Search results for "Numerical Analysis"

showing 10 items of 883 documents

Direct Numerical Methods for Optimal Control Problems

2003

Development of interior point methods for linear and quadratic programming problems occurred during the 1990’s. Because of their simplicity and their convergence properties, interior point methods are attractive solvers for such problems. Moreover, extensions have been made to more general convex programming problems.

Mathematical optimizationComputer scienceNumerical analysisConjugate gradient methodConvergence (routing)Convex optimizationMathematicsofComputing_NUMERICALANALYSISPositive-definite matrixQuadratic programmingOptimal controlInterior point method
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Numerical Simulation of a Contractivity Based Multiscale Cancer Invasion Model

2017

We present a problem-suited numerical method for a particularly challenging cancer invasion model. This model is a multiscale haptotaxis advection-reaction-diffusion system that describes the macroscopic dynamics of two types of cancer cells coupled with microscopic dynamics of the cells adhesion on the extracellular matrix. The difficulties to overcome arise from the non-constant advection and diffusion coefficients, a time delay term, as well as stiff reaction terms.

Mathematical optimizationComputer simulationQuantitative Biology::Tissues and OrgansNumerical analysisDynamics (mechanics)medicineCancerStatistical physicsDiffusion (business)medicine.diseaseHaptotaxisQuantitative Biology::Cell BehaviorMathematics
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Performance modeling of epidemic routing

2006

In this paper, we develop a rigorous, unified framework based on ordinary differential equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study of Markovian models is quite complex and numerical solution impractical for large networks, the corresponding ODE models yield closed-form expressions for several performance metrics of interest, and a numerical solution complexity that does not increase with the number of nodes. Using this ODE approach, we investigate how resources such as buffer space and the number of copies made for a packet can be tra…

Mathematical optimizationComputingMethodologies_SIMULATIONANDMODELINGComputer Networks and CommunicationsDifferential equationComputer scienceWireless ad hoc networkNetwork packetNumerical analysisMathematicsofComputing_NUMERICALANALYSISOdeMarkov processMarkov modelsymbols.namesakeOrdinary differential equationMetric (mathematics)symbolsRouting (electronic design automation)ScalingSimulation
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Functional A Posteriori Error Estimates for Time-Periodic Parabolic Optimal Control Problems

2015

This article is devoted to the a posteriori error analysis of multiharmonic finite element approximations to distributed optimal control problems with time-periodic state equations of parabolic type. We derive a posteriori estimates of the functional type, which are easily computable and provide guaranteed upper bounds for the state and co-state errors as well as for the cost functional. These theoretical results are confirmed by several numerical tests that show high efficiency of the a posteriori error bounds. peerReviewed

Mathematical optimizationControl and OptimizationMathematicsofComputing_NUMERICALANALYSISFinite element approximations010103 numerical & computational mathematicsType (model theory)01 natural sciencesparabolic time-periodic optimal control problemsError analysisFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisNumerical testsfunctional a posteriori error estimates0101 mathematicsMathematics - Optimization and Control49N20 35Q61 65M60 65F08Mathematicsta113Time periodicta111Numerical Analysis (math.NA)State (functional analysis)Optimal controlComputer Science Applications010101 applied mathematicsOptimization and Control (math.OC)multiharmonic finite element methodsSignal ProcessingA priori and a posterioriAnalysisNumerical Functional Analysis and Optimization
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Error Estimates for a Class of Elliptic Optimal Control Problems

2016

In this article, functional type a posteriori error estimates are presented for a certain class of optimal control problems with elliptic partial differential equation constraints. It is assumed that in the cost functional the state is measured in terms of the energy norm generated by the state equation. The functional a posteriori error estimates developed by Repin in the late 1990s are applied to estimate the cost function value from both sides without requiring the exact solution of the state equation. Moreover, a lower bound for the minimal cost functional value is derived. A meaningful error quantity coinciding with the gap between the cost functional values of an arbitrary admissible …

Mathematical optimizationControl and OptimizationNumerical analysis010102 general mathematicsta111010103 numerical & computational mathematicsOptimal control01 natural sciencesUpper and lower boundsComputer Science ApplicationsExact solutions in general relativityElliptic partial differential equationerror estimatesNorm (mathematics)Signal ProcessingA priori and a posterioriNumerical testselliptic optimal control problems0101 mathematicsAnalysisMathematics
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A New Numerical Method for Axisymmetrical Forming Processes

1987

Summary In this paper a numerical method for the analysis of axisymmetrical forming processes is proposed. This method represents the last development of a previous one which allows to solve forming problems in plane strain condition. The proposed model is baaed on the finite element discretization and on the linearization of the yield surface which leads to solve a LP problem. Two different examples of application, concerning the upsetting of a cylinder and of a hollow disk are reported.

Mathematical optimizationDiscretizationLinearizationYield surfaceMechanical EngineeringNumerical analysisForming processesApplied mathematicsCylinderDevelopment (differential geometry)Industrial and Manufacturing EngineeringFinite element methodMathematicsCIRP Annals
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A numerical method for imaging of biological microstructures by VHF waves

2014

Imaging techniques give a fundamental support to medical diagnostics during the pathology discovery as well as for the characterization of bio-medical structures. The imaging methods involve electromagnetic waves in a frequency range that spans from some Hz to GHz and over. Most of these methods involve ionizing waves and scanning of a large human body area even if only a focused inspection is needed. In this paper, a numerical method to evaluate the shape of microstructures for application in the medical field, with a very low invasiveness for the human body, is proposed. In particular, the tooth’s root canal is considered. In fact, this is one of the hot topics in the endodontic procedure…

Mathematical optimizationMedical diagnosticAcousticsRoot canalElectromagnetic radiationSettore MAT/08 - Analisi NumericaRobustness (computer science)medicineMethod of MomentLevenberg–Marquardt methodMethod of MomentsMathematicsNon-linear modelApplied MathematicsNumerical analysisBiological microstructureNon ionizing waveInverse problemMicrostructureMagnetic fieldSettore ING-IND/31 - ElettrotecnicaComputational Mathematicsmedicine.anatomical_structureLevenberg-Marquardt methodInverse problemSettore MED/36 - Diagnostica Per Immagini E RadioterapiaJournal of Computational and Applied Mathematics
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Error bounds for a convexity-preserving interpolation and its limit function

2008

AbstractError bounds between a nonlinear interpolation and the limit function of its associated subdivision scheme are estimated. The bounds can be evaluated without recursive subdivision. We show that this interpolation is convexity preserving, as its associated subdivision scheme. Finally, some numerical experiments are presented.

Mathematical optimizationNonlinear subdivision schemesbusiness.industryApplied MathematicsNumerical analysisMathematicsofComputing_NUMERICALANALYSISStairstep interpolationComputer Science::Computational GeometryConvexityMultivariate interpolationComputational MathematicsError boundsComputer Science::GraphicsNearest-neighbor interpolationTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONApplied mathematicsComputer Science::Symbolic ComputationConvexity preservingbusinessSpline interpolationSubdivisionInterpolationMathematicsComputingMethodologies_COMPUTERGRAPHICSJournal of Computational and Applied Mathematics
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Numerical solution of a multi-class model for batch settling in water resource recovery facilities

2017

In Torfs et al. (2017) a new unified framework to model settling tanks in water resource recovery facilities was proposed providing a set of partial differential equations (PDEs) modelling different settling unit processes in wastewater treatment such as primary and secondary settling tanks (PSTs and SSTs). The extension to a multi-class framework to deal with the distributed properties of the settling particles leads to a system of non-linear hyperbolic-parabolic PDEs whose solutions may contain very sharp transitions. This necessitates the use of a consistent and robust numerical method to obtain well-resolved and reliable approximations to the PDE solutions. The use of implicit–explicit …

Mathematical optimizationPartial differential equationDiscretizationApplied MathematicsReliability (computer networking)Numerical analysisRelaxation (iterative method)010103 numerical & computational mathematics01 natural sciences6. Clean water010101 applied mathematicsSet (abstract data type)SettlingModeling and Simulation0101 mathematicsConvection–diffusion equationMathematicsApplied Mathematical Modelling
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A Projected Algebraic Multigrid Method for Linear Complementarity Problems

2011

We present an algebraic version of an iterative multigrid method for obstacle problems, called projected algebraic multigrid (PAMG) here. We show that classical AMG algorithms can easily be extended to deal with this kind of problem. This paves the way for efficient multigrid solution of obstacle problems with partial differential equations arising, for example, in financial engineering.

Mathematical optimizationPartial differential equationIterative methodMathematicsofComputing_NUMERICALANALYSISComputer Science::Numerical AnalysisLinear complementarity problemMathematics::Numerical AnalysisFinancial engineeringMultigrid methodObstacleComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONObstacle problemComputer Science::Mathematical SoftwareApplied mathematicsAlgebraic numberMathematicsSSRN Electronic Journal
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