Kenan Sehic: Uncertainty Quantification is a relatively new field in the scientific computing and getting more attention as computer’s power increases. Uncertainty quantification is giving a meaning to the results obtained by numerical simulations.
The purpose of the PhD project is to develop, implement, validate and apply numerical Uncertainty Quantification methods to achieve accelerated and improved prediction of marine loads on offshore wind turbines.
The research will be conducted as a collaboration between DTU Compute and DTU Wind Energy within DeRisk Project. In marine engineering is very important to design structures that can withstand extreme failures due to wave-induced loadings like wind turbines. Usually these parameters, related to extreme wave scenarios, can be estimated from direct measurements, experiments and simulation tools. These validation procedures are subject to uncertainties that could lead to unexpected failures. The proper inclusion or the study of the influence of these uncertainties on the resulting engineering analysis and decisions requires ultimately a shift from a deterministic design approach to a probabilistic design approach. Modern numerical models for wave transformation enable accurate deterministic computation of marine loads on offshore structures, but in a realistic setting several model parameters, such as incident wave elevation and bottom friction, are stochastic variables.
The vision for this project is to surpass the quality of the load prediction and parameter sensitivity analysis achieved by the Monte Carlo approach commonly used in offshore engineering today. To this end, a promising approach is to employ a full analysis of the temporal evolution of the involved probability density functions, rather than to only consider a first few statistical moments of the stochastic variables. The latter, incomplete analysis characterizes a majority of the well-known approaches for uncertainty quantification.
PhD project title: Numerical Uncertainty Quantification for Stochastic Wave Loads
Effective start/end date 15/01/2017 → 14/01/2020
Main supervisor: Mirza Karamehmedovic, Co-supersor: Henrik Bredmose, Co-supervisor: John D. Sørensen
Keywords: Uncertainty Quantification, Fokker Planck Equation, Polynomial Chaos, Wave loads, Stochastic, Monte Carlo, Sensitivity Analysis