Nondestructive Corrosion Monitoring in Reinforced Concrete by Boundary Element Inverse Analysis

Kazuhiro Suga; Masato Yoshida; M. Ridha; Shigeru Aoki

doi:10.4028/www.scientific.net/AMR.33-37.1293

Paper Titles

Study on Erosion-Resistance of Electro-Thermal Explosion Ultra-High Speed Spraying MoSi₂-Based Coatings
p.1271

Erosion Behavior of TiC-xNi Composite Coatings In Situ Synthesized by Electro-Thermal Explosion Ultra-High Speed Spraying
p.1277

Performance Prediction of Pre-Corroded Aluminum Alloy Using Genetic Algorithm-Neural Network and Fuzzy Neural Network
p.1283

Non-Destructive Inspection of Rebar Corrosion in Concrete Structures by Using BEM and GA
p.1289

Nondestructive Corrosion Monitoring in Reinforced Concrete by Boundary Element Inverse Analysis
p.1293

Effective BEM for Corrosion Analysis of Net Structure
p.1299

Numerical Simulation of Corrosion under Different Solution Velocity
p.1303

Experimental Analysis and FEM Calculation of the Thermal Deformation for the Spindle System of Machining Center
p.1307

Study on Rules in Material Removal Rate and Surface Quality of Short Electric Arc Machining Process
p.1313

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 33-37Nondestructive Corrosion Monitoring in Reinforced...

Nondestructive Corrosion Monitoring in Reinforced Concrete by Boundary Element Inverse Analysis

Abstract:

This study proposes a monitoring method for corrosion on reinforced concrete structure using inverse analysis approach. At first, we define an inverse problem to identify the real and imaginary parts of the concrete conductivity and the impedance between concrete and steel. The observation of the inverse problem is the electric potential on the concrete structure surface when the AC impedance measurement is performed. The observation condition, such as layout of observation point and type of observation, of the inverse is optimized. The optimization is achieved by minimizing the average of eigen values of a posteriori estimate error covariance matrix based on the Kalman Filter estimation algorithm. We show a numerical simulation to solve the inverse problem on the optimized observation condition to evaluate the effectiveness of the condition. The simulation shows the real parts of the concrete conductivity and the impedance are well identified but imaginary parts of them are not. To overcome this difficulty, we evaluate the sensitivity of the imaginary part of the impedance to the real part and the imaginary part of the electric potential. We find the possibility that the observation of the imaginary part of the electric potential improves the estimation. Finally, a numerical simulation is performed under the optimized observation condition considering the above discussion. In the numerical simulation shows that considering the sensitivity of the parameters to the potential improves the solution on the inverse problem.