Quantum phenomena in numerical wave propagation

1989 ◽  
Vol 9 (6) ◽  
pp. 623-650 ◽  
Author(s):  
Robert Vichnevetsky
1988 ◽  
Vol 1 (21) ◽  
pp. 30 ◽  
Author(s):  
J.A. Vogel ◽  
A.C. Radder ◽  
J.H. De Reus

The performance of two numerical wave propagation models has been investigated by comparison with field data. The first model is a refractiondiffraction model based on the parabolic equation method. The second is a refraction model based on the wave action equation, using a regular grid. Two field situations, viz. a tidal inlet and a river estuary along the Dutch coast, were used to determine the influence of the local wind on waves behind an island and a breaker zone. It may be concluded from the results of the computations and measurements that a much better agreement is obtained when wave growth due to wind is properly accounted for in the numerical models. In complicated coastal areas the models perform well for both engineering and research purposes.


2019 ◽  
Author(s):  
Solvi Thrastarson ◽  
Martin van Driel ◽  
Lion Krischer ◽  
Dirk-Philip van Herwaarden ◽  
Christian Boehm ◽  
...  

Author(s):  
Hans Bihs ◽  
Weizhi Wang ◽  
Csaba Pakozdi ◽  
Arun Kamath

Abstract In situations where the calculation of ocean wave propagation and impact on structures are required, fast numerical solvers are desired in order to find relevant wave events. Computational fluid dynamics (CFD)-based numerical wave tanks (NWTs) emphasize on the hydrodynamic details such as fluid–structure interaction, which make them less ideal for the event identification due to the large computational resources involved. Therefore, a computationally efficient numerical wave model is needed to identify the events both for offshore deep-water wave fields and coastal wave fields where the bathymetry and coastline variations have strong impact on wave propagation. In the current paper, a new numerical wave model is represented that solves the Laplace equation for the flow potential and the nonlinear kinematic and dynamics free surface boundary conditions. This approach requires reduced computational resources compared to CFD-based NWTs. The resulting fully nonlinear potential flow solver REEF3D::FNPF uses a σ-coordinate grid for the computations. This allows the grid to follow the irregular bottom variation with great flexibility. The free surface boundary conditions are discretized using fifth-order weighted essentially non-oscillatory (WENO) finite difference methods and the third-order total variation diminishing (TVD) Runge–Kutta scheme for time stepping. The Laplace equation for the potential is solved with Hypre’s stabilized bi-conjugated gradient solver preconditioned with geometric multi-grid. REEF3D::FNPF is fully parallelized following the domain decomposition strategy and the message passing interface (MPI) communication protocol. The numerical results agree well with the experimental measurements in all tested cases and the model proves to be efficient and accurate for both offshore and coastal conditions.


2019 ◽  
Author(s):  
Hans Bihs ◽  
Weizhi Wang ◽  
Tobias Martin ◽  
Arun Kamath

Abstract In situations where the calculation of ocean wave propagation and impact on offshore structures is required, fast numerical solvers are desired in order to find relevant wave events in a first step. After the identification of the relevant events, Computational Fluid Dynamics (CFD) based Numerical Wave Tanks (NWT) with an interface capturing two-phase flow approach can be used to resolve the complex wave structure interaction, including breaking wave kinematics. CFD models emphasize detail of the hydrodynamic physics, which makes them not the ideal candidate for the event identification due to the large computational resources involved. In the current paper a new numerical wave model is represented that solves the Laplace equation for the flow potential and the nonlinear kinematic and dynamics free surface boundary conditions. This approach requires reduced computational resources compared to CFD based NWTs. In contrast to existing approaches, the resulting fully nonlinear potential flow solver REEF3D::FNPF uses a σ-coordinate grid for the computations. Solid boundaries are incorporated through a ghost cell immersed boundary method. The free surface boundary conditions are discretized using fifth-order WENO finite difference methods and the third-order TVD Runge-Kutta scheme for time stepping. The Laplace equation for the potential is solved with Hypres stabilized bi-conjugated gradient solver preconditioned with geometric multi-grid. REEF3D::FNPF is fully parallelized following the domain decomposition strategy and the MPI communication protocol. The model is successfully tested for wave propagation benchmark cases for shallow water conditions with variable bottom as well as deep water.


2019 ◽  
Vol 33 (4) ◽  
pp. 364-376 ◽  
Author(s):  
Woo-Dong Lee ◽  
Yeon-Myeong Jeong ◽  
Kyu-Nam Choi ◽  
Dong-Soo Hur

Modelling ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 355-369
Author(s):  
Giao Vu ◽  
Jithender J. Timothy ◽  
Divya S. Singh ◽  
Leslie A. Saydak ◽  
Erik H. Saenger ◽  
...  

High costs for the repair of concrete structures can be prevented if damage at an early stage of degradation is detected and precautionary maintenance measures are applied. To this end, we use numerical wave propagation simulations to identify simulated damage in concrete using convolutional neural networks. Damage in concrete subjected to compression is modeled at the mesoscale using the discrete element method. Ultrasonic wave propagation simulation on the damaged concrete specimens is performed using the rotated staggered finite-difference grid method. The simulated ultrasonic signals are used to train a CNN-based classifier capable of classifying three different damage stages (microcrack initiation, microcrack growth and microcrack coalescence leading to macrocracks) with an overall accuracy of 77%. The performance of the classifier is improved by refining the dataset via an analysis of the averaged envelope of the signal. The classifier using the refined dataset has an overall accuracy of 90%.


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