Studi Boundary Element Method dan Multi-objective Inverse Analysis untuk Simulasi Deteksi Multikorosi Beton Bertulang

M. Abrar Masykuri, M. Ihsan, S. Fonna, S. Huzni, Herdi Susanto

Abstract


Abstract

Nowadays, corrosion probem become one of the important problem for infrastructures over the world. Therefore, over the last decades, several corrosion reearch has been investigated. Several software have been developed to simulate corrosion that occurs on the reinforcing steel in concrete. The fundamental goal of the simulation is to predict the degree of corrosion that achieved. Many pioneering works allowed for the successful application of the boundary element method (BEM) to simulate the corrosion. This research aims to study the ability of Boundary Element Inverse Analysis (BEIA) in detecting corrosion that more than one location or known as Multi corrosion on the reinforcing steel in concrete. BEIA is a method that developed to detect corrosion in reinforced concrete. BEIA developed by combining the application of Boundary Element Method (BEM) and Multi-objective Particle Swarm Optimization (PSO). BEM used to calculate potential values on concrete surfaces. Furthermore, PSO is used to evaluate the cost function to detect corrosion on reinforcing steel inside concrete. To execute BEIA, it requires several input parameters include the results of meshing and potential data from the field. However, in this case, the field potential data used is the result of the calculation of  BEM simulation with a mesh size of 4mm and assuming the location of corrosion is at X1 = 50 mm and X2 = 350 mm. The simulation results from BEIA show that the position of the particles at the 150th iteration is already at the specified location, at X1 = 50 mm and X2 = 350 mm, this proves that Multi-objective BEIA can simulate multi corrosion detection that occur on a concreted surface..

 

Keywords—Multi corrosion, BEM,  Multi-objective, BEIA, corrosion detection, reinforced concrete


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References


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DOI: https://doi.org/10.35308/jmkn.v6i2.2760

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