Numerical approximation and analysis of the inverse Robin problem using the Kohn-Vogelius method

In this work, we numerically investigate the inverse Robin problem of recovering a piecewise constant Robin coefficient in an elliptic or parabolic problem from the Cauchy data on a part of the boundary, which arises commonly in several applications, e.g., non-destructive corrosion detection. We employ a Kohn-Vogelius type variational functional for the regularized reconstruction, and discretize the resulting optimization problem using the Galerkin finite element method on a graded mesh. We establish rigorous error estimates on the recovered Robin coefficient in terms of the mesh size, temporal step size and noise level. This is achieved by combining the approximation error of the direct problem, <italic>a priori</italic> estimates on the functional, and suitable conditional stability estimates of the continuous inverse problem. We present several numerical experiments to illustrate the approach and to complement the theoretical findings.

Authors

Publication Details

Journal
Mathematics of Computation
Published
2026-07-23
DOI
https://doi.org/10.1090/mcom/4222
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Numerical approximation and analysis of the inverse Robin problem using the Kohn-Vogelius method

Erik Burman, Bangti Jin, Siyu Cen, Zhi Zhou
Mathematics of Computation
Numerical methods in inverse problems
article

Numerical approximation and analysis of the inverse Robin problem using the Kohn-Vogelius method

Erik Burman, Bangti Jin, Siyu Cen, Zhi Zhou
article en

Abstract

In this work, we numerically investigate the inverse Robin problem of recovering a piecewise constant Robin coefficient in an elliptic or parabolic problem from the Cauchy data on a part of the boundary, which arises commonly in several applications, e.g., non-destructive corrosion detection. We employ a Kohn-Vogelius type variational functional for the regularized reconstruction, and discretize the resulting optimization problem using the Galerkin finite element method on a graded mesh. We establish rigorous error estimates on the recovered Robin coefficient in terms of the mesh size, temporal step size and noise level. This is achieved by combining the approximation error of the direct problem, <italic>a priori</italic> estimates on the functional, and suitable conditional stability estimates of the continuous inverse problem. We present several numerical experiments to illustrate the approach and to complement the theoretical findings.

Mathematics of Computation
Research Grants Council, University Grants Committee, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 88%
Numerical methods in inverse problems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.