1,509 research outputs found
A class of Galerkin schemes for time-dependent radiative transfer
The numerical solution of time-dependent radiative transfer problems is
challenging, both, due to the high dimension as well as the anisotropic
structure of the underlying integro-partial differential equation. In this
paper we propose a general framework for designing numerical methods for
time-dependent radiative transfer based on a Galerkin discretization in space
and angle combined with appropriate time stepping schemes. This allows us to
systematically incorporate boundary conditions and to preserve basic properties
like exponential stability and decay to equilibrium also on the discrete level.
We present the basic a-priori error analysis and provide abstract error
estimates that cover a wide class of methods. The starting point for our
considerations is to rewrite the radiative transfer problem as a system of
evolution equations which has a similar structure like first order hyperbolic
systems in acoustics or electrodynamics. This analogy allows us to generalize
the main arguments of the numerical analysis for such applications to the
radiative transfer problem under investigation. We also discuss a particular
discretization scheme based on a truncated spherical harmonic expansion in
angle, a finite element discretization in space, and the implicit Euler method
in time. The performance of the resulting mixed PN-finite element time stepping
scheme is demonstrated by computational results
On the uniqueness of nonlinear diffusion coefficients in the presence of lower order terms
We consider the identification of nonlinear diffusion coefficients of the
form or in quasi-linear parabolic and elliptic equations.
Uniqueness for this inverse problem is established under very general
assumptions using partial knowledge of the Dirichlet-to-Neumann map. The proof
of our main result relies on the construction of a series of appropriate
Dirichlet data and test functions with a particular singular behavior at the
boundary. This allows us to localize the analysis and to separate the principal
part of the equation from the remaining terms. We therefore do not require
specific knowledge of lower order terms or initial data which allows to apply
our results to a variety of applications. This is illustrated by discussing
some typical examples in detail
Simultaneous identification of diffusion and absorption coefficients in a quasilinear elliptic problem
In this work we consider the identifiability of two coefficients and
in a quasilinear elliptic partial differential equation from observation
of the Dirichlet-to-Neumann map. We use a linearization procedure due to Isakov
[On uniqueness in inverse problems for semilinear parabolic equations. Archive
for Rational Mechanics and Analysis, 1993] and special singular solutions to
first determine and for . Based on this partial
result, we are then able to determine for by an
adjoint approach.Comment: 10 pages; Proof of Theorem 4.1 correcte
Numerical identification of a nonlinear diffusion law via regularization in Hilbert scales
We consider the reconstruction of a diffusion coefficient in a quasilinear
elliptic problem from a single measurement of overspecified Neumann and
Dirichlet data. The uniqueness for this parameter identification problem has
been established by Cannon and we therefore focus on the stable solution in the
presence of data noise. For this, we utilize a reformulation of the inverse
problem as a linear ill-posed operator equation with perturbed data and
operators. We are able to explicitly characterize the mapping properties of the
corresponding operators which allow us to apply regularization in Hilbert
scales. We can then prove convergence and convergence rates of the regularized
reconstructions under very mild assumptions on the exact parameter. These are,
in fact, already needed for the analysis of the forward problem and no
additional source conditions are required. Numerical tests are presented to
illustrate the theoretical statements.Comment: 17 pages, 2 figure
Identification of Chemotaxis Models with Volume Filling
Chemotaxis refers to the directed movement of cells in response to a chemical
signal called chemoattractant. A crucial point in the mathematical modeling of
chemotactic processes is the correct description of the chemotactic sensitivity
and of the production rate of the chemoattractant. In this paper, we
investigate the identification of these non-linear parameter functions in a
chemotaxis model with volume filling. We also discuss the numerical realization
of Tikhonov regularization for the stable solution of the inverse problem. Our
theoretical findings are supported by numerical tests.Comment: Added bibfile missing in v2, no changes on conten
Identification of nonlinear heat conduction laws
We consider the identification of nonlinear heat conduction laws in
stationary and instationary heat transfer problems. Only a single additional
measurement of the temperature on a curve on the boundary is required to
determine the unknown parameter function on the range of observed temperatures.
We first present a new proof of Cannon's uniqueness result for the stationary
case, then derive a corresponding stability estimate, and finally extend our
argument to instationary problems
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