Optimization of electrical resistivity survey utilizing modified harmony search algorithm to predict anomalous zone ahead of tunnel faces

Predicting anomalies ahead of a tunnel face is essential to ensure construction safety and efficiency during tunneling. This study proposes an optimization system to estimate the characteristics of anomalies ahead of a tunnel face. The developed system can estimate the location, the thickness and the electrical resistivity of the anomaly using inverse analysis based on the modified harmony search algorithm with resistivity measurement. To verify the efficacy of the developed system, laboratory chamber tests were conducted by simulating ground formations with faults. The experimental results indicated that the developed system had substantial prediction performance with a short data analysis time. Notably, the location of an anomaly was relatively well predicted compared to the other properties, which is crucial information that can prevent potential risks. Therefore, the system could predict anomaly characteristics and enable the appropriate management of potential risks.