Search results for "Runge–Kutta methods"

showing 10 items of 13 documents

A Magnetohydrodynamic Auxiliary Propulsion system for docking assistance of autonomous vehicle

2016

In this article we present an approach to the description of Magnetohydrodynamic Auxiliary Propulsion system for docking assistance of autonomous vehicle. Preliminarily, an analytical model which includes an electromagnetic model and a thermal model is presented. Successively, in order to move beyond the analytical model, a 3-D MHD modeling tool and a Runge Kutta method based solver are presented and they are used to investigate an alternative MHD solutions. Some numerical analysis are given

010302 applied physicsEngineeringbusiness.industryNumerical analysis05 social sciencesControl engineeringOcean EngineeringSolverPropulsionSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciOceanography01 natural sciencesRunge–Kutta methodsMagnetohydrodinamic Propulsion SystemSettore ING-INF/04 - AutomaticaPhysics::Space Physics0502 economics and business0103 physical sciencesMagnetohydrodynamic driveElectromagnetic modelMagnetohydrodynamicsThermal modelbusinessInstrumentation050203 business & management
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New Families of Symplectic Runge-Kutta-Nyström Integration Methods

2001

We present new 6-th and 8-th order explicit symplectic Runge-Kutta-Nystrom methods for Hamiltonian systems which are more efficient than other previously known algorithms. The methods use the processing technique and non-trivial flows associated with different elements of the Lie algebra involved in the problem. Both the processor and the kernel are compositions of explicitly computable maps.

AlgebraRunge–Kutta methodsKernel (image processing)Lie algebraOrder (group theory)Mathematics::Numerical AnalysisSymplectic geometryHamiltonian systemMathematics
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Minimally implicit Runge-Kutta methods for Resistive Relativistic MHD

2016

The Relativistic Resistive Magnetohydrodynamic (RRMHD) equations are a hyperbolic system of partial differential equations used to describe the dynamics of relativistic magnetized fluids with a finite conductivity. Close to the ideal magnetohydrodynamic regime, the source term proportional to the conductivity becomes potentially stiff and cannot be handled with standard explicit time integration methods. We propose a new class of methods to deal with the stiffness fo the system, which we name Minimally Implicit Runge-Kutta methods. These methods avoid the development of numerical instabilities without increasing the computational costs in comparison with explicit methods, need no iterative …

AstrofísicaHistoryResistive touchscreenPartial differential equation010308 nuclear & particles physicsExplicit and implicit methodsNumerical methods for ordinary differential equationsStiffnessMagnetohidrodinàmica01 natural sciencesComputer Science ApplicationsEducationRunge–Kutta methods0103 physical sciencesmedicineCalculusApplied mathematicsMagnetohydrodynamic driveMagnetohydrodynamicsmedicine.symptom010303 astronomy & astrophysicsMathematics
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NUMERICAL ALGORITHMS

2013

For many systems of differential equations modeling problems in science and engineering, there are natural splittings of the right hand side into two parts, one non-stiff or mildly stiff, and the other one stiff. For such systems implicit-explicit (IMEX) integration combines an explicit scheme for the non-stiff part with an implicit scheme for the stiff part. In a recent series of papers two of the authors (Sandu and Zhang) have developed IMEX GLMs, a family of implicit-explicit schemes based on general linear methods. It has been shown that, due to their high stage order, IMEX GLMs require no additional coupling order conditions, and are not marred by order reduction. This work develops a …

General linear methodsMathematical optimizationIMEX methods; general linear methods; error analysis; order conditions; stability analysisIMEX methodsDifferential equationSCHEMESorder conditionsMathematics AppliedExtrapolationStability (learning theory)QUADRATIC STABILITYstability analysisPARABOLIC EQUATIONSSYSTEMSNORDSIECK METHODSFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisRUNGE-KUTTA METHODSMULTISTEP METHODSerror analysisMathematicsCONSTRUCTIONSeries (mathematics)Applied MathematicsNumerical analysisComputer Science - Numerical AnalysisStability analysisORDEROrder conditionsNumerical Analysis (math.NA)Computer Science::Numerical AnalysisRunge–Kutta methodsGeneral linear methodsError analysisORDINARY DIFFERENTIAL-EQUATIONSOrdinary differential equationgeneral linear methodsMathematics
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Explicit Algorithms for a New Time Dependent Model Based on Level Set Motion for Nonlinear Deblurring and Noise Removal

2000

In this paper we formulate a time dependent model to approximate the solution to the nonlinear total variation optimization problem for deblurring and noise removal introduced by Rudin and Osher [ Total variation based image restoration with free local constraints, in Proceedings IEEE Internat. Conf. Imag. Proc., IEEE Press, Piscataway, NJ, (1994), pp. 31--35] and Rudin, Osher, and Fatemi [ Phys. D, 60 (1992), pp. 259--268], respectively. Our model is based on level set motion whose steady state is quickly reached by means of an explicit procedure based on Roe's scheme [ J. Comput. Phys., 43 (1981), pp. 357--372], used in fluid dynamics. We show numerical evidence of the speed of resolution…

Level set (data structures)DeblurringOptimization problemApplied MathematicsConstrained optimizationWhite noiseComputational MathematicsRunge–Kutta methodssymbols.namesakeGaussian noisesymbolsAlgorithmImage restorationMathematicsSIAM Journal on Scientific Computing
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A Magnetohydrodynamic Generator for Marine Energy Harvesting

2018

In this article we present an approach to the description of Magneto-hydrodynamic Marine Energy Harvesting (MHMEH) system. Preliminarly, a general discussion on the principle of operation is presented. Successively, in order to move beyond the analytical model, a 3-D MHD modeling tool and a Runge Kutta method based solver are presented and they are used to investigate an alternative MHD solutions. Some numerical analyses are given.

Magnetohydrodynamic generatorComputer science020209 energyMagnetohydrodinamic Propulsion Systems02 engineering and technologySolverDesalinationFinite element methodlaw.inventionRunge–Kutta methodslawMarine energy0202 electrical engineering electronic engineering information engineeringApplied mathematicsMagnetohydrodynamicsOCEANS 2018 MTS/IEEE Charleston
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High-order Runge–Kutta–Nyström geometric methods with processing

2001

Abstract We present new families of sixth- and eighth-order Runge–Kutta–Nystrom geometric integrators with processing for ordinary differential equations. Both the processor and the kernel are composed of explicitly computable flows associated with non trivial elements belonging to the Lie algebra involved in the problem. Their efficiency is found to be superior to other previously known algorithms of equivalent order, in some case up to four orders of magnitude.

Numerical AnalysisDifferential equationApplied MathematicsMathematical analysisMathematicsofComputing_NUMERICALANALYSISLie groupMathematics::Numerical AnalysisComputational MathematicsRunge–Kutta methodsKernel methodKernel (image processing)Ordinary differential equationLie algebraInitial value problemApplied mathematicsMathematicsApplied Numerical Mathematics
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Order optimal preconditioners for fully implicit Runge-Kutta schemes applied to the bidomain equations

2010

The partial differential equation part of the bidomain equations is discretized in time with fully implicit Runge–Kutta methods, and the resulting block systems are preconditioned with a block diagonal preconditioner. By studying the time-stepping operator in the proper Sobolev spaces, we show that the preconditioned systems have bounded condition numbers given that the Runge–Kutta scheme is A-stable and irreducible with an invertible coefficient matrix. A new proof of order optimality of the preconditioners for the one-leg discretization in time of the bidomain equations is also presented. The theoretical results are verified by numerical experiments. Additionally, the concept of weakly po…

Numerical AnalysisPartial differential equationDiscretizationPreconditionerApplied MathematicsMathematical analysisBlock matrixComputer Science::Numerical AnalysisMathematics::Numerical Analysislaw.inventionSobolev spaceComputational MathematicsRunge–Kutta methodsInvertible matrixlawCoefficient matrixAnalysisMathematicsNumerical Methods for Partial Differential Equations
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Modelling phase transition kinetics of chenodeoxycholic acid with the Runge–Kutta method

2009

Abstract The phase transition kinetics of two chenodeoxycholic acid polymorphic modifications— form I (stable at high temperature), form III (stable at low temperature) and the amorphous phase has been examined under various conditions of temperature and relative humidity. Form III conversion to form I was examined at high temperature conditions and was found to be non-spontaneous, requiring seed crystals for initiation. The formation kinetic model of form I was created incorporating the three-dimensional seed crystal growth, the phase transition rate proportion to the surface area of form I crystals, and the influence of the amorphous phase surface area changes with an empirical stage poin…

Phase transitionDifferential Thermal AnalysisSpectrophotometry InfraredDifferential equationClinical BiochemistryPharmaceutical ScienceThermodynamicsChenodeoxycholic AcidKinetic energyPhase TransitionAnalytical ChemistryReaction rate constantDrug StabilityX-Ray DiffractionDrug DiscoverySample preparationSpectroscopySeed crystalModels StatisticalCalorimetry Differential ScanningChemistryTemperatureKineticsRunge–Kutta methodsCrystallographyX-ray crystallographyCrystallizationJournal of Pharmaceutical and Biomedical Analysis
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A computational magnetohydrodynamic model of a marine propulsion system

2016

In this article we present an approach to the description of Magnetohydrodynamic Propulsion. Preliminarly, an analytical model which includes an electromagnetic model and a thermal model is presented. Successively, in order to move beyond the analytical model, a 3-D MHD modeling tool and a Runge Kutta method based solver are presented and they are used to investigate an alternative MHD solutions. Some numerical analysis are given.

PhysicsNumerical analysisMechanicsSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciSolverPropulsionOceanographyFinite element methodMagnetohydrodinamic Propulsion SystemRunge–Kutta methodsSettore ING-INF/04 - AutomaticaPhysics::Plasma PhysicsMarine propulsionAutomotive EngineeringPhysics::Space PhysicsMagnetohydrodynamic driveMagnetohydrodynamicsOCEANS 2016 - Shanghai
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