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This session explores how excavation models can be optimized using inclinometer readings and site monitoring data to reduce the gap between analysis results and real field behavior. Through a 2D excavation retaining structure model in MIDAS GTS NX, the session explains how uncertainties such as soil properties, modelling assumptions, soil–structure interface conditions, groundwater, and unexpected soft layers can affect excavation predictions. It also introduces surrogate modelling-based back analysis as a practical method to calibrate soil parameters, improve model reliability, and make forward prediction more efficient. Participants will gain practical guidance on using monitoring data, back analysis, correlation analysis, and surrogate models to support smarter and more reliable geotechnical design.
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