Abstract
Obtaining the hydrodynamic pressure distribution on the wetted surface of floating structures is a critical step in structural analysis and is commonly achieved through pressure regeneration based on predicted global dynamic responses. Using derived hydrodynamic coefficients, various dynamic modeling approaches, including Cummins-equation-based nonlinear time-domain modeling, statistical linearization, and Lorentz linearization, can be applied to solve for the global dynamics of structures subjected to specific wave conditions. These dynamic modeling approaches differ in both computational efficiency and modeling fidelity. Despite their widespread use, a systematic comparison of these approaches, particularly between statistical and Lorentz linearization in predicting global dynamics and regenerated pressure fields, remains limited. This study addresses this gap by conducting a comparative study of linear-potential-flow-based dynamic modeling approaches using a generic cylindrical floater, incorporating a representative nonlinear external machinery effect through different modeling approaches. The resulting global responses are used to regenerate hydrodynamic pressure distributions, showing that all the dynamic modeling approaches agree well under low wave steepness. As wave steepness increases, the prediction performance of statistical linearization, Lorentz linearization, and a simplified Lorentz linearization, gradually decreases relative to the nonlinear time-domain model. Among these, the statistical linearization approach provides results closer to the nonlinear time-domain model than both Lorentz-based linearization methods, particularly in capturing global dynamics and reconstructing hydrodynamic pressure distributions under relatively high wave steepness. Given its high computational efficiency, the statistical linearization approach has the potential to be further developed as an efficient alternative modeling for estimating dynamic responses and hydrodynamic pressure distributions.