Search results for "65m15"

showing 3 items of 3 documents

Stochastic Galerkin method for cloud simulation

2018

AbstractWe develop a stochastic Galerkin method for a coupled Navier-Stokes-cloud system that models dynamics of warm clouds. Our goal is to explicitly describe the evolution of uncertainties that arise due to unknown input data, such as model parameters and initial or boundary conditions. The developed stochastic Galerkin method combines the space-time approximation obtained by a suitable finite volume method with a spectral-type approximation based on the generalized polynomial chaos expansion in the stochastic space. The resulting numerical scheme yields a second-order accurate approximation in both space and time and exponential convergence in the stochastic space. Our numerical results…

010504 meteorology & atmospheric sciencesComputer scienceuncertainty quantificationQC1-999cloud dynamicsFOS: Physical sciencesCloud simulation65m15010103 numerical & computational mathematics01 natural sciencespattern formationMeteorology. ClimatologyFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsStochastic galerkin0105 earth and related environmental sciencesnavier-stokes equationsPhysics65m2565l05Numerical Analysis (math.NA)65m06Computational Physics (physics.comp-ph)stochastic galerkin method35l4535l65finite volume schemesQC851-999Physics - Computational Physicsimex time discretization
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Guaranteed lower bounds for cost functionals of time-periodic parabolic optimization problems

2019

In this paper, a new technique is shown for deriving computable, guaranteed lower bounds of functional type (minorants) for two different cost functionals subject to a parabolic time-periodic boundary value problem. Together with previous results on upper bounds (majorants) for one of the cost functionals, both minorants and majorants lead to two-sided estimates of functional type for the optimal control problem. Both upper and lower bounds are derived for the second new cost functional subject to the same parabolic PDE-constraints, but where the target is a desired gradient. The time-periodic optimal control problems are discretized by the multiharmonic finite element method leading to lar…

Optimization problemtime-periodic conditionmultiharmonic finite element methodDiscretizationtwo-sided boundsSystems and Control (eess.SY)010103 numerical & computational mathematicsSystem of linear equationsElectrical Engineering and Systems Science - Systems and Control01 natural sciencesUpper and lower boundsSaddle pointFOS: MathematicsFOS: Electrical engineering electronic engineering information engineeringApplied mathematicsMathematics - Numerical AnalysisBoundary value problem0101 mathematicsMathematics - Optimization and ControlMathematicsosittaisdifferentiaaliyhtälöt35Kxx 65M60 65M70 65M15 65K10parabolic optimal control problemsNumerical Analysis (math.NA)matemaattinen optimointiOptimal controlFinite element method010101 applied mathematicsComputational MathematicsComputational Theory and MathematicsOptimization and Control (math.OC)Modeling and Simulationa posteriori error analysisnumeerinen analyysiguaranteed lower boundsComputers & Mathematics with Applications
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Time-dependent weak rate of convergence for functions of generalized bounded variation

2016

Let $W$ denote the Brownian motion. For any exponentially bounded Borel function $g$ the function $u$ defined by $u(t,x)= \mathbb{E}[g(x{+}\sigma W_{T-t})]$ is the stochastic solution of the backward heat equation with terminal condition $g$. Let $u^n(t,x)$ denote the corresponding approximation generated by a simple symmetric random walk with time steps $2T/n$ and space steps $\pm \sigma \sqrt{T/n}$ where $\sigma > 0$. For quite irregular terminal conditions $g$ (bounded variation on compact intervals, locally H\"older continuous) the rate of convergence of $u^n(t,x)$ to $u(t,x)$ is considered, and also the behavior of the error $u^n(t,x)-u(t,x)$ as $t$ tends to $T$

Statistics and ProbabilityApproximation using simple random walkweak rate of convergence01 natural sciencesStochastic solution41A25 65M15 (Primary) 35K05 60G50 (Secondary)010104 statistics & probabilityExponential growthFOS: Mathematics0101 mathematicsBrownian motionstokastiset prosessitMathematicsosittaisdifferentiaaliyhtälötApplied MathematicsProbability (math.PR)010102 general mathematicsMathematical analysisfinite difference approximation of the heat equationFunction (mathematics)Rate of convergenceBounded functionBounded variationnumeerinen analyysiapproksimointiStatistics Probability and UncertaintyMathematics - ProbabilityStochastic Analysis and Applications
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