Incremental wind-wave analysis of the structural capacity of offshore wind turbine support structures under extreme loading

•Incremental wind-wave analysis approach for the capacity of OWT support structures is proposed.•Single- and two-parameter IWWA accounts for independent and joint loading intensities of wind and wave.•IWWA calculations of OWT monopile and jacket Examples at Atlantic marine sites are performed.•The probability of failure and structural reliabilities of monopile and jackets are obtained.

Offshore wind turbine (OWT) support structures are subjected to non-proportional environmental wind and wave load patterns with respect to increases in wave height and with respect to wind and wave combined loading. Traditional approaches to estimating the ultimate capacity of offshore support structures are not ideally suited to analysis of OWTs. In this paper, the concept of incremental wind-wave (IWWA) analysis of the structural capacity of OWT support structures is proposed. The approach uses static pushover analysis of OWT support structures subject to wind and wave combined load patterns corresponding to increasing mean return period (MRP). The IWWA framework can be applied as a one-parameter approach (IWWA1) in which the MRP for the wind and wave conditions is assumed to be the same or a two-parameter approach (IWWA2) in which the MRPs associated with wind and wave conditions are related to a joint probability density function characterizing the wind and wave conditions at the site. Example calculations for monopile and jacket supported OWTs at Atlantic marine sites are performed under both one parameter and two parameters IWWA framework. The analyses illustrate that: the results of an IWWA analysis are site specific; and structural response can be dominated by either wind or wave conditions depending on structural characteristics and site conditions. Finally, reliability analyses for both examples excluding uncertainties in structural resistance are estimated based on their IWWA results and probabilistic models for site environmental conditions.