Nandar Hlaing PhD

O&M Optimization of Offshore Wind Turbine Support Structures Using Digital Twins

The offshore industry has been trending towards larger wind turbines in deeper water depths. Under harsher environments, the structure's degradation is faster as well as the maintenance tasks with human labour are more difficult and cost-demanding.  Automated inspections and monitoring solutions are increasingly desired. This PhD research aims to develop an optimal decision-making framework for operational management (inspection, monitoring, and maintenance) of offshore wind turbine support structures.

The development of optimal decision-making framework will be supported by using digital twins. A “digital twin” is a virtual replica of physical assets, processes and systems on which simulations can be run to predict failures before happening. The uncertain parameters of the “digital twin” can be updated as information is gained through Structural Health Monitoring (SHM) data from the installed sensors. Since the uncertainties are significantly reduced, the “digital twin” represents the real structure more accurately and helps the decision maker to make more rational and optimal decisions.

Publications

Nandar Hlaing, Pablo G. Morato, Philippe Rigo, Peyman Amirafshari, Athanasios Kolios & Jannie S. Nielsen 2020, The effect of failure criteria on risk-based inspection planning of offshore wind support structures. in Proceedings of The Seventh International Symposium on Life-cycle Civil Engineering, IALCCE2020