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design of experiments/parametric variation ('shape study') #3

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ryancoe opened this issue May 16, 2019 · 7 comments · May be fixed by #193
Open

design of experiments/parametric variation ('shape study') #3

ryancoe opened this issue May 16, 2019 · 7 comments · May be fixed by #193
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@ryancoe
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ryancoe commented May 16, 2019

Using the nominal design variables (r_1 = 20 m, r_2 = 30 m, d_1 = ?, d_2 = 42 m) and ranges given in SNL-WaterPower/WecOptTool#1, conduct a design of experiments study to better understand the sensitivity of the system to the different design variables.

@zmorrell-sand
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It looks like DAKOTA will do a very good job at performing this task, along with what is mentioned in issue SNL-WaterPower/WecOptTool_old#14 . I will try to get interfaces set up for both issues by the end of the week. I am thinking that a Box-Wilson Central Composite Design would be a good approach for both, as it is supported natively by DAKOTA, and it has the nice property of placing test points equidistant around the starting point.

@zmorrell-sand
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@ryancoe
I am having some issues with the RM3_debug.m file.

The first issue, which I found a workaround to using scp, is that Git LFS isn't installed on the Linux machines. This made it rather difficult to get the RM3_BEM.mat file to download properly. The cloned file only included the SHA256 signature, but not the actual file. I'm still not entirely sure what the issue was, but I got around it by downloading it onto the windows machine then using scp to copy the file to the correct location on the Linux machine,

The second, and currently more pressing issue that I have come across is that on line 11 of the RM3_debug.m file, you call a function called bretschneider, which is not in the WecOptTool source code as near as I can tell. I did a little bit of digging online, and I think that you are calling it from a tool called Wafo. Is Wafo a dependency for this tool, or is there somewhere else that I need to be looking for the file to add it to the path?

Thank You,
Zachary Morrell

@ryancoe
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ryancoe commented May 29, 2019 via email

@ryancoe
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ryancoe commented Jun 5, 2019

@zmorrell-sand - Just wanted to note our conversation here:

  1. Add the following responses:
    • power
    • volume
    • surface area
    • power/volume
    • power/(volume)^1/3
    • power/(volume)^2/3
    • power/(surface area)
    • power/(surface area)^1/2
  2. Rerun the study on an HPC
  3. Present the results with the plots you've created and those shown below

Screen Shot 2019-06-05 at 1 33 22 PM

Screen Shot 2019-06-05 at 1 33 15 PM

@ryancoe
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ryancoe commented Mar 12, 2020

Let's pick this back up again with the goal of demonstrating the usage of a parametric variation study to understand the objective function sensitivity to various design variables (e.g., by creating an example script).

@ryancoe ryancoe added the examples Tutorials and examples label Mar 12, 2020
@H0R5E H0R5E added this to the 0.2 milestone Apr 17, 2020
@H0R5E H0R5E modified the milestones: 0.2, 0.3 Jul 9, 2020
@H0R5E H0R5E modified the milestones: 1.x, 1.0 Jul 9, 2020
@ryancoe
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ryancoe commented Jul 16, 2020

@ssolson - Per our discussion, let's do a study on the WaveBot. For example, you could vary all of the geometric variables along with F_max and z_max. The responses of interest could be

  • power
  • volume
  • stroke (z_max)
  • F_max
  • area
  • natural period
  • bandwidth

Here's a MATLAB toolbox that I found a year ago that I thought might be interesting to look into. You can also just use lhsdesign and plot this stuff yourself.

Pianosi, Francesca, Fanny Sarrazin, and Thorsten Wagener. "A Matlab toolbox for global sensitivity analysis." Environmental Modelling & Software 70 (2015): 80-85. https://www.sciencedirect.com/science/article/pii/S1364815215001188

You can see where I did a version of this for the WaveBot_caseC https://github.com/SNL-WaterPower/WecOptTool/blob/7b441386db87e56b81b77978d4649c887b3451c1/waveBot_caseC.m#L110

@ssolson ssolson self-assigned this Jul 30, 2020
@H0R5E H0R5E modified the milestones: 1.0, 1.x Sep 15, 2020
@ryancoe ryancoe changed the title design of experiments/parametric variation design of experiments/parametric variation ('shape study') Oct 1, 2020
@H0R5E H0R5E modified the milestones: 1.x, 1.1 Oct 2, 2020
@ryancoe ryancoe mentioned this issue Oct 15, 2020
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@ryancoe
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ryancoe commented Oct 15, 2020

@ssolson - I was reading the paper below last night and it has a lot of good/relevant points that can be referenced and/or evaluated by this study.

Falnes Johannes and Hals Jørgen 2012Heaving buoys, point absorbers and arraysPhil. Trans. R. Soc. A.370246–277
http://doi.org/10.1098/rsta.2011.0249

@ssolson ssolson linked a pull request Oct 20, 2020 that will close this issue
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