
Multi-scale calibration of a non-hydrostatic model for wave ...
2023年10月1日 · Depth-averaged non-hydrostatic models such as XBNH (XBeach Non-Hydrostatic) are computationally cost-effective yet accurate tools to numerically simulate random wave runup. XBNH includes a number of calibration …
BEWARE database: A Bayesian-based system to assess wave ...
2017年11月14日 · A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, XBNH) was used to create a large synthetic database for use in a Bayesian Estimator for Wave Attack in Reef Environments (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts.
Modeling hurricane wave propagation and attenuation after ...
2024年1月15日 · In this study, the non-hydrostatic XBeach model (XBNH) was validated and applied to investigate wave propagation, breaking, and overtopping sand dunes in the coastal zone during various stages of the storm surge in Mexico Beach, Florida during Hurricane Michael (a Category 5 hurricane).
A Bayesian-Based System to Assess Wave-Driven Flooding ...
2017年11月2日 · The XBNH process-based numerical wave and water level model is shown to be capable of reproducing wave transformation processes on fringing reefs, including resonant reef flat amplification.
Simulating wave runup on an intermediate–reflective beach ...
Here, we use an incident-band wave-resolving, non-hydrostatic version of the XBeach model (XBNH) to simulate wave runup observed during the SandyDuck '97 experiment on an intermediate–reflective sandy beach.
A physics-informed machine learning model for time-dependent ...
2024年3月1日 · In this study, a physics-informed machine learning-based approach is proposed to efficiently and accurately simulate time-series wave runup. The methodology combines the computational efficiency of the Surfbeat (XBSB) mode with the accuracy of the nonhydrostatic (XBNH) mode of the XBeach model.
A Bayesian-based system to assess wave-driven flooding ...
A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, “XBNH”) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts.
[2401.08684] A Physics-informed machine learning model for ...
2024年1月12日 · In this study, a physics-informed machine learning-based approach is proposed to efficiently and accurately simulate time-series wave runup. The methodology combines the computational efficiency of the Surfbeat (XBSB) mode with the accuracy of the nonhydrostatic (XBNH) mode of the XBeach model.
XBeach: Non-hydrostatic model: Validation, verification and ...
2010年1月1日 · Depth-averaged non-hydrostatic models such as XBNH (XBeach Non-Hydrostatic) are computationally cost-effective yet accurate tools to numerically simulate random wave runup.
BEWARE database: A Bayesian-based system to assess wave ...
2017年11月13日 · A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts.
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