In [2]:
# Standard setup block for running Python code
from __future__ import division, print_function
import os
if os.path.split(os.getcwd())[-1] == "Lab notebooks":
os.chdir("../../")
print("Moved to experiment root directory")
from Modules.processing import *
from Modules.plotting import *
plt.style.use("Config/plotstyle.mplstyle")
%matplotlib inline
Got to the lab about 9 AM.
Homed turbine, tow, y-, and z-axes.
Tank depth is 2.44 m.
Mixed up seeding from surface with squeegee like yesterday.
9:23 AM -- Dummy tow at 1.0 m/s to mix tank.
9:26 AM -- Did another dummy tow. Vectrino SNR up around 12 dB.
9:32 AM -- Resuming Perf-0.6-b.
At run 15 Vectrino stopped recording at 2.5 seconds. Rerunning.
Had to restart PC before run 26. Locked up trying to process data on 4 cores while running the experiment.
11:17 AM -- Starting Perf-0.4-b
1:49 PM -- Filming run 25 with GoPro underwater.
2:16 PM -- Finished Perf-0.4-b. Going to fill out the higher TSR runs of Perf-1.0-b.
2:42 PM -- Starting Perf-1.2-b.
4:04 PM -- Backed up data.
5:17 PM -- Checking levelness error of YZ traverse:
5:49 PM -- Going to take Perf-0.8-b out to a TSR of 5.25 like Perf-0.8.
6:29 PM -- Pushing out max TSR for 1.2 m/s to 3.5.
6:55 PM -- Ending for today. Backing up data.
In [35]:
Section("Perf-1.2-b").process(nproc=1, nruns="new")
In [36]:
plot_perf_curves(preliminary=True, subplots=True)
In [6]:
# Calculating tare torque test matrix for experiment
def calc_rpm((tow_speed, tsr)):
omega = tsr*tow_speed/R
return omega/(2*np.pi)*60.0
lowest = (0.2, 1.0) # tow_speed, tsr
highest = (1.4, 4.0)
rpm_start = calc_rpm(lowest)
rpm_end = calc_rpm(highest)
steps = 25
rpms = np.linspace(rpm_start, rpm_end, steps)
revs = np.ones(len(rpms))*30.0
revs[0] = 4
revs[1] = 8
revs[2] = 12
revs[3] = 16
revs[4] = 20
revs[5] = 24
revs[-1] = 32
df = pd.DataFrame()
df["rpm"] = rpms
df.index.name = "run"
df["revs"] = revs
df.to_csv("Config/Test plan/Tare-torque.csv")
df["minutes"] = revs/rpms
df["samples"] = np.floor(df.minutes*60*2000)
df["samples_per_rev"] = df.samples/df.revs
print("Total time (minutes):", df.minutes.sum())
df
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