Result: Application of regularization technique to variational adjoint method: A case for nonlinear convection―diffusion problem

Title:
Application of regularization technique to variational adjoint method: A case for nonlinear convection―diffusion problem
Source:
Applied mathematics and computation. 218(8):4475-4482
Publisher Information:
Amsterdam: Elsevier, 2011.
Publication Year:
2011
Physical Description:
print, 32 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Algèbre linéaire numérique, Numerical linear algebra, Analyse numérique dans des espaces abstraits, Numerical analysis in abstract spaces, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Optimisation et calcul variationnel numériques, Numerical methods in optimization and calculus of variations, Algèbre linéaire numérique, Numerical linear algebra, Algebra lineal numérica, Analyse numérique, Numerical analysis, Análisis numérico, Calcul 1 dimension, One-dimensional calculations, Calcul variationnel, Variational calculus, Cálculo de variaciones, Condition initiale, Initial condition, Condición inicial, Equation convection diffusion, Convection diffusion equation, Ecuación convección difusión, Equation non linéaire, Non linear equation, Ecuación no lineal, Itération, Iteration, Iteracción, Mathématiques appliquées, Applied mathematics, Matemáticas aplicadas, Méthode optimisation, Optimization method, Método optimización, Méthode régularisation, Regularization method, Método regularización, Problème mal posé, Ill posed problem, Problema mal planteado, Problème non linéaire, Nonlinear problems, Programmation mathématique, Mathematical programming, Programación matemática, Régularisation, Regularization, Regularización, Système discret, Discrete system, Sistema discreto, Vitesse convergence, Convergence speed, Velocidad convergencia, 49R50, 65F22, 65J20, 65K10, 65Kxx, Data assimilation, Nonlinear convection-diffusion equation, Regularization term, Variational adjoint method
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
College of Mathematics and Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
College of Applied Meteorology, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
ISSN:
0096-3003
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.25313149
Database:
PASCAL Archive

Further Information

A discrete assimilation system for a one-dimensional variable coefficient convection-diffusion equation is constructed. The variational adjoint method combined with the regularization technique is employed to retrieve the initial condition and diffusion coefficient with the aid of a set of simulated observations. Several numerical experiments are performed: (a) retrieving both the initial condition and diffusion coefficient jointly (Experiment JR), (b) retrieving either of them separately (Experiment SR), (c) retrieving only the diffusion coefficient with the iteration count increased to 800 (Experiment NoR-SR), and (d) retrieving only the diffusion coefficient with the consideration of a regularization term based on the Experiment NoR-SR (Experiment AdR-SR). The results indicate that within the limit of 100 iterations, the retrieval quality of the Experiment SR is better than those from the Experiment JR. Compared with the initial condition, the diffusion coefficient is a little difficult to retrieve, whereas we still achieve the desired result by increasing the iterations or integrating the regularization term into the cost functional for the improvement with respect to the diffusion coefficient. Further comparisons between the Experiment NoR-SR and AdR-SR show that the regularization term can really help not only improve the precision of retrieval to a large extent, but also speed up the convergence of solution, even if some perturbations are imposed on those observations.