6,764 research outputs found
A modified Galerkin/finite element method for the numerical solution of the Serre-Green-Naghdi system
A new modified Galerkin / Finite Element Method is proposed for the numerical
solution of the fully nonlinear shallow water wave equations. The new numerical
method allows the use of low-order Lagrange finite element spaces, despite the
fact that the system contains third order spatial partial derivatives for the
depth averaged velocity of the fluid. After studying the efficacy and the
conservation properties of the new numerical method, we proceed with the
validation of the new numerical model and boundary conditions by comparing the
numerical solutions with laboratory experiments and with available theoretical
asymptotic results
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Multiderivative methods for nonlinear second order boundary value problems
Second, fourth and sixth order methods are developed and analysed for the numerical solution of non-linear second order boundary value problems.
The methods arise from a two-step recurrence relation involving exponential terms, these being replaced by Padé approximants .
The methods are tested on two problems from the literature
PORTA: A three-dimensional multilevel radiative transfer code for modeling the intensity and polarization of spectral lines with massively parallel computers
The interpretation of the intensity and polarization of the spectral line
radiation produced in the atmosphere of the Sun and of other stars requires
solving a radiative transfer problem that can be very complex, especially when
the main interest lies in modeling the spectral line polarization produced by
scattering processes and the Hanle and Zeeman effects. One of the difficulties
is that the plasma of a stellar atmosphere can be highly inhomogeneous and
dynamic, which implies the need to solve the non-equilibrium problem of the
generation and transfer of polarized radiation in realistic three-dimensional
(3D) stellar atmospheric models. Here we present PORTA, an efficient multilevel
radiative transfer code we have developed for the simulation of the spectral
line polarization caused by scattering processes and the Hanle and Zeeman
effects in 3D models of stellar atmospheres. The numerical method of solution
is based on the non-linear multigrid iterative method and on a novel
short-characteristics formal solver of the Stokes-vector transfer equation
which uses monotonic B\'ezier interpolation. Therefore, with PORTA the
computing time needed to obtain at each spatial grid point the self-consistent
values of the atomic density matrix (which quantifies the excitation state of
the atomic system) scales linearly with the total number of grid points.
Another crucial feature of PORTA is its parallelization strategy, which allows
us to speed up the numerical solution of complicated 3D problems by several
orders of magnitude with respect to sequential radiative transfer approaches,
given its excellent linear scaling with the number of available processors. The
PORTA code can also be conveniently applied to solve the simpler 3D radiative
transfer problem of unpolarized radiation in multilevel systems.Comment: 15 pages, 15 figures, to appear in Astronomy and Astrophysic
Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces
© 2007 EUCA.A novel online-computation approach to optimal control of nonlinear, noise-affected systems with continuous state and control spaces is presented. In the proposed algorithm, system noise is explicitly incorporated into the control decision. This leads to superior results compared to state-of-the-art nonlinear controllers that neglect this influence. The solution of an optimal nonlinear controller for a corresponding deterministic system is employed to find a meaningful state space restriction. This restriction is obtained by means of approximate state prediction using the noisy system equation. Within this constrained state space, an optimal closed-loop solution for a finite decision-making horizon (prediction horizon) is determined within an adaptively restricted optimization space. Interleaving stochastic dynamic programming and value function approximation yields a solution to the considered optimal control problem. The enhanced performance of the proposed discrete-time controller is illustrated by means of a scalar example system. Nonlinear model predictive control is applied to address approximate treatment of infinite-horizon problems by the finite-horizon controller
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