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Prescribed thermo for AIDA calibrations #487

Merged
merged 1 commit into from
Dec 4, 2024
Merged

Prescribed thermo for AIDA calibrations #487

merged 1 commit into from
Dec 4, 2024

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amylu00
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@amylu00 amylu00 commented Nov 22, 2024

Changing AIDA calibrations for HOM so that we are prescribing cooling rate and pressure.

@amylu00 amylu00 self-assigned this Nov 22, 2024
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amylu00 commented Nov 22, 2024

Cooling rate is not completely linear. Seems like latent heat and/or heating from chamber walls has a pretty significant effect later in the experiment. Should I make cooling rate nonlinear in the model to match or is that unnecessary?

Screenshot 2024-11-21 at 5 04 06 PM

@amylu00 amylu00 requested a review from trontrytel November 22, 2024 01:05
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Cooling rate is not completely linear. Seems like latent heat and/or heating from chamber walls has a pretty significant effect later in the experiment. Should I make cooling rate nonlinear in the model to match or is that unnecessary?

I would vote for not fitting any lines then and just driving it with what is in the measurements. We can interpolate between the two points in time from the measurements to get the rate at each time step

@amylu00 amylu00 force-pushed the al/box_AIDA_calib branch 2 times, most recently from 0ab1f1b to 934d4b9 Compare November 22, 2024 23:07
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codecov bot commented Nov 22, 2024

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 95.82%. Comparing base (fc936d7) to head (3cb3864).
Report is 3 commits behind head on main.

Additional details and impacted files
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  Coverage   95.82%   95.82%           
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  Files          41       41           
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Components Coverage Δ
src 97.48% <ø> (ø)
ext 69.79% <ø> (ø)

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I'm not sure about the AIDA_rate function. Maybe something like this would be nicer?

import Interpolations as Intp
# example values

FT = Float32
t_in  = FT[0.130,  0.464,  0.573,  1.100,  1.653,  2.216,  2.760]
p_in = FT[991.3,  954.2,  942.0, 886.9,  831.5,  778.9, 729.8]

p_of_t = Intp.linear_interpolation(t_in, p_in)

p = p_of_t(0.5)

Then you could compute the gradient for any t and dt combination?

@amylu00 amylu00 force-pushed the al/box_AIDA_calib branch 3 times, most recently from 5666393 to 61b34e7 Compare November 27, 2024 19:30
@amylu00 amylu00 requested a review from trontrytel November 27, 2024 19:31
@amylu00 amylu00 force-pushed the al/box_AIDA_calib branch 3 times, most recently from 1e0bb97 to 6988f3b Compare December 2, 2024 23:38
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Thank you!

@amylu00 amylu00 merged commit ee7d3ac into main Dec 4, 2024
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@amylu00 amylu00 deleted the al/box_AIDA_calib branch December 4, 2024 18:37
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