Waves are important physical phenomena in an ocean,and their accurate prediction is essential for ocean engineering,maritime traffic,and marine early warning systems.This study focuses on the Qinhuangdao Sea area loca...Waves are important physical phenomena in an ocean,and their accurate prediction is essential for ocean engineering,maritime traffic,and marine early warning systems.This study focuses on the Qinhuangdao Sea area located in the Bohai Sea,China.Herein,we use on-site wind data to correct the reanalysis wind data obtained from the European Centre for Medium-Range Weather Forecasts(ECMWF),improving the accuracy of boundary conditions.Then,we use the Simulating WAves Nearshore(SWAN)model to simulate the regional wave field over time.A regional wave-parameter prediction model is then developed using a limited number of sampled data(covering only 2 years,2020–2021);the model is based on the Whale Optimization Algorithm(WOA),convolutional neural networks(CNNs),and long short-term memory(LSTM)neural networks.WOA is used to optimize the CNN and LSTM framework;in this framework,CNN extracts spatial features,and the LSTM network captures temporal features,enabling accurate short and long-term predictions of wave height,period,and direction.The experimental results showed that despite the small sample size,the model achieves a goodness of fit of 0.9957 for wave height prediction,0.9973 for period,and 0.9749 for wave direction in short-term forecasting.As the prediction step size increases,the accuracy of the model decreases.When the prediction step size reaches 9 h,the root mean square error for the prediction of wave height,period,and direction increases to 0.2060 m,0.4582 s,and32.5358°,respectively.The reliability and applicability of the model are further validated by the experimental results.Our findings highlighted the potential of the developed model in operational wave forecasting,even with a limited number of sampled data.展开更多
A hybrid model combining Fully Non-Linear Potential Flow Theory(FNPT)based on the Finite Element Method(FEM)and the Unified Navier-Stokes equation,using the 3D Improved Meshless Local Petrov Galerkin method with Ranki...A hybrid model combining Fully Non-Linear Potential Flow Theory(FNPT)based on the Finite Element Method(FEM)and the Unified Navier-Stokes equation,using the 3D Improved Meshless Local Petrov Galerkin method with Rankine Source(IMLPG_R),is developed to study wave interactions with a porous layer.In previous studies,the above formulations are applied to wave interaction with fixed cylindrical structures.The present study extends this framework by integrating a unified governing equation within the hybrid modeling approach to capture the dynamics of wave interaction with porous media.The porous layers are employed to replicate the wave-dissipating behavior of the structure.A weak coupling strategy is implemented within a designated buffer zone,wherein field variables from the 2D Fully Nonlinear Potential Theory(FNPT)simulations are transferred to the 3D Improved Moving Least Squares-based Petrov-Galerkin(IMLPG_R)model at each time step.This domain decomposition significantly reduces computational cost compared to a full 3D simulation by partitioning the domain into two subregions:the FNPT domain representing the far-field without structures,and the IMLPG_R domain encompassing the porous region.The Unified Navier-Stokes formulation is extended by incorporating additional drag forces governed by Darcy’s law to model the resistance introduced by the porous medium.A stationary background node framework is utilized for interpolation by fluid particles at each time step to accommodate the porous representation.To enhance numerical stability and accuracy,particularly in the presence of sloping boundaries,the Particle Shifting Technique(PST)is integrated into the IMLPG_R model.This implementation involves a modified version of the PST algorithm,where key parameters such as the weight function,velocity ratio,and radius of influence are optimized for IMLPG_R.This is the first time the application of 3D IMLPG_R for porous structure has been reported.Further,the model is subsequently validated against experimental data.展开更多
通过采用水平二维的Boussinesq方程的FUNWAVE-TVD(fully nonlinear wave model with total variation diminishing)数值模型模拟了孤立波在三维珊瑚堡礁附近的波浪传播变形和岸滩爬高。首先通过已有的物理试验对模型进行了验证,随后分...通过采用水平二维的Boussinesq方程的FUNWAVE-TVD(fully nonlinear wave model with total variation diminishing)数值模型模拟了孤立波在三维珊瑚堡礁附近的波浪传播变形和岸滩爬高。首先通过已有的物理试验对模型进行了验证,随后分析了不同珊瑚礁宽度、口门宽度和口门位置对堡礁附近波浪传播变形和爬高的影响。珊瑚礁的存在能够有效减小孤立波的作用,随着珊瑚礁宽度的增加,波高减小得更为迅速,整个环岛的爬高值不断减小,背浪面附近的爬高值很小且存在一定的不稳定性。珊瑚礁对中央岛屿海岸爬高的削弱作用随着珊瑚礁宽度的增加而减小;随着口门宽度的增大,口门附近潟湖内波高增大的范围变大。口门宽度对爬高的影响在中央岛屿迎浪面一定范围内比较显著,随着口门宽度的增大,该范围内中央岛屿迎浪面的爬高增大,最大爬高由双峰向单峰转变,在此范围之外的爬高值几乎不受口门宽度的影响;随着波浪来波方向与口门夹角的增大,口门附近潟湖内孤立波波高增大的范围减小,口门位置的改变仅仅影响岛屿上与口门相接近区域的爬高,这个影响区域随着波浪来波方向与口门夹角的增大向口门后方偏移。展开更多
基金supported by the National Natural Science Foundation of China(Nos.52071057,52171247)the Liaoning Youth Elite Talent Program(No.XLYC220309)。
文摘Waves are important physical phenomena in an ocean,and their accurate prediction is essential for ocean engineering,maritime traffic,and marine early warning systems.This study focuses on the Qinhuangdao Sea area located in the Bohai Sea,China.Herein,we use on-site wind data to correct the reanalysis wind data obtained from the European Centre for Medium-Range Weather Forecasts(ECMWF),improving the accuracy of boundary conditions.Then,we use the Simulating WAves Nearshore(SWAN)model to simulate the regional wave field over time.A regional wave-parameter prediction model is then developed using a limited number of sampled data(covering only 2 years,2020–2021);the model is based on the Whale Optimization Algorithm(WOA),convolutional neural networks(CNNs),and long short-term memory(LSTM)neural networks.WOA is used to optimize the CNN and LSTM framework;in this framework,CNN extracts spatial features,and the LSTM network captures temporal features,enabling accurate short and long-term predictions of wave height,period,and direction.The experimental results showed that despite the small sample size,the model achieves a goodness of fit of 0.9957 for wave height prediction,0.9973 for period,and 0.9749 for wave direction in short-term forecasting.As the prediction step size increases,the accuracy of the model decreases.When the prediction step size reaches 9 h,the root mean square error for the prediction of wave height,period,and direction increases to 0.2060 m,0.4582 s,and32.5358°,respectively.The reliability and applicability of the model are further validated by the experimental results.Our findings highlighted the potential of the developed model in operational wave forecasting,even with a limited number of sampled data.
基金funded by Prime Minister’s Research Fellowship(PMRF),grant number SB22230924OEPMRF008608.
文摘A hybrid model combining Fully Non-Linear Potential Flow Theory(FNPT)based on the Finite Element Method(FEM)and the Unified Navier-Stokes equation,using the 3D Improved Meshless Local Petrov Galerkin method with Rankine Source(IMLPG_R),is developed to study wave interactions with a porous layer.In previous studies,the above formulations are applied to wave interaction with fixed cylindrical structures.The present study extends this framework by integrating a unified governing equation within the hybrid modeling approach to capture the dynamics of wave interaction with porous media.The porous layers are employed to replicate the wave-dissipating behavior of the structure.A weak coupling strategy is implemented within a designated buffer zone,wherein field variables from the 2D Fully Nonlinear Potential Theory(FNPT)simulations are transferred to the 3D Improved Moving Least Squares-based Petrov-Galerkin(IMLPG_R)model at each time step.This domain decomposition significantly reduces computational cost compared to a full 3D simulation by partitioning the domain into two subregions:the FNPT domain representing the far-field without structures,and the IMLPG_R domain encompassing the porous region.The Unified Navier-Stokes formulation is extended by incorporating additional drag forces governed by Darcy’s law to model the resistance introduced by the porous medium.A stationary background node framework is utilized for interpolation by fluid particles at each time step to accommodate the porous representation.To enhance numerical stability and accuracy,particularly in the presence of sloping boundaries,the Particle Shifting Technique(PST)is integrated into the IMLPG_R model.This implementation involves a modified version of the PST algorithm,where key parameters such as the weight function,velocity ratio,and radius of influence are optimized for IMLPG_R.This is the first time the application of 3D IMLPG_R for porous structure has been reported.Further,the model is subsequently validated against experimental data.
文摘通过采用水平二维的Boussinesq方程的FUNWAVE-TVD(fully nonlinear wave model with total variation diminishing)数值模型模拟了孤立波在三维珊瑚堡礁附近的波浪传播变形和岸滩爬高。首先通过已有的物理试验对模型进行了验证,随后分析了不同珊瑚礁宽度、口门宽度和口门位置对堡礁附近波浪传播变形和爬高的影响。珊瑚礁的存在能够有效减小孤立波的作用,随着珊瑚礁宽度的增加,波高减小得更为迅速,整个环岛的爬高值不断减小,背浪面附近的爬高值很小且存在一定的不稳定性。珊瑚礁对中央岛屿海岸爬高的削弱作用随着珊瑚礁宽度的增加而减小;随着口门宽度的增大,口门附近潟湖内波高增大的范围变大。口门宽度对爬高的影响在中央岛屿迎浪面一定范围内比较显著,随着口门宽度的增大,该范围内中央岛屿迎浪面的爬高增大,最大爬高由双峰向单峰转变,在此范围之外的爬高值几乎不受口门宽度的影响;随着波浪来波方向与口门夹角的增大,口门附近潟湖内孤立波波高增大的范围减小,口门位置的改变仅仅影响岛屿上与口门相接近区域的爬高,这个影响区域随着波浪来波方向与口门夹角的增大向口门后方偏移。
