Framework for uncertainty quantification of wave-structure interaction in a flume
<|reference_start|>Framework for uncertainty quantification of wave-structure interaction in a flume: In this paper we propose a numerical procedure for the quantification of uncertainties in wave-structure interaction. We utilise the smoothed particle hydrodynamics (SPH) scheme for modelling the wave mechanics, coupled one-way with a finite element method (FEM) for the structural response. Physical wave flumes are extensively used in the study of hydrodynamics especially in wave-structure interaction (WSI) and prediction of forces to near-shore structures in disaster mitigation and offshore structures in the oil and gas, and more recently renewable energy sector. Over the years, numerical wave flumes have been developed extensively to enable the modelling of complex wave-structure interaction. However, most of these studies are deterministic and limited to using either simple flexible beams or rigid monolithic structures to model the structural part in the WSI. Additionally, uncertainties are commonly observed in both wave and structural parameters and need to be accounted for. This work presents a numerical framework to enable uncertainty quantification for wave-structure interaction problems in terms of the forces experienced by the structure. A one-way coupling between SPH with the FEM and uncertainty quantification (UQ) is proposed. We employ the so-called Tokyo wave flume geometry, which has potential for future surrogate modelling in WSI. The developed model is validated using numerical and experimental results from the literature and is used to demonstrate the prediction of probabilistic responses of structures under breaking and non-breaking wave scenarios.<|reference_end|>
@article{luo2024framework,
    title={Framework for uncertainty quantification of wave-structure interaction
  in a flume},
    author={Xiaoyuan Luo and Vijay Nandurdikar and Sangri-Yi and Alistair Revell
  and Georgios Fourtakas and Ajay B. Harish},
    journal={arXiv preprint arXiv:2408.10784},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.10784},
    primaryClass={math.NA cs.NA math-ph math.MP}
}