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Nonlinear Problems (nonlinear + problem)
Selected AbstractsOscillatory flow of a fourth-order fluidINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 3 2009T. Hayat Abstract This study deals with the incompressible flow of a fourth-order fluid over a porous plate oscillating in its own plane. Numerical solution of the nonlinear problem governing the flow is given. The influence of various parameters of interest on the velocity distribution is shown and discussed with the help of several graphs. Copyright © 2008 John Wiley & Sons, Ltd. [source] Nonlinear predictive control of smooth nonlinear systems based on Volterra models.INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 16 2010Application to a pilot plant Abstract There is a large demand to apply nonlinear algorithms to control nonlinear systems. With algorithms considering the process nonlinearities, better control performance is expected in the whole operating range than with linear control algorithms. Three predictive control algorithms based on a Volterra model are considered. The iterative predictive control algorithm to solve the complete nonlinear problem uses the non-autoregressive Volterra model calculated from the identified autoregressive Volterra model. Two algorithms for a reduced nonlinear optimization problem are considered for the unconstrained case, where an analytic control expression can be given. The performance of the three algorithms is analyzed and compared for reference signal tracking and disturbance rejection. The algorithms are applied and compared in simulation to control a Wiener model, and are used for real-time control of a chemical pilot plant. Copyright © 2009 John Wiley & Sons, Ltd. [source] SOLID FOODS FREEZE-DRYING SIMULATION AND EXPERIMENTAL DATAJOURNAL OF FOOD PROCESS ENGINEERING, Issue 2 2005S. KHALLOUFI ABSTRACT This article presents a mathematical model describing the unsteady heat and mass transfer during the freeze drying of biological materials. The model was built from the mass and energy balances in the dried and frozen regions of the material undergoing freeze drying. A set of coupled nonlinear partial differential equations permitted the description of the temperature and pressure profiles, together with the position of the sublimation interface. These equations were transformed to a finite element scheme and numerically solved using the Newton-Raphson approach to represent the nonlinear problem and the interface position. Most parameters involved in the model (i.e., thermal conductivity, specific heat, density, heat and mass transfer coefficients etc.) were obtained from experimental data cited in the literature. The dehydration kinetics and the temperature profiles of potato and apple slabs were experimentally determined during freeze drying. The simulation results agreed closely with the water content experimental data. The prediction of temperature profiles within the solid was, however, less accurate. [source] First-Order Schemes in the Numerical Quantization MethodMATHEMATICAL FINANCE, Issue 1 2003V. Bally The numerical quantization method is a grid method that relies on the approximation of the solution to a nonlinear problem by piecewise constant functions. Its purpose is to compute a large number of conditional expectations along the path of the associated diffusion process. We give here an improvement of this method by describing a first-order scheme based on piecewise linear approximations. Main ingredients are correction terms in the transition probability weights. We emphasize the fact that in the case of optimal quantization, many of these correcting terms vanish. We think that this is a strong argument to use it. The problem of pricing and hedging American options is investigated and a priori estimates of the errors are proposed. [source] Application of Superposition with Nonlinear Head-Dependent FluxesGROUND WATER, Issue 2 2008Timothy Durbin While superposition is commonly used to address linear ground water problems, it can also be used to address certain nonlinear problems. In particular, it can be used to address problems with nonlinear head-dependent fluxes, where the problem can be separated conveniently into steady-state and transient-state components. Superposition can be used to simulate the transient-state head changes independently from the steady-state heads. The problems addressable by superposition include phreatophyte discharges, stream-aquifer interactions, spring discharges, and drain discharges. Each of these represents a nonlinear head-dependent flux, where the flux depends on the elevation of the land surface or some other feature. Superposition is applied by referencing elevations to the local steady-state water table and by imposing the negative of the steady-state flux on the transient-state problem. [source] An interpolation-based local differential quadrature method to solve partial differential equations using irregularly distributed nodesINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 7 2008Hang Ma Abstract To circumvent the constraint in application of the conventional differential quadrature (DQ) method that the solution domain has to be a regular region, an interpolation-based local differential quadrature (LDQ) method is proposed in this paper. Instead of using regular nodes placed on mesh lines in the DQ method (DQM), irregularly distributed nodes are employed in the LDQ method. That is, any spatial derivative at a nodal point is approximated by a linear weighted sum of the functional values of irregularly distributed nodes in the local physical domain. The feature of the new approach lies in the fact that the weighting coefficients are determined by the quadrature rule over the irregularly distributed local supporting nodes with the aid of nodal interpolation techniques developed in the paper. Because of this distinctive feature, the LDQ method can be consistently applied to linear and nonlinear problems and is really a mesh-free method without the limitation in the solution domain of the conventional DQM. The effectiveness and efficiency of the method are validated by two simple numerical examples by solving boundary-value problems of a linear and a nonlinear partial differential equation. Copyright © 2007 John Wiley & Sons, Ltd. [source] Krylov precise time-step integration methodINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 11 2006T. C. Fung Abstract An efficient precise time-step integration (PTI) algorithm to solve large-scale transient problems is presented in this paper. The Krylov subspace method and the Padé approximations are applied to modify the original PTI algorithm in order to improve the computational efficiency. Both the stability and accuracy characteristics of the resultant algorithms are investigated. The efficiency can be further improved by expanding the dimension to avoid the computation of the particular solutions. The present algorithm can also be extended to tackle nonlinear problems without difficulty. Two numerical examples are given to illustrate the highly accurate and efficient algorithm. Copyright © 2006 John Wiley & Sons, Ltd. [source] PID adaptive control of incremental and arclength continuation in nonlinear applicationsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 11 2009A. M. P. Valli Abstract A proportional-integral-derivative (PID) control approach is developed, implemented and investigated numerically in conjunction with continuation techniques for nonlinear problems. The associated algorithm uses PID control to adapt parameter stepsize for branch,following strategies such as those applicable to turning point and bifurcation problems. As representative continuation strategies, incremental Newton, Euler,Newton and pseudo-arclength continuation techniques are considered. Supporting numerical experiments are conducted for finite element simulation of the ,driven cavity' Navier,Stokes benchmark over a range in Reynolds number, the classical Bratu turning point problem over a reaction parameter range, and for coupled fluid flow and heat transfer over a range in Rayleigh number. Computational performance using PID stepsize control in conjunction with inexact Newton,Krylov solution for coupled flow and heat transfer is also examined for a 3D test case. Copyright © 2009 John Wiley & Sons, Ltd. [source] Implicit symmetrized streamfunction formulations of magnetohydrodynamicsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 11 2008K. S. Kang Abstract We apply the finite element method to the classic tilt instability problem of two-dimensional, incompressible magnetohydrodynamics, using a streamfunction approach to enforce the divergence-free conditions on the magnetic and velocity fields. We compare two formulations of the governing equations, the standard one based on streamfunctions and a hybrid formulation with velocities and magnetic field components. We use a finite element discretization on unstructured meshes and an implicit time discretization scheme. We use the PETSc library with index sets for parallelization. To solve the nonlinear problems on each time step, we compare two nonlinear Gauss-Seidel-type methods and Newton's method with several time-step sizes. We use GMRES in PETSc with multigrid preconditioning to solve the linear subproblems within the nonlinear solvers. We also study the scalability of this simulation on a cluster. Copyright © 2008 John Wiley & Sons, Ltd. [source] An optimal spectrum-balancing algorithm for digital subscriber lines based on particle swarm optimizationINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 9 2008Meiqin Tang Abstract This paper presents a new algorithm for optimal spectrum balancing in modern digital subscriber line (DSL) systems using particle swarm optimization (PSO). In DSL, crosstalk is one of the major performance bottlenecks, therefore various dynamic spectrum management algorithms have been proposed to reduce excess crosstalks among users by dynamically optimizing transmission power spectra. In fact, the objective function in the spectrum optimization problem is always nonconcave. PSO is a new evolution algorithm based on the movement and intelligence of swarms looking for the most fertile feeding location, which can solve discontinuous, nonconvex and nonlinear problems efficiently. The proposed algorithm optimizes the weighted rate sum. These weights allow the system operator to place differing qualities of service or importance levels on each user, which makes it possible for the system to avoid the selfish-optimum. We can show that the proposed algorithm converges to the global optimal solutions. Simulation results demonstrate that our algorithm can guarantee fast convergence within a few iterations and solve the nonconvex optimization problems efficiently. Copyright © 2008 John Wiley & Sons, Ltd. [source] Global optimization of mixed-integer nonlinear problemsAICHE JOURNAL, Issue 9 2000C. S. Adjiman Two novel deterministic global optimization algorithms for nonconvex mixed-integer problems (MINLPs) are proposed, using the advances of the ,BB algorithm for nonconvex NLPs of Adjiman et al. The special structure mixed-integer ,BB algorithm (SMIN-,BB) addresses problems with nonconvexities in the continuous variables and linear and mixed-bilinear participation of the binary variables. The general structure mixed-integer ,BB algorithm (GMIN-,BB) is applicable to a very general class of problems for which the continuous relaxation is twice continuously differentiable. Both algorithms are developed using the concepts of branch-and-bound, but they differ in their approach to each of the required steps. The SMIN-,BB algorithm is based on the convex underestimation of the continuous functions, while the GMIN-,BB algorithm is centered around the convex relaxation of the entire problem. Both algorithms rely on optimization or interval-based variable-bound updates to enhance efficiency. A series of medium-size engineering applications demonstrates the performance of the algorithms. Finally, a comparison of the two algorithms on the same problems highlights the value of algorithms that can handle binary or integer variables without reformulation. [source] Multiscale methods for elliptic homogenization problems,NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS, Issue 2 2006Zhangxin ChenArticle first published online: 10 JUN 200 Abstract In this article we study two families of multiscale methods for numerically solving elliptic homogenization problems. The recently developed multiscale finite element method [Hou and Wu, J Comp Phys 134 (1997), 169,189] captures the effect of microscales on macroscales through modification of finite element basis functions. Here we reformulate this method that captures the same effect through modification of bilinear forms in the finite element formulation. This new formulation is a general approach that can handle a large variety of differential problems and numerical methods. It can be easily extended to nonlinear problems and mixed finite element methods, for example. The latter extension is carried out in this article. The recently introduced heterogeneous multiscale method [Engquist and Engquist, Comm Math Sci 1 (2003), 87,132] is designed for efficient numerical solution of problems with multiscales and multiphysics. In the second part of this article, we study this method in mixed form (we call it the mixed heterogeneous multiscale method). We present a detailed analysis for stability and convergence of this new method. Estimates are obtained for the error between the homogenized and numerical multiscale solutions. Strategies for retrieving the microstructural information from the numerical solution are provided and analyzed. Relationship between the multiscale finite element and heterogeneous multiscale methods is discussed. © 2005 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2006 [source] Minimal-power control of hydrogen evolution reactionsOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 2 2010Vicente Costanza Abstract An integral approach to solve finite-horizon optimal control problems posed by set-point changes in electrochemical hydrogen reactions is developed. The methodology extends to nonlinear problems with regular, convex Hamiltonians that cannot be explicitly minimized, i.e. where the functional dependence of the H -minimal control on the state and costate variables is not known. The Lagrangian functions determining trajectory costs will not have special restrictions other than positiveness, but for simplicity the final penalty will be assumed quadratic. The answer to the problem is constructed through the solution to a coupled system of three first-order quasi-linear partial differential equations (PDEs) for the missing boundary conditions x(T), ,(0) of the Hamiltonian equations, and for the final value of the control variable u(T). The independent variables of these PDEs are the time-duration T of the process and the characteristic parameter S of the final penalty. The solution provides information on the whole (T, S)-family of control problems, which can be used not only to construct the individual optimal control strategies online, but also for global design purposes. Copyright © 2009 John Wiley & Sons, Ltd. [source] Adaptive finite element procedures for elastoplastic problems at finite strainsPROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2003A. Koch Dipl.-Ing. A major difficulty in the context of adaptive analysis of geometrically nonlinear problems is to provide a robust remeshing procedure that accounts both for the error caused by the spatial discretization and for the error due to the time discretization. For stability problems, such as strain localization and necking, it is essential to provide a step,size control in order to get a robust algorithm for the solution of the boundary value problem. For this purpose we developed an easy to implement step,size control algorithm. In addition we will consider possible a posteriori error indicators for the spatial error distribution of elastoplastic problems at finite strains. This indicator is adopted for a density,function,based adaptive remeshing procedure. Both error indicators are combined for the adaptive analysis in time and space. The performance of the proposed method is documented by means of representative numerical examples. [source] Application of support vector regression for developing soft sensors for nonlinear processes,THE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 5 2010Saneej B. Chitralekha Abstract The field of soft sensor development has gained significant importance in the recent past with the development of efficient and easily employable computational tools for this purpose. The basic idea is to convert the information contained in the input,output data collected from the process into a mathematical model. Such a mathematical model can be used as a cost efficient substitute for hardware sensors. The Support Vector Regression (SVR) tool is one such computational tool that has recently received much attention in the system identification literature, especially because of its successes in building nonlinear blackbox models. The main feature of the algorithm is the use of a nonlinear kernel transformation to map the input variables into a feature space so that their relationship with the output variable becomes linear in the transformed space. This method has excellent generalisation capabilities to high-dimensional nonlinear problems due to the use of functions such as the radial basis functions which have good approximation capabilities as kernels. Another attractive feature of the method is its convex optimization formulation which eradicates the problem of local minima while identifying the nonlinear models. In this work, we demonstrate the application of SVR as an efficient and easy-to-use tool for developing soft sensors for nonlinear processes. In an industrial case study, we illustrate the development of a steady-state Melt Index soft sensor for an industrial scale ethylene vinyl acetate (EVA) polymer extrusion process using SVR. The SVR-based soft sensor, valid over a wide range of melt indices, outperformed the existing nonlinear least-square-based soft sensor in terms of lower prediction errors. In the remaining two other case studies, we demonstrate the application of SVR for developing soft sensors in the form of dynamic models for two nonlinear processes: a simulated pH neutralisation process and a laboratory scale twin screw polymer extrusion process. A heuristic procedure is proposed for developing a dynamic nonlinear-ARX model-based soft sensor using SVR, in which the optimal delay and orders are automatically arrived at using the input,output data. Le domaine du développement des capteurs logiciels a récemment gagné en importance avec la création d'outils de calcul efficaces et facilement utilisables à cette fin. L'idée de base est de convertir l'information obtenue dans les données d'entrée et de sortie recueillies à partir du processus dans un modèle mathématique. Un tel modèle mathématique peut servir de solution de rechange économique pour les capteurs matériels. L'outil de régression par machine à vecteur de support (RMVS) constitue un outil de calcul qui a récemment été l'objet de beaucoup d'attention dans la littérature des systèmes d'identification, surtout en raison de ses succès dans la création de modèles de boîte noire non linéaires. Dans ce travail, nous démontrons l'application de la RMVS comme outil efficace et facile à utiliser pour la création de capteurs logiciels pour les procédés non linéaires. Dans une étude de cas industrielle, nous illustrons le développement d'un capteur logiciel à indice de fluidité à état permanent pour un processus d'extrusion du polymère d'acétate de vinyle-éthylène à l'échelle industrielle en utilisant la RMVS. Le capteur logiciel fondé sur la RMVS, valide sur une vaste gamme d'indices de fluidité, a surclassé le capteur logiciel fondé sur les moindres carrés non linéaires existant en matière d'erreurs de prédiction plus faibles. Dans les deux autres études de cas, nous démontrons l'application de la RMVS pour la création de capteurs logiciels sous la forme de modèles dynamiques pour deux procédés non linéaires: un processus de neutralisation du pH simulé et un processus d'extrusion de polymère à deux vis à l'échelle laboratoire. Une procédure heuristique est proposée pour la création d'un capteur logiciel fondé sur un modèle ARX non linéaire dynamique en utilisant la RMVS, dans lequel on atteint automatiquement le délai optimal et les ordres en utilisant les données d'entrée et de sortie. [source] Fault isolation in nonlinear systems with structured partial principal component analysis and clustering analysisTHE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 3 2000Yunbing Huang Abstract Partial principal component analysis (PCA) and parity relations are proven to be useful methods in fault isolation. To overcome the limitation of applying partial PCA to nonlinear problems, a new approach utilizing clustering analysis is proposed. By dividing a partial data set into smaller subsets, one can build more accurate PCA models with fewer principal components, and isolate faults with higher precision. Simulations on a 2 × 2 nonlinear system and the Tennessee Eastman (TE) process show the advantages of using the clustered partial PCA method over other nonlinear approaches. L'analyse des principaux constituants partielle et les relations de parité s'avèrent des méthodes utiles pour isoler les défaillances. Mais étant donné les limites d'application de l'analyse partielle des principaux constituants, on propose une nouvelle méthode reposant sur l'analyse de la formation des grappes. En divisant un jeu de données partielles en plusieurs sous-groupes plus petits, on peut créer des modèles d'analyse des principaux constituants plus précis avec un nombre de constituants moins importants et isoler les défaillances avec une meilleure précision. Les simulations sur un système non linéaire 2 × 2 et le procédé Tennessee Eastman (TE) montrent les avantages de la méthode d'analyse des principaux constituants partielle par grappes par rapport aux autres methodes non linéaires. [source] | |||||||||||||||||||||||||