Postdoc “Benchmarks of methods estimating the fatigue and optimizing the layout of reference Floating Offshore Wind Farms”

The postdoctoral student will contribute to Phase 2 of IEA Wind TCP Task 49, within the IDEA project on the design and optimization of reference floating wind farms. The first part of the work will focus on Task 1.1, which investigates how the discretization, or binning, of environmental and operational conditions affects fatigue-load and damage estimation. The student will contribute to an international benchmark, first for an isolated floating wind turbine and then for an entire wind farm. IFPEN’s contribution will use MAKSUR supervised adaptive kriging approach to efficiently sample wind, wave, current and wake conditions leading to fatigue damage accumulation.

The second part will address Task 2.4, dedicated to benchmarking optimization methods for floating wind-farm layouts. Using the OptiWITS software, the postdoctorate student will develop and validate an optimization strategy that accounts for fatigue constraints, together with production, extreme loads and mooring-system requirements. Metamodels will be used to reduce the computational cost of fatigue evaluations. The computations will be compared to approaches of IDEA partners and disseminated in international conferences.

The doctoral degree must have been obtained no more than three years before the start of the postdoctoral position. Please note that the position is subject to a pending.

Participate in technical meetings with partners involved in IEA Wind TCP Task 49

Prepare case studies for IFPEN’s contributions

• Perform fatigue-load and damage calculations for a single floating wind turbine using the IFPEN’s MAKSUR approach
• Extend the fatigue-estimation methodology to the wind-farm scale, taking wake effects into account
• Perform calculations and analyze floating wind-farm layout optimization using the OptiWITS software, while considering production, load, fatigue and mooring-system constraints
• Compare the results with those obtained by the IDEA partners and contribute to the assessment of accuracy, robustness and computational cost
• Present the research results in collaboration with IDEA’s partners at international conferences

Occasional travel lasting a few days within France and abroad (for example to attend an international conference). The role can be carried out partly remotely.

Technical skills

• Knowledge of offshore wind turbines or the offshore industry
• Experience with wind-turbine, floating-structure or coupled aero-hydro-servo-elastic simulation tools would be an advantage
• Proficiency in Python for data processing, numerical simulations and statistical analysis
• Familiarity with optimization methods and High-Performance computing
• Ability to prepare clear technical documentation and communicate scientific results in English

Other skills

• Teamwork
• Enthusiasm for scientific research
• Independence
• Attention to detail

Languages

A good knowledge of English is essential (minimum C1 level)

PhD in solid mechanics or fluid mechanics with an application to wind power or offshore engineering

For further information and to apply, please contact: alice.nassor@ifpen.fr