Periodic Reporting for period 1 - DeP2WIND (A data-driven framework towards sustainable reuse of decommissioned petroleum platforms as support structures for wind energy production)
Periodo di rendicontazione: 2023-05-01 al 2025-04-30
DeP2WIND: A data-driven framework for the sustainable reuse of decommissioned petroleum platforms as support structures for wind energy production is a project aimed at accelerating the energy transition and repurposing existing steel waste in the marine environment. Offshore platforms in marine environments have long been researched and used for oil and gas exploration, with a significant impact on the European energy sector. Nonetheless, these constructions are abandoned in the sea after their operating lifespan and are not fully decommissioned, posing a pollution danger to the surrounding environment.
The DeP2WIND project proposes new frameworks for managing the reuse and repurposing of such structures based on their health state. The project investigates multidisciplinary techniques to analyzing the status of decommissioned platforms and addressing corrosion behavior in steel components. These innovative technologies will serve as the foundation for deciding how to reuse or recycle these structures.
Motivation and Problems addressed:
Approximately 6,000 offshore oil and gas platforms are in operation around the world, with 2,500 to 3,000 offshore petroleum platforms - or nearly half - expected to be decommissioned over the next 17 years because they will no longer be economically viable to operate. This will result in massive steel trash in the marine environment, which must be handled.
The DeP2WIND project tackled a variety of engineering problems, beginning with simulating the degradation state of the steel platform due to corrosion caused by the harsh climate, as well as evaluating the structure's reliability over time and which parts should be maintained or replaced. Furthermore, the project addresses the issue of new wind turbine designs that will be mounted on the resulting platform in the future.
Pathway to impact:
The successful completion of the DeP2WIND project has positioned its output as transformative tools for accelerating energy transition in a safe path, by minimizing steel waste and repurposing steel elements in a cost-effective way to boost renewable energy. By providing more accurate models for predicting steel deterioration in marine environments, a cost-effective maintenance-based reliability approach may be simply adopted to minimize maintenance costs while increasing structural safety. Furthermore, the employment of optimization theory-based AI assists in implementing novel designs of wind turbines.
The DeP2WIND project proposes new frameworks for managing the reuse and repurposing of such structures based on their health state. The project investigates multidisciplinary techniques to analyzing the status of decommissioned platforms and addressing corrosion behavior in steel components. These innovative technologies will serve as the foundation for deciding how to reuse or recycle these structures.
Motivation and Problems addressed:
Approximately 6,000 offshore oil and gas platforms are in operation around the world, with 2,500 to 3,000 offshore petroleum platforms - or nearly half - expected to be decommissioned over the next 17 years because they will no longer be economically viable to operate. This will result in massive steel trash in the marine environment, which must be handled.
The DeP2WIND project tackled a variety of engineering problems, beginning with simulating the degradation state of the steel platform due to corrosion caused by the harsh climate, as well as evaluating the structure's reliability over time and which parts should be maintained or replaced. Furthermore, the project addresses the issue of new wind turbine designs that will be mounted on the resulting platform in the future.
Pathway to impact:
The successful completion of the DeP2WIND project has positioned its output as transformative tools for accelerating energy transition in a safe path, by minimizing steel waste and repurposing steel elements in a cost-effective way to boost renewable energy. By providing more accurate models for predicting steel deterioration in marine environments, a cost-effective maintenance-based reliability approach may be simply adopted to minimize maintenance costs while increasing structural safety. Furthermore, the employment of optimization theory-based AI assists in implementing novel designs of wind turbines.
Throughout the DeP2WIND project, several actions were carried out in accordance within the proposed timeline framework. The experienced researcher collected degradation data from steel structures in the Norwegian offshore using installed sensors, then performed in-depth statistical analysis before developing a novel framework to model corrosion deterioration using advanced AI approaches. This resulted in a significant advancement in corrosion modeling methodologies employing AI in steel structures exposed to a severe marine environment. Then, structural reliability theory is utilized to assess the failure probability over time, which is employed as a threshold for carrying out a cost-effective decommissioned platform maintenance plan. This framework produced cost-effective results for handling abandoned structures. Following that, optimization concept-based AI modeling is utilized to propose a new wind turbine design, resulting in a holistic perspective on reusing decommissioned platform as support structures to accelerate energy transition. Furthermore, the experienced researcher was in charge of project management, dissemination activities, and establishing new collaborations both within and outside the host institution.
The DeP2WIND output successfully advanced the current state of the art and contributed to high-quality new knowledge in the fields of structural engineering, AI, reliability analysis, asset management, and energy transition structures through conference participation, workshop and mini-symposiums organization, and the publication of peer-reviewed scientific articles. This impact is demonstrated by the development of cutting-edge AI models for modeling deterioration in steel structures located in harsh marine environments, as well as the application of AI-based reliability and optimization concepts for the reuse of decommissioned offshore platforms, which contribute to waste reduction and the acceleration of the energy transition. The fellowship has improved the Experienced Researcher's professional profile as well as the host institution's research profile by encouraging collaboration and knowledge transfer.
The DeP2WIND has addressed pressing issues in European infrastructure, particularly the problem of the waste associated with the decommissioned oil and gas platforms. Thus, the project aligns with the European Green Deal and the United Nations SDGs—specifically affordable and clean energy (Goal 7), climate action (Goal 13) and life below water (Goal 14) —
The DeP2WIND project also improves decision-making processes connected to the maintenance and operation of aging structures, allowing for predictive maintenance solutions that save costs while increasing efficiency. These innovations help to ensure the economic sustainability of Europe's infrastructure by reducing resource consumption and operational downtime for civil structures.
The DeP2WIND has addressed pressing issues in European infrastructure, particularly the problem of the waste associated with the decommissioned oil and gas platforms. Thus, the project aligns with the European Green Deal and the United Nations SDGs—specifically affordable and clean energy (Goal 7), climate action (Goal 13) and life below water (Goal 14) —
The DeP2WIND project also improves decision-making processes connected to the maintenance and operation of aging structures, allowing for predictive maintenance solutions that save costs while increasing efficiency. These innovations help to ensure the economic sustainability of Europe's infrastructure by reducing resource consumption and operational downtime for civil structures.