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OpenFoam resulting .csv file details #14
The explanation is fairly complex and I had wanted to update all of the GH files that we are using so that you could get a clear sense of the workflow that @TheodoreGalanos and I are using (the files before were a bit hacky and incomplete such that they would have created more confusion than clarity).
To answer your first question, Wind Factors (as Theodore has defined it to me) are the relationship between the wind speeds at the points in the CFD simulation and the recorded meteorological wind speed at 10 meters above the ground. In other words, multiplying the wind factor for a given point by the meteorological wind speed at a given hour gives you the CFD wind speed for the point. Working with wind factors is particularly useful for helping extrapolate the results of CFD simulations to an entire year since, any hour when you have the wind blowing in the direction of the CFD simulation you can multiply the wind factors by the EPW wind speed for the hour and get an estimate of wind speeds on the ground. Of course, this method relies on the assumption that winds blowing in a similar direction at different speeds will still exhibit a similar pattern of wind speed distribution (and only the intensity of the wind speed in this pattern changes). Since this assumption can potentially introduce a lot of error, Theodore tried to mitigate this by running CFD simulations using the average wind speeds for each cardinal direction in the EPW file. The hope is that, even if there is some error for a given hour of the year that does not have a similar wind speed to the CFD simulation, over the whole year, the results should be in the correct range.
The quick answer to the second question is that the direction of the wind in the file that I posted is 10 degrees from North (hence WindFactor(10)) but the more meaningful answer is more complex. Theodore spent a solid 3 months running 36 CFD simulations for all wind directions (at 10-degree increments), which took a huge amount of time and computer power. In order to use these results to evaluate outdoor thermal comfort, we are using the wind factor method I described above and we are using one of the 36 CFD simulations to approximate wind speeds across an urban space for each hour of the EPW. 36 wind directions would be too large of an example for me to share here so I am including an example that uses just 6 of Theodore's CFD simulations below (at the following degrees from North: 0, 60, 120, 180, 240, 300)
The whole workflow has been split up into 3 separate GH files for ease of use/explanation:
You will also see in that last step that we are using your PET functions for the mircrolimate maps. They are really the only comfort model that can describe this situation so, again, I thank you greatly for adding them!
Let me know if you have any other questions/suggestions on the workflow.
referenced this issue
Jun 10, 2016
I am terribly sorry for coming back this late. Need to find a better way to stay up to date with github since checking in often doesn't seem to work.
Chris pretty much covered everything perfectly in his answer so I'm not so sure what I can add, apart from the apology.
The case study we have been using is a quite complicated one, as Chris mentioned, with the wind comfort study being done every 10 dg intervals. So, as Chris said, the wind factor(10) would be the wind factor for the 10 dg direction, which in reality ranges from 5 to 15 degrees on the compass.
Wind factors are a good way of going from instantaneous speeds (which is what an outdoor wind CFD assessment provides) to yearly values and that's why we use it. Chris built a few awesome components that do this work fast and efficient and actually make this practical.
Unfortunately, the CFD study is not as optimized as I'd like. For example, the geometry is rotated for every simulation, in order to keep the Inlet/Outlet on the y vertical direction. That means, and you can probably see that in the MapCFD2MicroclimateMapPts file, that we need to rotate the points each time to fit them to the stationary Geometry in Rhino. In future descriptions of this process, this will be optimized, probably by creating a circular mesh which allows to specify the inlet/outlet by radians on the vertical boundary of the mesh.
Also, hopefully, such issues can be rectified in the future if the whole pre and post-process is done through GH and Butterfly. Maybe the program is smart enough to rotate automatically and save instances of the geometry to which it maps the points later for example. I'm not really sure about this.
As for PET, I'd also like to thank you for your contribution. I haven't actually had the chance to test it, will give it a try as soon as I can. But it does allow us to implement a thermal comfort model that is sensitive to specific heights of wind velocities. For example in the same study, the areas of the roof of the left building and the garden area in the middle level of the right building were also assessed. PET will make, I would guess, this assessment much more accurate.
Wow, I said a lot considering I didn't have much to contribute. I'll call it a day then :)
referenced this issue
Jun 10, 2016
Chris and Theodore thank you for the informative replies. They helped me understand better what the current Butterfly components do.
I did a few cfd simulations for urban environments myself, with support from Liam Harrington, and I would like to share some of the thoughts based on upper replies:
Again thank you for the detailed answers, and again please accept my apologies for such a late reply.
I also apologize for a late reply.
Thanks, as always, for all of the insight and knowledge. The height above the ground values make a lot of sense to me. Particularly if we are using a log wind profile, 1.1m is just about the closest distance that we can get to the ground before the meteorological wind speed drops to 0 (since the roughness length of urban areas is 1 m).
I was wondering if there is a source for the 8-16 standard number of cardinal directions. This minimum number is something that @TheodoreGalanos and I have been trying to understand and any previous literature would be very helpful. My guess is that this minimum number of simulations might be different depending on whether we are trying to assess safety, mechanical comfort, or thermal comfort since some of these metrics seem to require a finer level of resolution than others.
Hi @chriswmackey ,
I am not aware of the exact literature which mentions 8 being the bare minimum.
There are a number of papers which mention the usage of 16 wind directions regardless of the purpose of the cfd simulation (air pollution, pedestrian wind speeds, wind turbines, air ventilation). These are just a couple of those I found with quick google:
"The Guidelines recommend the use of a numerical model for each of the 16 wind directions to evaluate the design wind speed for wind turbines."
"For pedestrian-level wind studies, simulations need to be performed for many (e.g. 12 or 16) wind directions"
"The solution proposed (Santiago et al., 2013) is to run only a set of scenarios (corresponding to 16 wind directions) using steady CFD-RANS simulations."
Thanks for the info, @stgeorges !
I can not comment on 16 to 36 difference.
My upper replies where related with the cfd simulation minimal number of wind directions.