| Abstract |
As one of the most developed areas on this planet, the coastal regions have the greatest concentration of assets, abundant developments, critical infrastructures and complex ecosystems. However, due to the global climate change, the coastlines are unprecedentedly threatened by the accelerated occurrence of natural hazards, such as coastal flooding, landslide and tsunami, leading to serious coastal erosion and retreating landward. Some existing researches have confirmed that the coastline retreating rate depends highly on the environmental drivers such as wave action, temperature and rainfall, following a highly complex and non-linear relationship, while the mechanisms of progressive cliff failures remain unclear. ENHANCE will employ the emerging digital technologies of advanced numerical modelling and Artificial Intelligence (AI) to investigate the triggering mechanisms of coastal landslides and mitigation measures. The key climatic factors governing the cliff stability and their inter-dependency relationship will be clarified by the data-driven AI analyses. Then, a coupled continuous-discontinuous modelling will be performed to investigate the undercutting-notch effect on the progressive failure of coastal cliffs, clarifying the large deformation, crack propagation and mass movement. A novel fluid-solid-thermal coupling constitutive model will be developed to investigate the multi-physics responses of coastal slopes under changing climate conditions. The developed numerical modelling platform aims to be scalable for EU/worldwide applications by explicitly considering the temporal and spatial variabilities of geological formation properties. Consequently, an integrated coastal cliff management framework will be proposed for effective decision-makings on urban planning, hazard forecasting and mitigation. The findings will contribute to the UN 2030 Agenda for SDGs (9, 11, 13) and the European Green Deal, featuring great intellectual merits and engineering impacts. |