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Jesper Nielsen

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About Jesper Nielsen

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    Fire Warden
  • Birthday 09/15/1987

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    racquet sports, bike riding, good food, nature in general, relaxing in the shade on a hot day, looking out the window when I should be working...

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  1. To reply to my own post in record time. Replace the .so and .so.1 files from the 2020 install with those which worked with a previous install. The .so file in the dropbox is only 1KB
  2. Installed and ready to roll but... From where can I access the compatible tuflowfv_external_turb.dll , libtuflowfv_external_turb.so & libtuflowfv_external_turb.so.1 The versions accessed through the wiki don't seem to work. Thanks
  3. Hi Camille Please find attached. Sorry for the delay - I have only just recently updated my email. Cheerio mybathy.m
  4. Hi there I would like to install the latest release (I hear its pretty good). Further to the above instructions, I would like to have the latest installation identifiable in shell scripts with a name other than tuflowfv, using instead say tuflowfv_2019_01_008. What is the recommended approach? Thanks
  5. Faaaaaaaaaaaaaaaaaaaaaaaaaaaaaar out! Should have looked at this hours ago
  6. It is quite easy to generate a fancy looking 3D image of your model bathymetry like the one in the attached image using the mybathy.m function and Matlab's various different lighting options. By using the "bounds" input you can trim down the model thus making it more manageable when zooming, rotating and panning in 3D. Example: % create the fvcontrol object (if you are not going to add any other fvg objects then you could just create a figure) fvcObj = fvgraphics; % create the axes into which to plot your bathymetry. ax = axes; % use the DataAspectRatio property to scale the elevations with respect to the x-y plane. set(ax,'DataAspectRatio',[1 1 0.1]) % set(ax,'DataAspectRatio',[1 1 10000]) % Something more like this will be required when your model is in spherical coordinates % plot the bathymetry within the rectangle defined by 4 points h = mybathy(ax,'mymodel.nc','bounds',[x1 y1; x2 y2; x3 y3; x4 y4]); % manually adjust the view angle using the pan, zoom and rotate 3D icons in the figure tool bar % apply some lighting (see matlab help doc) lighting phong camlight right
  7. When I look at the waves within a simulation I like to view the wave heights overlain with wave vectors. The magnitude of the vectors is the WVHT output and the direction the WVDIR output (cartesian convention). A neat way to do this is to use the "Expression" property of a fvg_sheetvec object. Example: % create the control object fvcObj = fvgraphics; % visualise the wave heights sheetObj = fvg_sheet(fvcObj,'mymodel.nc','Variables','WVHT'); % create the expression which defines the x-component and then the y-component of your vectors. The x-component must come first expression{1} = 'WVHT.*cosd(WVDIR)'; expression{2} = 'WVHT.*sind(WVDIR)'; % create the vector object vecObj = fvg_sheetvec(fvcObj,'mymodel.nc','Expression',expression)
  8. Hi there. Modelling small rivers and creeks in TUFLOW-FV can be a challenging undertaking for several reasons. Representing the bathymetry and flow fields of the channel with cells sufficiently large enough to allow for a sensible timestep and thus acceptable run-times is certainly one of the biggest challenges. I will touch on this here... Say you have a natural channel approximately 60m wide and with a maximum depth of 5m - a moderately sized creek or small river connected to the ocean with upstream freshwater inflows. You have used rectangular cells which are typically 15m wide and 30m long. You have inspected your cell center elevations off a detailed and highly reliable DEM or other bathymetric data set. You think that this model will represent reality. You run your model in 3D and compare to some salinity measurements. You discover that your model has far less stratification than the data. What is going on? Each element has a discrete elevation. Lets consider, for example, the chain of elements defining one of the banks of your channel connecting the downstream boundary to the upstream boundary. The chain of cells consists of cells which have elevations inspected from the bathymetry data at 30m intervals. Thus the model represents the relatively smoothly undulating bathymetry with a series of discrete steps. Abrupt changes in cell elevations force abrupt changes in velocity. Where the velocities are abruptly increased the turbulent mixing is consequently abruptly increased. This phenomenon is probably contributing to the lack of stratification in your model. How to fix it? The matlab utility "fv_cellcentres_channel_smooth.m" It is an almost fully automated way to smooth the bathymetry along the channel - it has worked a treat for me. I have not uploaded it yet but if you would like to give it a whirl just send through a msg and I'll send it through. Plenty more to follow on this topic...
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