Three Dimensional Terzaghi Consolidation

Three-dimensional Terzaghi consolidation, modeling the time-dependent settlement of soil under load, is a complex problem currently being addressed using advanced computational methods. Research focuses on improving the accuracy and efficiency of solutions, particularly through physics-informed neural networks (PINNs), which incorporate the governing partial differential equations directly into the model architecture. These techniques are being applied to both forward (predicting settlement) and inverse (identifying soil parameters) problems, showing promise for improved accuracy in soil settlement prediction and geotechnical engineering applications. Furthermore, continual learning algorithms are being explored to adapt models to evolving conditions and handle large, complex datasets.