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@ -119,3 +119,19 @@
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year={2020},
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year={2020},
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publisher={Elsevier}
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publisher={Elsevier}
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}
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}
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@book{violeau2012,
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title={Fluid mechanics and the SPH method: theory and applications},
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author={Violeau, Damien},
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year={2012},
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publisher={Oxford University Press}
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}
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@article{violeau2007,
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title={Numerical modelling of complex turbulent free-surface flows with the SPH method: an overview},
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author={Violeau, Damien and Issa, Reza},
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journal={International Journal for Numerical Methods in Fluids},
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volume={53},
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number={2},
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pages={277--304},
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year={2007},
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publisher={Wiley Online Library}
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}
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152
nature/main.tex
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nature/main.tex
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@ -56,47 +56,59 @@ initiation. A parametrisation of waves depending on their source is also used to
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on the type of scenario --- wave or tsunami. Those equations were later revised by \textcite{nandasena2011}, as they
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on the type of scenario --- wave or tsunami. Those equations were later revised by \textcite{nandasena2011}, as they
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were found to be partially incorrect. A revised formulation based on the same considerations was provided.
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were found to be partially incorrect. A revised formulation based on the same considerations was provided.
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The assumptions on which \citeauthor{nott2003, nandasena2011} are based were then critisized by \textcite{weiss2015}. In
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The assumptions on which \textcite{nott2003, nandasena2011} are based were then critisized by \textcite{weiss2015}. In
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fact, according to them, the initiation of movement is not sufficient to guarantee block displacement.
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fact, according to them, the initiation of movement is not sufficient to guarantee block displacement.
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\textcite{weiss2015} highlights the importance of the time dependency on block displacement. A method is proposed that
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\textcite{weiss2015} highlights the importance of the time dependency on block displacement. A method is proposed that
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allows to find the wave amplitude that lead to block displacement.
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allows to find the wave amplitude that lead to block displacement. Additionally, more recent research by
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\textcite{lodhi2020} has shown that the equations proposed by \textcite{nott2003, nandasena2011} tend to overestimate
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the minimum flow velocity needed to displace a block.
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% Lack of observations -> observation
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% Lack of observations -> observation
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Whether it is \textcite{nott2003}, \textcite{nandasena2011} or \textcite{weiss2015}, all the proposed analytical
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Whether it is \textcite{nott2003}, \textcite{nandasena2011} or \textcite{weiss2015}, all the proposed analytical
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equations suffer from a major flaw; they are all based on simplified analytical models and statistical analysis.
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equations suffer from a major flaw: they are all based on very simplified analytical models and statistical analysis.
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Unfortunately, no block displacement event seems to have been observed directly in the past.
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Unfortunately, no block displacement event seems to have been observed directly in the past, and those events are
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difficult to predict.
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In this paper, we study such an event. On February 28, 2017, a \SI{50}{\tonne} concrete block was dropped by a wave on
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In this paper, we study such an event. On February 28, 2017, a \SI{50}{\tonne} concrete block was dropped by a wave on
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the crest of the Artha breakwater. Luckily, the event was captured by a photographer, and a wave buoy located
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the crest of the Artha breakwater (Figure~\ref{fig:photo}). Luckily, the event was captured by a photographer, and a
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\SI{1.2}{\km} offshore captured the seastate. Information from the photographer allowed to establish the approximate
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wave buoy located \SI{1.2}{\km} offshore captured the seastate. Information from the photographer allowed to establish
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time at which the block displacement occured. The goal of this paper is to model the hydrodynamic conditions near the
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the approximate time at which the block displacement occured. The goal of this paper is to model the hydrodynamic
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breakwater that lead to the displacement of the \SI{50}{\tonne} concrete block.
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conditions near the breakwater that lead to the displacement of the \SI{50}{\tonne} concrete block.
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% Modeling flow accounting for porous media
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% Modeling flow accounting for porous media
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Several approaches can be used when modelling flow near a breakwater. Depth-averaged models can be used to study the
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Several approaches can be used when modelling flow near a breakwater. Depth-averaged models can be used to study the
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transformation of waves on complex bottoms. Studying the hydrodynamic conditions under the surface can be achieved using
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transformation of waves on complex bottoms. Studying the hydrodynamic conditions under the surface can be achieved
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smoothed-particles hydrodynamics (SPH) or volume of fluid (VOF) models. SPH models rely on a Lagrangian representation
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using smoothed-particles hydrodynamics (SPH) or volume of fluid (VOF) models. SPH models rely on a Lagrangian
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of the fluid, while VOF models rely on an Eulerian representation. VOF models are generally more mature for the study of
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representation of the fluid \parencite{violeau2012}, while VOF models rely on an Eulerian representation. VOF models
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multiphase incompressible flows.
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are generally more mature for the study of multiphase incompressible flows, while SPH models generally require more
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processing power for similar results \parencite{violeau2007}.
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In this paper, we first use a one-dimensionnal depth-averaged non-linear non-hydrostatic model to verify that the signal
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In this paper, we first use a one-dimensionnal depth-averaged non-linear non-hydrostatic model to verify that the
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measured by the wave buoy can be used as an incident wave input for the determination of hydrodynamic conditions near
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signal measured by the wave buoy can be used as an incident wave input for the determination of hydrodynamic conditions
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the breakwater. For this model, we use a SWASH model \parencite{zijlema2011} already calibrated by \textcite{poncet2021}
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near the breakwater. For this model, we use a SWASH model \parencite{zijlema2011} already calibrated by
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on a domain reaching \SI{1450}{\m} offshore of the breakwater.
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\textcite{poncet2021} on a domain reaching \SI{1450}{\m} offshore of the breakwater.
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Then, we use a nested VOF model in two vertical dimensions that uses the output from the larger scale SWASH model as
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Then, we use a nested VOF model in two vertical dimensions that uses the output from the larger scale SWASH model as
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initial and boundary conditions to obtain the hydrodynamic conditions on the breakwater. The models uses olaFlow
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initial and boundary conditions to obtain the hydrodynamic conditions on the breakwater. The model uses olaFlow
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\parencite{higuera2015}, a VOF model based on volume averaged Reynolds averaged Navier-Stokes (VARANS) equations, and
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\parencite{higuera2015}, a VOF model based on volume averaged Reynolds averaged Navier-Stokes (VARANS) equations, and
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which relies on a macroscopic representation of the porous armour of the breakwater. The model is qualitatively
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which relies on a macroscopic representation of the porous armour of the breakwater. The model is qualitatively
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calibrated using photographs from the storm of February 28, 2017. Results from the nested models are finally compared to
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calibrated using photographs from the storm of February 28, 2017. Results from the nested models are finally compared
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the analytical equations provided by \textcite{nandasena2011}.
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to the analytical equations provided by \textcite{nandasena2011}.
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\begin{figure*}
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\centering
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\includegraphics[height=.4\textwidth]{fig/pic1.jpg}
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\includegraphics[height=.4\textwidth]{fig/pic2.jpg}
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\caption{Photographs taken during and after the wave that displaced a \SI{50}{\tonne} concrete block onto the Artha
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breakwater.}\label{fig:photo}
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\end{figure*}
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\section{Results}
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\section{Results}
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\subsection{Identified wave}
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\subsection{Identified wave}
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Preliminary work with the photographer allowed to identify the time at which the block displacement event happened.
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Preliminary work with the photographer allowed to identify the time at which the block displacement event happened.
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Using the data from the wave buoy located \SI{1250}{\m} offshore of the Artha breakwater, a seamingly abnormally large
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Using the data from the wave buoy located \SI{1250}{\m} offshore of the Artha breakwater, a seamingly abnormally large
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wave of \SI{14}{\m} amplitude was identified that is supposed to have lead to the block displacement.
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wave of \SI{14}{\m} amplitude was identified that is supposed to have led to the block displacement.
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Initial analysis of the buoy data plotted in Figure~\ref{fig:wave} shows that the movement of the buoy follows two
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Initial analysis of the buoy data plotted in Figure~\ref{fig:wave} shows that the movement of the buoy follows two
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orbitals that correspond to an incident wave direction. These results would indicate that the identified wave is
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orbitals that correspond to an incident wave direction. These results would indicate that the identified wave is
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@ -115,14 +127,10 @@ with a period of over \SI{30}{\s}.
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\subsection{Reflection analysis}
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\subsection{Reflection analysis}
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The results from the large scale SWASH model using two configurations --- one of them being the real bathymetry, and the
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The results from the large scale SWASH model using two configurations --- one of them being the real bathymetry, and
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other being a simplified bathymetry without the breakwater --- are compared in Figure~\ref{fig:swash}. The results
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the other being a simplified bathymetry without the breakwater --- are compared in Figure~\ref{fig:swash}. The results
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obtained with both simulations show a maximum wave amplitude of \SI{13.9}{\m} for the real bathymetry, and \SI{12.1}{\m}
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obtained with both simulations show a maximum wave amplitude of \SI{13.9}{\m} for the real bathymetry, and
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in the case where the breakwater is removed.
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\SI{12.1}{\m} in the case where the breakwater is removed.
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The 13\% difference between those values highlights the existence of a notable amount of reflection at the buoy.
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Nonetheless, the gap between the values is still fairly small and the extreme wave identified on February 28, 2017 at
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17:23:08 could still be considered as an incident wave.
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\begin{figure*}
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\begin{figure*}
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\centering
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\centering
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@ -146,12 +154,10 @@ crest increases, with a zone reaching \SI{400}{\m} long in front of the wave whe
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qualitatively estimated position of the wave front.}\label{fig:swash_trans}
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qualitatively estimated position of the wave front.}\label{fig:swash_trans}
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\end{figure*}
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\end{figure*}
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\subsection{Wavelet analysis}
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In an attempt to understand the identified wave, a wavelet analysis is conducted on raw buoy data as well as at
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In an attempt to understand the identified wave, a wavelet analysis is conducted on raw buoy data as well as at
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different points along the SWASH model using the method proposed by \textcite{torrence1998}. The results are displayed
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different points along the SWASH model using the method proposed by \textcite{torrence1998}. The results are displayed
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in Figure~\ref{fig:wavelet} and Figure~\ref{fig:wavelet_sw}. The wavelet power spectrum shows that the major component
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in Figure~\ref{fig:wavelet} and Figure~\ref{fig:wavelet_sw}. The wavelet power spectrum shows that the major component
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in the identified wave is a high energy infragravity wave, with a period of around \SI{60}{\s}.
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in identified rogue waves is a high energy infragravity wave, with a period of around \SI{60}{\s}.
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The SWASH model seems to indicate that the observed transformation of the wave can be characterized by a transfer of
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The SWASH model seems to indicate that the observed transformation of the wave can be characterized by a transfer of
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energy from the infragravity band to shorter waves from around \SI{600}{\m} to \SI{300}{\m}, and returning to the
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energy from the infragravity band to shorter waves from around \SI{600}{\m} to \SI{300}{\m}, and returning to the
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@ -159,8 +165,9 @@ infragravity band at \SI{200}{\m}.
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\begin{figure*}
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\begin{figure*}
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\centering
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\centering
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\includegraphics{fig/wavelet9312.pdf}
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\includegraphics{fig/wavelet.pdf}
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\caption{Normalized wavelet power spectrum from the raw buoy timeseries.}\label{fig:wavelet}
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\caption{Normalized wavelet power spectrum from the raw buoy timeseries for identified rogue waves on february 28,
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2017.}\label{fig:wavelet}
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\end{figure*}
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\end{figure*}
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\begin{figure*}
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\begin{figure*}
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\centering
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\centering
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@ -172,16 +179,17 @@ infragravity band at \SI{200}{\m}.
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The two-dimensionnal olaFlow model near the breakwater allowed to compute the flow velocity near and on the breakwater
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The two-dimensionnal olaFlow model near the breakwater allowed to compute the flow velocity near and on the breakwater
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during the passage of the identified wave. The results displayed in Figure~\ref{fig:U} show that the flow velocity
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during the passage of the identified wave. The results displayed in Figure~\ref{fig:U} show that the flow velocity
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reaches a maximum of \SI{14.5}{\m\per\s} towards the breakwater during the identified extreme wave. Although the maximum
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reaches a maximum of \SI{14.5}{\m\per\s} towards the breakwater during the identified extreme wave. Although the
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reached velocity is slightly lower than earlier shorter waves (at $t=\SI{100}{\s}$ and $t=\SI{120}{\s}$, with a maximum
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maximum reached velocity is similar to earlier shorter waves, the flow velocity remains high for twice as long as
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velocity of \SI{17.3}{\m\per\s}), the flow velocity remains high for twice as long as during those earlier waves. The
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during those earlier waves. The tail of the identified wave also exhibits a water level over \SI{5}{\m} for over
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tail of the identified wave also exhibits a water level over \SI{5}{\m} for over \SI{40}{\s}.
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\SI{40}{\s}.
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\begin{figure*}
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\begin{figure*}
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\centering
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\centering
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\includegraphics{fig/U.pdf}
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\includegraphics{fig/U.pdf}
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\caption{Horizontal flow velocity computed with the olaFlow model at $x=\SI{-20}{\m}$ on the breakwater armor. The
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\caption{Horizontal flow velocity computed with the olaFlow model at $x=\SI{-20}{\m}$ on the breakwater armor.
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identified wave reaches this point around $t=\SI{175}{\s}$.}\label{fig:U}
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Bottom: horizontal flow velocity at $z=\SI{5}{\m}$. The identified wave reaches this point around
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$t=\SI{175}{\s}$.}\label{fig:U}
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\end{figure*}
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\end{figure*}
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\section{Discussion}
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\section{Discussion}
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@ -194,12 +202,19 @@ twice the significant wave height over a given period. The identified wave fits
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rogue waves often occur from non-linear superposition of smaller waves. This seems to be what we observe on
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rogue waves often occur from non-linear superposition of smaller waves. This seems to be what we observe on
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Figure~\ref{fig:wave}.
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Figure~\ref{fig:wave}.
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The wavelet power spectrum shows that a very prominent infragravity component is present, which usually corresponds to
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As displayed in Figure~\ref{fig:wavelet}, a total of 4 rogue waves were identified on february 28, 2017 in the raw buoy
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non-linear interactions of smaller waves. \textcite{dysthe2008} mentions that such waves in coastal waters are often the
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timeseries using the wave height criteria proposed by \textcite{dysthe2008}. The wavelet power spectrum shows that a
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result of refractive focusing. On February 28, 2017, the frequency of rogue waves was found to be of 1 wave per 1627,
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very prominent infragravity component is present, which usually corresponds to non-linear interactions of smaller
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which is considerably more than the excedance probability of 1 over 10\textsuperscript4 calculated by
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waves. \textcite{dysthe2008} mentions that such waves in coastal waters are often the result of refractive focusing. On
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\textcite{dysthe2008}. Additionnal studies should be conducted to understand focusing and the formation of rogue waves
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February 28, 2017, the frequency of rogue waves was found to be of 1 wave per 1627, which is considerably more than the
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in front of the Saint-Jean-de-Luz bay.
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excedance probability of 1 over 10\textsuperscript4 calculated by \textcite{dysthe2008}. Additionnal studies should be
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conducted to understand focusing and the formation of rogue waves in front of the Saint-Jean-de-Luz bay.
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An important point to note is that rogue waves are often short-lived: their nature means that they often separate into
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shorter waves shortly after appearing. A reason for which such rogue waves can be maintained over longer distances can
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be a change from a dispersive environment such as deep water to a non-dispersive environment. The bathymetry near the
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wave buoy (Figure~\ref{fig:bathy}) shows that this might be what we observe here, as the buoy is located near a step in
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the bathymetry, from around \SI{40}{\m} to \SI{20}{\m} depth.
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\subsection{Reflection analysis}
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\subsection{Reflection analysis}
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@ -207,10 +222,11 @@ The 13\% difference between those values highlights the existence of a notable a
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Nonetheless, the gap between the values is still fairly small and the extreme wave identified on February 28, 2017 at
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Nonetheless, the gap between the values is still fairly small and the extreme wave identified on February 28, 2017 at
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17:23:08 could still be considered as an incident wave.
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17:23:08 could still be considered as an incident wave.
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Unfortunately, the spectrum wave generation method used by SWASH could not reproduce simlar waves to the one observed at
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Unfortunately, the spectrum wave generation method used by SWASH could not reproduce simlar waves to the one observed
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the buoy. As mentionned by \textcite{dysthe2008}, such rogue waves cannot be deterministicly from the wave spectrum. For
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at the buoy. As mentionned by \textcite{dysthe2008}, such rogue waves cannot be deterministicly from the wave spectrum.
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this reason, this study only allows us to observe the influence of reflection on short waves, while mostly ignoring
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For this reason, this study only allows us to observe the influence of reflection on short waves, while mostly ignoring
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infragravity waves.
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infragravity waves. Those results are only useful if we consider that infragravity waves behave similarly to shorter
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waves regarding reflection.
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\subsection{Wave transformation}
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\subsection{Wave transformation}
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@ -236,11 +252,16 @@ Those results tend to confirm recent research by \textcite{lodhi2020}, where it
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threshold tend to overestimate the minimal flow velocity needed for block movement, although further validation of the
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threshold tend to overestimate the minimal flow velocity needed for block movement, although further validation of the
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model that is used would be needed to confirm those findings.
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model that is used would be needed to confirm those findings.
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Additionally, the flow velocity that is reached during the identified wave is not the highest that is reached in the
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Additionally, similar flow velocities are reached in the model. Other shorter waves yield similar flow velocities on
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model. Other shorter waves yield similar flow velocities on the breakwater, but in a smaller timeframe. The importance
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the breakwater, but in a smaller timeframe. The importance of time dependency in studying block displacement would be
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of time dependency in studying block displacement would be in accordance with research from \textcite{weiss2015}, who
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in accordance with research from \textcite{weiss2015}, who suggested that the use of time-dependent equations for block
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suggested that the use of time-dependent equations for block displacement would lead to a better understanding of the
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displacement would lead to a better understanding of the phenomenon.
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phenomenon.
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Although those results are a major step in a better understanding of block displacement in coastal regions, further
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work is needed to understand in more depth the formation and propagation of infragravity waves in the near-shore
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region. Furthermore, this study was limited to a single block displacement event, and further work should be done to
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obtain more measurements and observations of such events, although their rarity and unpredictability makes this task
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difficult.
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\section{Methods}
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\section{Methods}
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@ -261,14 +282,23 @@ over \SI{0.2}{\Hz}.
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All wavelet analysis in this study is conducted using a continuous wavelet transform over a Morlet window. The wavelet
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All wavelet analysis in this study is conducted using a continuous wavelet transform over a Morlet window. The wavelet
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power spectrum is normalized by the variance of the timeseries, following the method proposed by
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power spectrum is normalized by the variance of the timeseries, following the method proposed by
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\textcite{torrence1998}.
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\textcite{torrence1998}. This analysis extracts a time-dependent power spectrum and allows to identify the composition
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of waves in a time-series.
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\subsection{SWASH models}
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\subsection{SWASH models}
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\subsubsection{Domain}
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\subsubsection{Domain}
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\begin{figure}
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\centering
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\includegraphics{fig/bathy2d.pdf}
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\caption{Bathymetry in front of the Artha breakwater. The extremities of the line are the buoy and the
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breakwater.}\label{fig:bathy}
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\end{figure}
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A \SI{1750}{\m} long domain is constructed in order to study wave reflection and wave transformation over the bottom
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A \SI{1750}{\m} long domain is constructed in order to study wave reflection and wave transformation over the bottom
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from the wave buoy to the breakwater. Bathymetry with a resolution of around \SI{1}{\m} was used for most of the domain.
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from the wave buoy to the breakwater. Bathymetry with a resolution of around \SI{1}{\m} was used for most of the domain
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(Figure~\ref{fig:bathy}).
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The breakwater model used in the study is taken from \textcite{poncet2021}. A smoothed section is created and considered
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The breakwater model used in the study is taken from \textcite{poncet2021}. A smoothed section is created and considered
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as a porous media in the model.
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as a porous media in the model.
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@ -322,12 +352,12 @@ the SWASH model, the porous armour was considered at a macroscopic scale.
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A volume-of-fluid (VOF) model in two-vertical dimensions based on volume-averaged Reynolds-averaged Navier-Stokes
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A volume-of-fluid (VOF) model in two-vertical dimensions based on volume-averaged Reynolds-averaged Navier-Stokes
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(VARANS) equations is used (olaFlow, \cite{higuera2015}). The model was initially setup using generic values for porous
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(VARANS) equations is used (olaFlow, \cite{higuera2015}). The model was initially setup using generic values for porous
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breakwater studies. A sensibility study conducted on the porosity parameters found a minor influence of these values on
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breakwater studies. A sensibility study conducted on the porosity parameters found the influence of these values on
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the final results.
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the final results to be very minor.
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The k-ω SST turbulence model was used, as it produced much more realistic results than the default k-ε model, especially
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The k-ω SST turbulence model was used, as it produced much more realistic results than the default k-ε model,
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compared to the photographs from the storm of February 28, 2017. The k-ε model yielded very high viscosity and thus
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especially compared to the photographs from the storm of February 28, 2017. The k-ε model yielded very high viscosity
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strong dissipation in the entire domain, preventing an accurate wave breaking representation.
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and thus strong dissipation in the entire domain, preventing an accurate wave breaking representation.
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\subsubsection{Boundary conditions}
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\subsubsection{Boundary conditions}
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Loading…
Reference in a new issue