follows, we will present the application of the methodology PGD to the problem in order to approximate the displacement field as the sum of the separated functions. We will consider as new variables of the problem, parameters models associated with the characteristic of the materials, in addition to the frequency. Finally, the quality of the results will be assessed based on an example.

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La evaluación de las prestaciones de las embarcaciones a vela ha constituido un objetivo para ingenieros navales y marinos desde los principios de la historia de la navegación. El conocimiento acerca de estas prestaciones, ha crecido desde la identificación de los factores clave relacionados con ellas(eslora, estabilidad, desplazamiento y superficie vélica), a una comprensión más completa de las complejas fuerzas y acoplamientos involucrados en el equilibrio. Junto con este conocimiento, la aparición de los ordenadores ha hecho posible llevar a cabo estas tareas de una forma sistemática. Esto incluye el cálculo detallado de fuerzas, pero también, el uso de estas fuerzas junto con la descripción de una embarcación a vela para la predicción de su comportamiento y, finalmente, sus prestaciones. Esta investigación tiene como objetivo proporcionar una definición global y abierta de un conjunto de modelos y reglas para describir y analizar este comportamiento. Esto se lleva a cabo sin aplicar restricciones en cuanto al tipo de barco o cálculo, sino de una forma generalizada, de modo que sea posible resolver cualquier situación, tanto estacionaria como en el dominio del tiempo. Para ello se comienza con una definición básica de los factores que condicionan el comportamiento de una embarcación a vela. A continuación se proporciona una metodología para gestionar el uso de datos de diferentes orígenes para el cálculo de fuerzas, siempre con el la solución del problema como objetivo. Esta última parte se plasma en un programa de ordenador, PASim, cuyo propósito es evaluar las prestaciones de diferentes ti pos de embarcaciones a vela en un amplio rango de condiciones. Varios ejemplos presentan diferentes usos de PASim con el objetivo de ilustrar algunos de los aspectos discutidos a lo largo de la definición del problema y su solución . Finalmente, se presenta una estructura global de cara a proporcionar una representación virtual de la embarcación real, en la cual, no solo e l comportamiento sino también su manejo, son cercanos a la experiencia de los navegantes en el mundo real. Esta estructura global se propone como el núcleo (un motor de software) de un simulador físico para el que se proporciona una especificación básica. ABSTRACT The assessment of the performance of sailing yachts, and ships in general, has been an objective for naval architects and sailors since the beginning of the history of navigation. The knowledge has grown from identifying the key factors that influence performance(length, stability, displacement and sail area), to a much more complete understanding of the complex forces and couplings involved in the equilibrium. Along with this knowledge, the advent of computers has made it possible to perform the associated tasks in a systematic way. This includes the detailed calculation of forces, but also the use of those forces, along with the description of a sailing yacht, to predict its behavior, and ultimately, its performance. The aim of this investigation is to provide a global and open definition of a set of models and rules to describe and analyze the behavior of a sailing yacht. This is done without applying any restriction to the type of yacht or calculation, but rather in a generalized way, capable of solving any possible situation, whether it is in a steady state or in the time domain. First, the basic definition of the factors that condition the behavior of a sailing yacht is given. Then, a methodology is provided to assist with the use of data from different origins for the calculation of forces, always aiming towards the solution of the problem. This last part is implemented as a computational tool, PASim, intended to assess the performance of different types of sailing yachts in a wide range of conditions. Several examples then present different uses of PASim, as a way to illustrate some of the aspects discussed throughout the definition of the problem and its solution. Finally, a global structure is presented to provide a general virtual representation of the real yacht, in which not only the behavior, but also its handling is close to the experience of the sailors in the real world. This global structure is proposed as the core (a software engine) of a physical yacht simulator, for which a basic specification is provided.

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The study of passive scalar transport in a turbulent velocity field leads naturally to the notion of generalized flows, which are families of probability distributions on the space of solutions to the associated ordinary differential equations which no longer satisfy the uniqueness theorem for ordinary differential equations. Two most natural regularizations of this problem, namely the regularization via adding small molecular diffusion and the regularization via smoothing out the velocity field, are considered. White-in-time random velocity fields are used as an example to examine the variety of phenomena that take place when the velocity field is not spatially regular. Three different regimes, characterized by their degrees of compressibility, are isolated in the parameter space. In the regime of intermediate compressibility, the two different regularizations give rise to two different scaling behaviors for the structure functions of the passive scalar. Physically, this means that the scaling depends on Prandtl number. In the other two regimes, the two different regularizations give rise to the same generalized flows even though the sense of convergence can be very different. The “one force, one solution” principle is established for the scalar field in the weakly compressible regime, and for the difference of the scalar in the strongly compressible regime, which is the regime of inverse cascade. Existence and uniqueness of an invariant measure are also proved in these regimes when the transport equation is suitably forced. Finally incomplete self similarity in the sense of Barenblatt and Chorin is established.

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The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.

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The Perk-Schultz model may be expressed in terms of the solution of the Yang-Baxter equation associated with the fundamental representation of the untwisted affine extension of the general linear quantum superalgebra U-q (gl(m/n)], with a multiparametric coproduct action as given by Reshetikhin. Here, we present analogous explicit expressions for solutions of the Yang-Baxter equation associated with the fundamental representations of the twisted and untwisted affine extensions of the orthosymplectic quantum superalgebras U-q[osp(m/n)]. In this manner, we obtain generalizations of the Perk-Schultz model.

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In this work the solution of a class of capital investment problems is considered within the framework of mathematical programming. Upon the basis of the net present value criterion, the problems in question are mainly characterized by the fact that the cost of capital is defined as a non-decreasing function of the investment requirements. Capital rationing and some cases of technological dependence are also included, this approach leading to zero-one non-linear programming problems, for which specifically designed solution procedures supported by a general branch and bound development are presented. In the context of both this development and the relevant mathematical properties of the previously mentioned zero-one programs, a generalized zero-one model is also discussed. Finally,a variant of the scheme, connected with the search sequencing of optimal solutions, is presented as an alternative in which reduced storage limitations are encountered.

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This work was supported by the Bulgarian National Science Fund under grant BY-TH-105/2005.

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2000 Mathematics Subject Classification: Primary 46F25, 26A33; Secondary: 46G20

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2000 Mathematics Subject Classification: 47H04, 65K10.