FLOAT: Fatigue-Aware Design Optimization of Floating Offshore Wind Turbine Towers

TL;DR

This paper introduces FLOAT, a framework that significantly accelerates fatigue-aware design optimization of floating offshore wind turbine towers by combining lightweight estimation, probabilistic sampling, and high-performance modeling, enabling practical, reliable, and scalable tower design.

Contribution

FLOAT integrates a lightweight fatigue estimator, probabilistic wind-wave sampling, and high-fidelity calibration to enable efficient, fatigue-aware optimization of FOWT towers, reducing computational costs and supporting innovative design.

Findings

Extended fatigue life from 9 months to 25 years.

Reduced simulation requirements by orders of magnitude.

Achieved lowest-mass fatigue-compliant tower design.

Abstract

Upscaling is central to offshore wind's cost-reduction strategy, with increasingly large rotors and nacelles requiring taller and stronger towers. In Floating Offshore Wind Turbines (FOWTs), this trend amplifies fatigue loads due to coupled wind-wave dynamics and platform motion. Conventional fatigue evaluation requires millions of high-fidelity simulations, creating prohibitive computational costs and slowing design innovation. This paper presents FLOAT (Fatigue-aware Lightweight Optimization and Analysis for Towers), a framework that accelerates fatigue-aware tower design. It integrates three key contributions: a lightweight fatigue estimation method that enables efficient optimization, a Monte Carlo-based probabilistic wind-wave sampling approach that reduces required simulations, and enhanced high-fidelity modeling through pitch/heave-platform calibration and High-Performance Computing execution. The framework is applied to the IEA 22 MW FOWT tower, delivering, to the authors' knowledge, the first fatigue-oriented redesign of this benchmark model: FLOAT 22 MW FOWT tower. Validation against 6,468 simulations shows that the optimized tower extends the estimated fatigue life from 9 months to 25 years while avoiding resonance, and that the lightweight fatigue estimator provides conservative predictions with a mean relative error of -8.6%. Achieving this lifetime requires increased tower mass, yielding the lowest-mass fatigue-compliant design. All results and the reported lifetime extension are obtained within the considered fatigue scope (DLC 1.2, aligned wind-wave conditions). By reducing simulation requirements by orders of magnitude, FLOAT enables reliable and scalable tower design for next-generation FOWTs, bridging industrial needs and academic research while generating high-fidelity datasets that can support data-driven and AI-assisted design methodologies.