Welcome. Today is Wednesday, February 21st, 2018 and this is the NHERI Early Career Researcher Forum. This forum is intended

to foster the exchange of ideas and be a platform of best practices for

successful research. It is intended to highlight compelling research, build up

the natural hazards engineering student community, and provide presentation

opportunities. For more information, visit the NHERI website at Designsafe-ci.org

where you can find links to the SimCenter and the NHERI Learning Center.

Today’s webinar is coordinated by the Natural Hazards Engineering Research

Infrastructures Computational Modeling and Simulation Center. This webinar is

supported by the National Science Foundation under

Awards 1612843 and 152817. Any statements in this webinar are those of the presenter and do not necessarily

represent the views of the National Science Foundation. Today’s presentation

is by Nikos Kalligeris. He is a postdoctoral scholar in Civil

Engineering at UCLA. His primary research interests lie in near shore

hydrodynamics during extreme events such as tsunamis and hurricanes. His analysis

combines numerical modeling laboratory experiments and field observations. Dr.

Kalligeris has been a member of several reconnaissance field surveys for

tsunamis around the world and the title of his presentation is “Tsunami-Induced

Turbulent Coherent Structures: Large-scale Experimental Observations

and Interpretations.” And Nikos I invite you to begin. Thank you.

Thank you for the introduction, Matt, and also thank you for giving the

opportunity to present my research on this forum. So,

my talk today as you mentioned is on tsunami-induced turbulent coherent structures

and turbulent coherent structures is the scientific term for eddies that have

been observed to form in the near shore during tsunamis. My talk today — during my PhD

when I was at the University of Southern California, I

participated in an NSF funded project where we studied the generation and

evolution of tsunami-induced turbulent coherent structures, and in today’s presentation, we will

talk about the findings from these laboratory experiments and also about the value for

harbor applications in tsunami prone areas. So, this here is a quick breakdown

of my presentation today. I will first give a brief introduction on tsunamis

and more specifically on tsunami-induced currents and then I will briefly talk

about what we know about tsunami-induced coherent structures both from

observations with field surveys and also from the literature and then in

the main part of my presentation, I will talk about the lab experiments that we

conducted, how we collected the experimental data and also the

interpretation of our findings. And at the end, I will talk about the

value of the experimental results, and how to extend this work that we did in

the future. So, real quick, tsunamis are geophysical scale waves that are predominantly generated by submarine earthquakes. If the earthquake is big

enough, the co-seismic seafloor deformation will set off waves and

these waves can reach wave lengths from tens to hundreds of kilometers. And due

to their very long wave lengths, they can travel vast distances even across oceans.

In the deep water, they have a very small amplitude but as they approached the shore, they grow in amplitude and they have the

potential to flood vast areas. Past research has primarily focused on

flooding for the obvious reason of saving lives and property in coastal

areas. And there has been analytical and numerical models have

been have been developed to predict the coastal flooding. The numerical models

typically employ the nonlinear shallow water equations which capture the

flow at a relatively low computational cost. Given accurate

initial conditions, it has been shown time and time again that these standard

models used for tsunami modeling can accurately reproduce

propagation across an ocean and as seen on the last notes but also predict

coastal flooding in coastal areas. Like an example is shown on the right.

So, tsunami research has advanced to the point that we are now able to do

accurate forecasts and for tsunami-induced flooding even in real time. But when it

comes to tsunami-induced, while tsunamis induce flooding is very well understood,

when it comes to tsunami-induced currents, things start to become a little

bit trickier. These two figures here show on the left the maximum tsunami

amplitude in Crescent City, California during the 2011 Japan tsunami. And on the

right you can see the corresponding maximum current speeds at the

same harbor and same tsunami event. It is immediately apparent from these two

plots, that maximum currents are much more localized as compared to tsunami amplitudes.

High currents can be seen around the port structures

and where they reach up to 12 knots. But in the rest of the domain, they are

relatively, the current speed is relatively low. In this animation here,

which is also for Crescent City, for the same tsunami event, will show you what is

happening during the tsunami. As you can see, while the tsunami currents approach the

near shore, they sort of bend around the coastal structures and they accelerate.

It is this interaction of the currents with the shoreline that creates the

highly localized current field that we saw in the previous transparency. Flow

separation and strong horizontal shearing near the port structures also

introduces vorticity and this vorticity in turn generates eddies. So, if the

conditions are favorable, or unfavorable if you may, these eddies may grow in very

large size and it can even occupy the whole harbor or port base. One such eddy

was spotted in Port Oarai during the 2011 Japan tsunami.

Port Oarai is located south of the Fukushima power plant and where the

nuclear disaster happened right after the 2011 earthquake. In this footage, which was

taken from a helicopter, a gigantic eddy with a diameter much much larger than

the local water depth can be seen spinning inside the harbor for tens

of minutes until it was washed away by the next incoming wave. These large

eddies come with high rotational flow speeds that can exert forces in port

structures but also move a lot of sediment around in the port. They are also

notorious for dragging ships inside these eddies and they can be

carried along with them. One of the best-known examples of a ship caught

inside a tsunami-induced eddy took place in Port Salalah, Oman during the 2004

Indonesian tsunami. Scientists went to Oman and specifically in Port Salalah

to take quantitative measurements nine months approximately after the tsunami.

It is a standard practice to interview eyewitnesses in those reconnaissance

missions and ask information about the tsunami. So, in this case in Port Salalah

the harbor master described how an hour and a half after the arrival of the tsunami and

this 285 meter container ship by the name Maersk Mandraki was caught

inside a tsunami-induced eddy and broke its moorings. It started spinning out of

control and any attempts to free the ship from the eddies via tugboats

was were left in vain. So, the ship was dragged off shore. It almost hit the

break water and eventually was beached in a nearby sandbar. This

sketch here was approximately drawn by the harbormaster who described the

event. Luckily, the ship didn’t collide with any other ship, but you can imagine

many worse scenarios of having a ship inside a port out of control. At

the time, this was a mysterious phenomenon when this was recorded and my

advisor, Costas Synolakis, attributed this to harbor resonance, but now we know that

this was not harbor resonance, but it was one of those turbulent incoherent structures

that form during a tsunami and where the flow separates around a sharp corner

like this one here, seen here. So, apart from observational reports

there is not much that we know about tsunami-induced eddies because fundamental research into

the generation evolution of those tsunami-induced eddies is practically

non-existent. For research into eddies in the context of natural processes

like the ones discussed here, we have to go to literature in the hydraulics

community and specifically studies in shallow flows. So, shallow or 2d flows exhibit weak vertical variability,

similar to what we coastal engineers call shallow water waves where the

length of the wave is much longer than the local water depth. So, one of these

eddies that we study grow in lengths that are much larger than the local

water depth. They are called Turbulent Coherent Structures. The exact

definition of which is given here. From this point on, and excuse me for the

confusion, I will use the term Turbulent Coherent Structure eddy and vortex

interchangeably, but they all mean, all these terms, mean the same thing. So, from

what we know in the literature, the predominant generation mechanism for

these turbulent coherent structures is topographic forcing, as seen in the

figure here. Topographic forcing exerts transverse shear and which

eventually leads to flow separation on the lee side and the generation of an

eddy. Tsunami-induced turbulent coherent structures are not the only types of

geophysical-scale turbulent coherent

structures that we know. One example of another known case is

shown here and it has a name of tidal flushing. So, when the tidal-induced

currents in a tidal inlet are very strong, during ebb tide, the currents at

the tip at the inlet mouth may separate and form this sort of

dipole that can self propel itself to the offshore.There has been significant

research where they’ve studied under what conditions these dipoles form

and under what conditions they separate from the inlet month and migrate

offshore. These sort of dipoles can have important implications for

nutrient exchange between the estuary and the offshore. Other types of geophysical-scale turbulent coherent structures that we know are shown here. On the left, you can see a

mesoscale eddy forming east of Tasmania. And these mesoscale turbulent coherent structures

are very important because they exhibit different properties than the

surrounding ocean and because they can carry heat and carbon and also

oxygen and salt and they can travel very vast distances, and so it has been

studied thoroughly and other geophysical-scale turbulent coherent structures that

we know also exists in the atmosphere, not only in the oceans. For example, hurricanes are a type of turbulent coherent structure structure that exhibits similar

properties like the one shown here. The atmosphere is, like the ocean, is

limited in terms of depth. So, this type of vortex can also be considered as

shallow. Even though these turbulent coherent structures are in a different scale,

and because they’re in a different scale, Coriolis force starts to become

important. There’s still a lot of information that we can extract from the

research that has done on these vortices. So, since

fundamental research is absent for tsunami-induced turbulent coherent structures,

we set up a simplified experiment at Oregon State University’s tsunami basin. When we

recreated the generation of a turbulent coherent structure using appropriate scaling,

as seen in the videos here, we collected all the data necessary to study both the

generation and evolution of those turbulent coherent structures in a well

controlled environment. The results and the analysis can be meaningfully

translated to the prototype scale for harbor applications. So, Oregon State

University’s wave basin is one of the largest in the world and it has a 44 —

it’s 44 meters long and it’s 26 and a half meters wide.

It has a piston type wave maker on the left side and vertical walls on the

other three sides. We built an impermeable breakwater along the width

of the basin leaving a three meter gap between the breakwater tip and the side

wall. And in this way, we created a simplified image of a port. I have

put a label of the offshore basin on the left side, since this is the side of the

wave maker. But based on this geometry, the port side can be either of them,

either left or right. The boundary conditions that created a stable

turbulent coherent structure is shown in the next figure. It consists of a slow push

forward of the main wave maker and a and a sudden retreat which created an

asymmetric N-wave. In terms of the chosen water depth, it translates to

an experimental scale of approximately 1/27 and the experimental

wave period and wave amplitudes both translate to very realistic protoype

scales and this is one of the rare cases where both the time and the length

vectors are left relatively undistorted in this experiment. In terms

of the dimensionless, the important dimensionless numbers, it can be

concluded that the laboratory results are scale independent for small scale

geophysical flows like the ones that we are interested in. The experiment can be

broken down into three phases. In the first phase, the wave maker pushes

forward, and it also pushes the water from the left basin towards the right

basin, creating a left-to-right current in the harbor channel, and this

creates a turbulent coherent structure on the right side of the breakwater tip. As the

wave maker suddenly retreats it creates, it changes the direction

inside the harbor channel and now it’s from right to left and

this current is further reinforced by the reflection of the leading elevation

wave off the right wall. So, this in the beginning generates a starting jet that

forms into a vortex and this vortex eventually detaches from the starting

jet and starts evolving as a free vortex in the offshore basin. And this

constitutes the third and final phase of the experiment. Four overhead cameras

were used to visually capture the water surface and surface tracers were

introduced in the flow to extract a surface velocities through a technique

called a particle tracking velocimetry or PTV, in short. It is a non-invasive

technique to extract surface velocities over big areas. We repeated the same experiment many many times to examine both the

repeatability of the experiment but also to collectively obtain a satisfactory

density of data. This rectified video shows one of the PTV experiments as

recorded by the four overhead cameras. I had to speed up the video for this

presentation. So, you can see how the water pushes the water to the right side

creating initial TCS and then as the flow reverses the starting jet

evolves into a vortex that starts evolving freely after it’s detached from

the trailing jet in the offshore basin and you can see that the tracers

accumulate at the vortex center in what is known as a flow convergent

zone near the center. And we have to keep supplying the flow with with tracers to

extract velocities from this area. The the vortex eventually occupied the

whole offshore basin and circulation was still visible inside the wave basin

even one hour after the experiments. So, in order to — the methodology — to

extract surface velocities from this type of videos consists of four basic steps.

The first step is to detect the center of those tracers and the second step is

to track them in time. Then you have to convert the image coordinates to world

coordinates and then extract surface velocity vectors and physical units. This

animation here corresponds to the rectified video I showed you before. Each of these velocity vectors

corresponds to one of the tracers that was tracked in the flow. The velocity in

the basin reached one metre and a half meters per second which can be

translated to a prototype 15 knots which is very high speeds in these types of

flows that we are studying. The methodology and implementation of

particle tracking velocimetry was validated through measurements of ADV instruments

that were positioned into in the locations shown in the figure here. ADV

stands for acoustic doppler velocimetry and these are instruments

that measure the velocity in all three directions, x and y. And as you can see,

the black here, the black curves in those top plots, correspond to ADV

measurements and the red corresponds to the PTV extracted velocity. So, as you can

see from these plots that they compare well. The velocity extraction was done carefully. Now, we also used a stereo camera

configuration for the area around the the breakwater tip in order to extract

velocity vectors in more detail. What this stereo camera configuration allows is to

extract velocities and the location of the tracers in all three directions, in

what is known as stereo or 3D PTV. Stereo 3D PTV requires an additional step

compared to 2D PTV which is the stereoscopic particle matching between

the tracers and tracked with one camera to match them with the tracers

captured with the other camera. So, since we can extract surface

elevation through 3D PTV, I could compare my results using the wave gauges that

were laid out in the wave basin, the location of which is shown

with red crosses in this figure here. Black again is the measurements and

this time of the wave guages and the red is the 3D PTV extracted surface

elevation. As you can see, the implementation of a 3D PTV worked

really great in this example here. In terms of the tools I used for

the 2D and 3D PTV are shown here. For the camera

intrinsic parameterization which has to do with the distortion introduced by the

lens of the camera, I used the camera calibration toolbox

developed by Dr. Bouguet of Caltech and you can download this toolbox through

this link. In terms of the camera extrinsic parameters, which has to do

with image to world coordinates transformation, I used the Direct Linear Transformation

equations and I’m providing here a reference to

implement these equations. And last in terms of the particle

identification and particle tracking, I used the methodology of Crocker and

Grier, and more specifically, the implementation through the MATLAB

toolbox at the link provided here. For a 3D PTV, I had to develop my own

PTV toolbox which is based on the work by Capart et al. And the

difference here is that for my 3D PTV experiments, the inter-particle spacing

was smaller compared to the flow speed. So, this made it more complicated

for conventional PTV algorithms to follow the tracers. So, we needed an

extra matching criteria and the work by Capart et al uses the topology of

the neighboring tracers and through Voronoi five-stars which worked really

great in the application I wanted to use it for. In terms of the stereoscopic

particle matching, again, I developed my own toolbox which is based on the

work by Douxchamps and others, 2005. Even though I have developed my own toolbox, I

haven’t released those yet. I’m planning to do so in the near future in case

this can be useful for the research of others. Also, if anyone from the audience

wants to know more about this implementation, I can provide more

details at the end of my presentation. Now, after I went through the data, the methodology of collecting data, I

will now move into the analysis and I will start from the second phase of the

experiments where the offshore TCS is being generated. Now for this application, I overlaid all the scattered velocity

vectors from 2Dand 3D PTV, and I averaged them on a regular grid like seen

in this animation, and by obtaining the mean velocity field on a regular grid,

I was able to calculate the spatial derivatives and obtain important metrics

that describe the flow. One of those important metrics is swirl strength.

Swirl strength is a metric that describes the local rotation of the

fluid similar to vorticity. Maps of swirl strength shown here were used to track

the location and the spatial extent of starting-jet vortex and eventually

the turbulent coherent structure. The zero swirl strength contour as shown with the green

polygons, denoted the boundary of the starting-jet and eventually the vortex.

What I was interested in, in this stage, was to see how the starting-jet and

the vortex grow and how quickly it grows and how it scales. So, in other words, I had

to find a dimensionless number that will make the data to collapse

on a straight line. And if you find this dimensionless number, then you can

translate this to prototype scales, and I was inspired by experiments done in

vortex rings and I found this dimensionless number which gave me the

right scaling as shown here. The other thing that I was interested in,

in his experimental stage, was to see at what time the vortex separates

from the trailing jet that keeps supplying it with kinetic energy. So, this

time step corresponds to this time shown here where the

vortex has detached from the jet. This can also be shown through a

plot that shows the growth of circulation and circulation denoted

with capital gamma is a metric that gives you the strength of the vortex.

And you can see that it is at this time that the vortex separates which is also

shown by this rapid decay of circulation. Again, I had to find a

dimensionless number that will tell me what are the important parameters in the

flow with which the vortex detachment time scales with which can again be

translated to the prototype scale for harbor applications. I believe that the

most interesting physics happen after this vortex gets detached from the trailing

jet in what is the third experimental phase. For this experimental stage, the

first thing I had to do was find the path that the experimental

turbulent coherent structure followed in the offshore basin. To achieve that, I used two

different methods to track the center of the vortex. In the beginning,

where I had a nice distribution of tracers, I could compute vorticity

maps and through those vorticity maps I could define my vortex center as the

location of maximal vorticity. But at later stages of TCS development,

because of flow convergence and divergence near the vortex center, in

some instances I was left with very very little tracers to work with and compute

vorticity maps. So, in these cases, I used the tracer conglomerate the vortex center and I detected the

boundary of this tracer conglomerate through image processing and the

center of mud mass of these polygons defined my vortex center. So, after going

through this tedious work of extracting the path of the TCS center, you can get a

plot like this which shows the path of the experimental vortices for all the

22 experiments that we did. So, seeing this plot, I was, I could see that

repeatability is fairly good because the vortices followed

approximately the same path even though this is a highly turbulent

flow which means that there is a lot of there are many stochastic elements involved.

And the second observation that intrigued me by looking at this plot was

that the vortices in all the experiments started to converge towards the same

location and inside the offshore basin. So, this was an

observation that I had to explain and I will get back to as to why this happened

in a few slides. Extracting the the vortex center allowed me to convert

all the scattered velocity vectors from a Cartesian coordinate system to a

TCS centered coordinate system, and I could compute the velocity vectors

in the azimuthal, so along the arc of a circle, and the velocity azimuthal

direction, also the radial which is a way or towards the center of a circle.

And from the scattered velocity data, I could obtain the mean velocity profiles

which was a convenient representation of the flow field since my vortex was not

perfectly, the experimental vortex, was not perfectly axisymmetric. So, through

those mean velocity profiles, I could find out what rate the maximum

azimuthal velocity was decaying with time. So, by following the the peaks of each

mean velocity profile in time, you can draw a decay curve like the one shown on

the right. We know from the literature that

the predominant and the key mechanism in shallow turbulent coherent structures is

bottom friction and we were looking for a simple analytical formula that can

explain this decay and we can use this analytical formulation also

for harbor applications, and it would be great to have one to use. A simple

formula can be derived by equating the angular momentum with the

bottom friction with a bottom friction force and if you make the

simplification that you have a perfectly azimuthal flow, so no velocity in the

radial component, and also that the vortex doesn’t grow very quickly in time,

in terms of the spatial growth in the radial direction, then this force balance

comes down into a first order differential equation where you can

compute the decay of max azimuthal velocity with time. If you plug in the

only free parameter which is the bottom shear stress, you can get a green curve

which is the prediction of the analytical decay and it perfectly

matches the experimental decay which is great news because this is a very simple

formula that we can use for harbor applications to see how quickly those turbulent

coherent structures decay in time. As the turbulent coherent structure was slowing down, it was also growing in size by obtaining

more and more ambient fluid from its perimeter in what is called

viscous diffusion. The growth rate predicted by viscous diffusion is shown

here with the blue dashed line. The measured vortex radius is shown with the

black circles and as you can see up to this point it’s following the

theoretical prediction of viscous diffusion. But, as you move further in time, you can see

that the vortex area starts to fluctuate, and it stops following the

theoretical prediction. Again, this was an intriguing finding

that I’ve had to somehow explain. It occurred to me that it

might have something to do with the vertical, with the spatial confinement of

the vortex in the offshore basin. So, once you plot the minimum distance to the

vertical boundaries, you can notice that the vortex radius was confined, but

by those vertical boundaries which was the sidewalls of the basin and the

breakwater. In other words, the vortex, the experimental vortex, was constantly

trying to find more space to grow and the reason why all the TCS centers

ended up in the same location was because this location allowed it to grow

to its maximum size it could go for this

particular geometry that we tried in the wave basin. As a matter of fact,

this, the turbulent coherent structure, that was observed in Port Oarai

also ended up approximately in the center of the port basin. So, again

this is an important observation that we can predict where this, where these large

eddies will end up. And we can also use viscous diffusion as an approximate method to predict the spatial growth of

those turbulent coherent structures in the prototype scale. The last thing I wanted to do is to characterize the turbulent coherent structural flow field and so I went

through the literature to try to find a vortex profile that fits my observations.

It can be shown that, in theory, any monopolar polar vortex will converge to the

so-called stirring vortex. The stirring vortex has an idealized flow

profile as shown in this plot here and it has a free parameter alpha that

controls the steepness of the velocity profile. The higher the alpha is, the more

unstable the vortex becomes and by unstable I mean that the single vortex

can break down in a multi-polar vortex or break down into more individual

vortices. The name of stirring vortex is derived by the way it can be recreated

in a laboratory. In the lab, you spin, you submerge, a cylinder inside your

fluid, start spinning the fluid inside the cylinder and then lift the

cylinder, and let the rotating fluid interact with the ambient fluid

and your flow profile will start converging to this a-profile and certain

profiles have have been used and obviously in the literature describes

cyclonic vortices like the recent hurricane Harvey. So, with that in mind, I

started fitting my scattered experimental data to this theoretical stirring profile.

And you can see, that this free parameter alpha is approximately 0.35 based on the

experimental results. This is much lower than alpha equals 2 that has been found

to fit the atmospheric vortices and this vertical profile has been derived

for using the root mean square error as a goodness of fit parameter. I was able

to determine that the scattered velocity data started to converge towards

the a-profile at around 400 seconds which is very meaningful because

this shows you that there is some time after which we can use this theoretical profile

to describe a tsunami-induced turbulent coherent structure. The only question

that remains is what happens before this key time here. Why didn’t the scaled

velocity data follow this theoretical prediction at previous times? And the

clue lies, the clue to answer this question lies in the radial velocity

components. In shallow flows, the radial velocity and the vertical

velocity components are described as secondary flow components because

they are much weaker compared to the azimuthal. But as you can see from the

plots here in earlier times, the radial velocity component was significant and

at around 400 seconds, it started to become insignificant. So, in other words,

the deviation from the perfect azimuthal velocity profile was the reason why

the experimental vortex didn’t follow this theoretical stirring profile at

earlier times. By computing the ratio of the kinetic energy in the

radial direction over the kinetic energy in the azimuthal direction, I was further

able to demonstrate that at around 400 seconds was what is called the

transition to quasi 2-dimensional flow. This has important implications because

when it comes to mixing and sediment transport, but also when it comes to the

use of numerical models. Because the standard numerical models used for

tsunami modeling are depth-averaged which means that everything that happens in

the water column is averaged out, it means that in the beginning, while

the flow is highly three-dimensional, those models will not capture the

physics accurately, but there is a time after which they will start reproducing

the physics more more accurately. So, in summary, in the context of near shore

currents induced by tsunamis, we started, we created the

generation and evolution of a tsunami induced current in the laboratory. And we

we collected all the data necessary to study both its generation and evolution.

And the results that were yield have important implications for applications

for ports and harbors where the timescales of developments of TCS

development can be applied for. And the forces on port structures can be

computed as well as the sediment transport potential. The laboratory data can be further used to validate numerical models used

for tsunami forecasting. And if better numerical models are derived for

forecasting, means that decision-makers can make, can manage, ship evacuation

during a tsunami more efficiently. My last aspiration is that my research will

have an effect on future port and harbor design in tsunami-prone

areas. We are currently in the process of modeling the Oregon

experiments using a large eddy simulation model which is a fully 3D

model with very small, with very high resolution. We are testing different

turbulence schemes including the Standard Smagorinsky and Dynamic

Lagrangian, and the results will be validated through the

laboratory data. We have already made a lot of progress already and the results are promising. And once

we fully validate the methodology, we can examine the 3D flow structure of the

flow and the turbulent properties of the flow as well. Also in the future,

using this implementation, we can test different boundary conditions and

different geometries in the harbor. This is an ongoing collaboration between

the University of Southern California and the University of Delaware. So, while

this study has already yielded very interesting results, there are still

things that can be improved. For example, because I only collected surface

velocity information on the water surface, I couldn’t

examine the full 3D structure of the flow. Also, I wasn’t able to study the

turbulent properties of the flow through in-situ measurements. Hopefully, the large

eddy simulations will offer insights in these two areas.

But it would be very good if these can be studied also in the laboratory in

the future. Last, since I only studied one boundary condition one harbor configuration, I

wasn’t able to fully examine under which conditions wave induced TCSs form, and

examine also how the time causation to quasi two-dimensional scales with time.

The last thing I want to show is a video captured in the lab. We put some model

ships at the tip of the breakwater to simulate how ships can be entrained

in those turbulent coherent structures. Just like the unfortunate ship Maersk Mandraki was captured in an eddy in Portal Salalah in Oman. You can see how

this video demonstrates how difficult it would be to control the ship

under those circumstances. I would like to acknowledge all the

sources of funding and this project was funded by an NEES-NSF grant awarded to

my advisor Professor Lynett. And I was also supported by two fellowships at

USC. As I said, it was Professor Lynett’s project and I was very fortunate to be

involved in. And I would also like to thank my colleagues, Aycut Ayca and Adam

Ryan, for their help during the the experiments.

Thank you very much for your attention. Thank you Nikos very much for the

presentation. At this time, we’ll start the question and answer session.

Attendees are reminded that questions should be submitted through the chat

panel and directed to the moderator and Nikos, the first question starts out

with a comment which is: A great discussion, a very interesting topic. How

could the insights provided by the research be useful to emergency managers

to improve ship evacuation before tsunamis, and what would your

takeaway advice be to harbor masters and emergency planners in coastal areas? Okay.

So, the first question was how this can be used — this information – can be used for ship evacuation. So, what we what this fundamental research

does is to show the first order problem. So, we have a very

simplified geometry that doesn’t necessarily correspond to any harbor

geometry that you can find out in the field, in the prototype scale. But it

shows what the important physics are in the flow. So, once we figure this out then

we can improve the numerical models to capture the right physics. So, if we

improve the numerical models, then we can improve the forecast, right? And

by improving the forecast, then emergency managers can make

better decisions of which parts of the port have to be first evaluated.

But there’s an answer, there’s another takeaway message that whatever —

which is a very simple one — that wherever you have very sharp corners inside the

harbor, then you can expect these eddies to form, right.

This is very simple, and if the conditions are favorable then you can

use some of those simplified analytical equations that came out of my

research to predict how quickly those eddies will grow in size and what the

flow structure looks like in terms of the velocity profile, and so you can

derive some simple models to calculate both forces on structures, see what the sediment transport potential is, etc. Okay.

Oh thank you. Are there any field measurements of tsunami induced eddies

that would help corroborate this research? We don’t have quantitative

measurements per se of those eddies. There are some, there are very limited

data out there in the literature that measure tsunami-induced currents in harbors.

We published a paper in 2016 where we measured GRL where we measured

tsunami induced currents in a harbor in Southern California,

in Ventura during the 2015 Chilean tsunami but the measurements that we

took mostly corresponded to the starting jet and not in a fully developed eddy

like the one I studied in my experiment. Now, as part of my post doc

at UCLA, we are laying out a methodology to be ready to deploy instrumentation,

and in a future tsunami, where we can capture the flow field of a fully developed TCS.

We don’t know if we’re ever gonna be successful in

such an attempt, but we will try. Okay Another question is: can you remind me

how the radius of a vortex was estimated? Okay. So, the radius of the vortex — and I

have included this. It was extracted from vorticity maps. So, I was setting a

threshold to maximum vorticity. So, at each time I had a maximum vorticity that

correspond to the center of the vortex. If you can define your vortex

boundary, as for example, ten percent of the maximum vorticity at each time, and

this contour of ten percent of maximum vorticity defined the vortex boundary.

That is how I defined it in my study. Okay. And that’s how those black

points were extracted. I think we have time for one more question and it is: from your

experience working at OSU’s wave basin, what suggestions do you have for those

starting their PhDs who plan on conducting experimental research in

fluid mechanics. The most important aspect when it comes to experiments in

fluid mechanics is the experimental scaling. So, if you don’t get the

experimental scaling correctly, your results are meaningless. And they cannot

be meaningfully extrapolated in the full-scale. So, that’s the most

important message. Another couple of tips is that it was always

important to do some quality assessment of the data as you collect them.

For example, each day or each week, make sure that your data is good.

Not go back home without anything meaningful to work with. Also,

from my research, I found out that there’s always room to develop your

own ideas when it comes to data collection. It’s always good to read the

literature in what tools are already available out there, but don’t be

afraid to to develop your own that suit your application better. Okay,

Well in fact, we’re at the conclusion of today’s Early Career Researcher Forum.

On behalf of the attendees, thank you Nikos for taking the time to share your

research. To the attendees, thank you for your participation and questions. Please

check the SimCenter’s website at simenter.designsafe-ci.org and check

your inbox for emails from [email protected] that will have

registration links for additional upcoming webinars in the Early Career

Researcher Forum and the Natural Hazards Engineering 101 webinar series.

Thank you for attending today’s forum.