PRO-ARMOUR · AI-driven probabilistic method for response-based design of rock armour slopes

Линиите свързват координатора с партньорите.

Накратко на български

Цел на проекта

Coastal regions are increasingly threatened by more severe and frequent storms and sea-level rise, which intensify erosion and flooding risks and endanger ports and coastal regions. To counter these hazards, rubble-mound breakwaters constructed with large quarry rocks are the most widely used protection structures worldwide. However, their construction demands vast material volumes, high financial costs, and generates significant CO2 emissions. Despite these investments, the hydraulic stability of armour units remains a critical challenge in design practice. Current methods largely rely on deterministic or semi-probabilistic approaches, applying conservative safety factors that ensure stability but result in overdesign, excessive rock consumption, and inflated carbon footprints. PRO-ARMOUR tackles this gap by delivering a new response-based AI-driven probabilistic method for rock armour design. The project combines advanced Level III Monte Carlo simulations, physics-informed AI-driven surrogate models, and a novel 3D experimental dataset to predict armour unit response under random waves and quantify uncertainty and failure probability with high accuracy. These advances will be translated into an open-access Python tool, providing engineers, contractors, and policymakers with transparent and practical tool for risk-informed design. By enabling cost-effective and climate-resilient solutions, PRO-ARMOUR will reduce armour use, construction costs, and CO2 emissions, directly supporting EU sustainability and adaptation goals. Hosted at TU Delft (Netherlands) with a secondment at the Polytechnic University of Bari (Italy), the fellowship merges world-leading expertise in probabilistic modelling, AI, breakwater engineering and experimental hydraulics. Beyond scientific innovation, I will foster societal impact by strengthening the resilience of vulnerable coastal communities, and economic and environmental impact through measurable savings and lower carbon footprints.

Оригинален текст от CORDIS (на английски).

Участници

• TECHNISCHE UNIVERSITEIT DELFT · DelftКоординаторНидерландия
• POLITECNICO DI BARI · BariИталия

Връзки

• Виж в CORDIS