Abstract. The need for cost-effective support structure designs for offshore wind turbines has led to continued interest in the
development of design optimization methods. So far, almost no studies have considered the effect of uncertainty, and
hence probabilistic constraints, on the support structure design optimization problem. In this work, we present a
general methodology that implements recent developments in gradient-based design optimization, in particular the use
of analytical gradients, within the context of reliability-based design optimization methods. Gradient-based
optimization is typically more efficient and has more well-defined convergence properties than gradient-free methods,
making this the preferred paradigm for reliability-based optimization where possible. By an assumed factorization of
the uncertain response into a design-independent, probabilistic part and a design-dependent but completely
deterministic part, it is possible to computationally decouple the reliability analysis from the design
optimization. Furthermore, this decoupling makes no further assumption about the functional nature of the stochastic
response, meaning that high-fidelity surrogate modeling through Gaussian process regression of the probabilistic part
can be performed while using analytical gradient-based methods for the design optimization. We apply this methodology
to several different cases based around a uniform cantilever beam and the OC3 Monopile and different loading and
constraint scenarios. The results demonstrate the viability of the approach in terms of obtaining reliable, optimal
support structure designs and furthermore show that in practice only a limited amount of additional computational
effort is required compared to deterministic design optimization. While there are some limitations in the applied
cases, and some further refinement might be necessary for applications to high-fidelity design scenarios, the
demonstrated capabilities of the proposed methodology show that efficient reliability-based optimization for offshore
wind turbine support structures is feasible.
Modifications of the Charged Balls Method
