15 / 2025-07-09 09:37:39

A Fusion Framework of Numerical Simulation and Machine Learning for Long-Term Stability Assessment of Artificial Island Slopes

Numerical Simulation,Machine Learning,Long-term Slope Stability,Intelligent Assessment

The South China Sea boasts a strategic geographical location and abundant resources, constituting a critical area for China's national security and maritime development strategy. However, artificial islands and reefs are persistently subjected to the coupled effects of complex marine dynamic environments, including waves and earthquakes. Their stability is paramount to the safety of the island/reef structures and associated infrastructure. Current research predominantly focuses on short-term responses under single-wave or single-earthquake loading, making it difficult to reveal the true evolutionary patterns of long-term stability under the cumulative impact of repeated extreme events. This paper highlights that coral sand, the primary fill material for these artificial islands/reefs, possesses distinctive physico-mechanical properties (e.g., high porosity, high crushability) that render it susceptible to liquefaction and significant displacements under external forces. To address this, we propose an approach centered on wave-earthquake coupling. This involves generating extensive datasets of slope response reflecting real physical processes through numerical simulation. Subsequently, leveraging advanced machine learning techniques, an intelligent assessment framework capable of predicting long-term evolutionary trends is constructed. This methodology integrates the strengths of physical mechanisms and data-driven approaches, offering a viable alternative to costly traditional numerical simulations, especially under data-scarce conditions. It thus provides an efficient and scalable technical solution for evaluating the long-term stability of artificial island/reef slopes, better aligning with the practical engineering demands faced by these structures in the extreme and uncertain environment of the South China Sea.