An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay
Cong Tang, Shu‐Yu He, Wan‐Huan Zhou
Abstract
Recently, the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly. However, updating the ground settlement profile, which is crucial for determining potential damage to nearby infrastructures, has received limited attention. To address this, this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile. The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly. Furthermore, the model is physically interpretable, which can provide valuable references for construction adjustments. The effectiveness of the proposed method is demonstrated through two field case studies, showing that it can yield satisfactory predictions for the settlement profile.