Distribution of individual wave overtopping volumes in shallow water wave conditions

Nørgaard, Jørgen; Andersen, Thomas Lykke; Burcharth, Hans F.

doi:10.1016/j.coastaleng.2013.09.003

Cited by 34 publications

(47 citation statements)

References 9 publications

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“…Predicted wave loads with specific exceedance probabilities using the formulae by Nørgaard et al (2013) and the modified run-up formula were compared to results from the model tests described in Nørgaard et al (2012Nørgaard et al ( , 2013Nørgaard et al ( , and 2014. Good agreement was obtained between measured and predicted wave loads as long as dynamic loads were obtained on the crown wall (exceedance probabilities up to around α = 5% for the evaluated load time series in the present case).…”

Section: Discussionmentioning

confidence: 99%

“…6 for both deep and shallow water wave conditions, where predictions from the wave height distributions are compared to the measurements from the model tests by Nørgaard et al (2012Nørgaard et al ( , 2013Nørgaard et al ( , and 2014 As seen, relatively good performances are obtained in deep and shallow water wave conditions from both the Goda (2010) breaker index method and the Battjes & Groenendijk (2000) distribution. The Rayleigh distribution significantly over-predicts the low-exceedance wave heights in shallow water wave conditions.…”

Section: Wave Height Distribution In Deep and Shallow Watermentioning

confidence: 99%

“…6 and 7 formulae are compared to the measured loads from the model tests by Nørgaard et al (2012Nørgaard et al ( , 2013Nørgaard et al ( , and 2014 in Figs. 10 and 11, respectively.…”

Section: Statistical Distribution Of Wave Loads On Rubble Mound Breakmentioning

confidence: 99%

“…The physical model test setup in the present paper is further described in Nørgaard et al (2012Nørgaard et al ( , 2013Nørgaard et al ( , and 2014). The 2D model tests are performed at Aalborg University in a 25 m long and 1.5 m wide wave flume.…”

Section: Physical Model Test Studymentioning

confidence: 99%

“…A simplified one-dimensional approach described in Burcharth et al (2008) and Nørgaard et al (2012) is used for this analysis, together with the model test data by Nørgaard et al (2012Nørgaard et al ( , 2013Nørgaard et al ( , and 2014.…”

Section: Objectives In Present Papermentioning

confidence: 99%

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Distribution of Wave Loads for Design of Crown Walls in Deep and Shallow Water

Nørgaard

Andersen

2014

Int. Conf. Coastal. Eng.

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This paper puts forward a new method to determine horizontal wave loads on rubble mound breakwater crown walls with specific exceedance probabilities based on the formulae by Nørgaard et al. (2013) as well as presents a new modified version of the wave run-up formula by Van der Meer & Stam (1992). Predictions from the method are compared to measured horizontal wave loads from scaled model tests, and the new method provides results which are in agreement with measured values as long as the wave loads on the crown wall are relatively impulsive. Another aim of the paper has been to compare the displacements of a crown wall exposed to wave loads with different exceedance probabilities in an overload situation (in this case the loads exceeded by 0.1 % and 1/250 of the incident waves). The comparison is made using the assumption that the Eigenfrequency of the crown wall and breakwater is significantly higher than the dynamic wave load impulses on the structure. The relatively small difference in the evaluated exceedance probabilities has a significant influence on the displacement of the monolithic structure. Therefore, probabilistic design tools are recommended. Tools from the present paper will be used in future studies in more detailed investigations on the influence from the load exceedance probability on the stability of crown walls.

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Section: Discussionmentioning

confidence: 99%

Section: Wave Height Distribution In Deep and Shallow Watermentioning

confidence: 99%

“…6 and 7 formulae are compared to the measured loads from the model tests by Nørgaard et al (2012Nørgaard et al ( , 2013Nørgaard et al ( , and 2014 in Figs. 10 and 11, respectively.…”

Section: Statistical Distribution Of Wave Loads On Rubble Mound Breakmentioning

confidence: 99%

Section: Physical Model Test Studymentioning

confidence: 99%

Section: Objectives In Present Papermentioning

confidence: 99%

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Distribution of Wave Loads for Design of Crown Walls in Deep and Shallow Water

Nørgaard

Andersen

2014

Int. Conf. Coastal. Eng.

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Estimation and Prediction of Typhoons and Wave Overtopping in Qingdao, China

Wang

Hao

et al. 2020

J. Ocean Univ. China

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When introducing physics-constrained deep learning solutions to the volumetric super-resolution of scientific data, the training is challenging to converge and always time-consuming. We propose a new hierarchical sampling method based on octree to solve these difficulties. In our approach, scientific data is preprocessed before training, and a hierarchical octreebased data structure is built to guide sampling on the latent context grid. Each leaf node in the octree corresponds to an indivisible subblock of the volumetric data. The dimensions of the subblocks are different, making the number of sample points in each randomly cropped training data block to be adaptive. We reconstruct the octree at intervals according to loss distribution to perform the multi-stage training. With the Rayleigh-Bénard convection problem, we deploy our method to state-of-the-art models. We constructed adequate experiments to evaluate the training performance and model accuracy of our method. Experiments indicate that our sampling optimization improves the convergence performance of physics-constrained deep learning super-resolution solutions. Furthermore, the sample points and training time are significantly reduced with no drop in model accuracy. We also test our method in training tasks of other deep neural networks, and the results show our sampling optimization has extensive effectiveness and applicability. The code is publicly available at https://github.com/xinjiewang/octree-based sampling.

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New relationship for estimation of wave overtopping on vertical walls

Eskandari

Kamalian

2017

China Ocean Eng

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Distribution of individual wave overtopping volumes in shallow water wave conditions

Cited by 34 publications

References 9 publications

Distribution of Wave Loads for Design of Crown Walls in Deep and Shallow Water

Distribution of Wave Loads for Design of Crown Walls in Deep and Shallow Water

Estimation and Prediction of Typhoons and Wave Overtopping in Qingdao, China

New relationship for estimation of wave overtopping on vertical walls

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