Development of a Digital Twin System for Retaining Walls

초록

Investigating the ground conditions during the construction phase is crucial for ensuring the stability of Earth-retaining walls. While ground information is typically obtained through site investigations, the actual characteristics of the ground may differ from the obtained results. Real-time analysis of the wall's stability requires reflecting the actual state of the ground. Furthermore, to secure the stability of the wall when instability is detected, appropriate solutions need to be provided. This study aims to propose a digital twin model for Earth-retaining walls that utilizes the differential evolution algorithm to predict the actual ground conditions and employs artificial intelligence learning to assess the wall's stability in real-time. Through this study, it was demonstrated that the digital twin model of the retaining wall, using artificial intelligence learning, exhibited high accuracy. It enables real-time assessment of the wall's stability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

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