From 21521749cff5d235c7023f67c134360ed834f3ac Mon Sep 17 00:00:00 2001 From: Andrew Ning Date: Fri, 20 Sep 2024 09:26:06 -0600 Subject: [PATCH] accel file --- atom.xml | 2 +- feed.xml | 2 +- me275/schedule/accel.dat | 1201 +++++++++++++++++++++++++++++++++ me275/schedule/hw3/index.html | 2 +- 4 files changed, 1204 insertions(+), 3 deletions(-) create mode 100644 me275/schedule/accel.dat diff --git a/atom.xml b/atom.xml index 7427d24e..a5021f56 100644 --- a/atom.xml +++ b/atom.xml @@ -4,7 +4,7 @@ FLOW Lab - 2024-09-20T09:21:56-06:00 + 2024-09-20T09:26:01-06:00 http://flow.byu.edu Andrew Ning diff --git a/feed.xml b/feed.xml index 24b69395..1ae8355e 100644 --- a/feed.xml +++ b/feed.xml @@ -1 +1 @@ -Jekyll2024-09-20T09:21:56-06:00http://flow.byu.edu/feed.xmlFLOW LabFlight, Optimization, and Wind LaboratoryAndrew NingOptimization Book Available2021-10-15T00:00:00-06:002021-10-15T00:00:00-06:00http://flow.byu.edu/posts/opt-book]]>Andrew NingBEM Paper2021-07-30T00:00:00-06:002021-07-30T00:00:00-06:00http://flow.byu.edu/posts/bem-paper]]>Andrew NingEduardo Research Update2021-03-01T00:00:00-07:002021-03-01T00:00:00-07:00http://flow.byu.edu/posts/eduardo-latest]]>Eduardo AlvarezReformulated VPM2021-02-01T00:00:00-07:002021-02-01T00:00:00-07:00http://flow.byu.edu/posts/reformulated-vpm]]>Eduardo AlvarezOptimization Book Announcement2021-01-20T00:00:00-07:002021-01-20T00:00:00-07:00http://flow.byu.edu/posts/optimization-book]]>Andrew NingPJ Defense2020-09-30T00:00:00-06:002020-09-30T00:00:00-06:00http://flow.byu.edu/posts/pj-defense]]>Andrew NingVPM Paper2020-08-30T00:00:00-06:002020-08-30T00:00:00-06:00http://flow.byu.edu/posts/vpm-paper]]>Eduardo AlvarezAirborne Wind with Vortex Particle Method2020-08-16T00:00:00-06:002020-08-16T00:00:00-06:00http://flow.byu.edu/posts/wind-harvesting]]>Judd Mehr and Eduardo AlvarezEduardo’s Past Three 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Announcement2021-01-20T00:00:00-07:002021-01-20T00:00:00-07:00http://flow.byu.edu/posts/optimization-book]]>Andrew NingPJ Defense2020-09-30T00:00:00-06:002020-09-30T00:00:00-06:00http://flow.byu.edu/posts/pj-defense]]>Andrew NingVPM Paper2020-08-30T00:00:00-06:002020-08-30T00:00:00-06:00http://flow.byu.edu/posts/vpm-paper]]>Eduardo AlvarezAirborne Wind with Vortex Particle Method2020-08-16T00:00:00-06:002020-08-16T00:00:00-06:00http://flow.byu.edu/posts/wind-harvesting]]>Judd Mehr and Eduardo AlvarezEduardo’s Past Three Years2020-08-10T00:00:00-06:002020-08-10T00:00:00-06:00http://flow.byu.edu/posts/eduardo-three-years]]>Eduardo AlvarezFLOWUnsteady in Google Drive2020-08-02T00:00:00-06:002020-08-02T00:00:00-06:00http://flow.byu.edu/posts/google-drive-vpm]]>Eduardo Alvarez \ No newline at end of file diff --git a/me275/schedule/accel.dat b/me275/schedule/accel.dat new file mode 100644 index 00000000..c0af84e3 --- /dev/null +++ b/me275/schedule/accel.dat @@ -0,0 +1,1201 @@ + 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787d8d2b..79fc6cdf 100644 --- a/me275/schedule/hw3/index.html +++ b/me275/schedule/hw3/index.html @@ -122,7 +122,7 @@

HW 3

Integrate this using np.trapz (or np.trapezoid depending on your version of numpy) for a range of linspace discretization points demonstrating convergence (show a plot with number of discretization points on x-axis and the integral on y-axis). Also evaluate the integral using scipy.integrate.quad and compare the result (add a dashed line to the plot with the resulting integral).

  • -

    An accelerometer is placed on the first stage of a rocket launch. The results are in file accel.dat, which has two columns: time (s) and acceleration (m/s\(^2\)) starting from rest. Numerically integrate to find velocity as a function of time. Make a figure with two subplots, with velocity vs. time on top and acceleration vs. time on bottom (see this example of pyplot.subplot, although you should label your axes). Why is the velocity data less noisy than the acceleration data?

    +

    An accelerometer is placed on the first stage of a rocket launch. The results are in file accel.dat (may need to right click and save as), which has two columns: time (s) and acceleration (m/s\(^2\)) starting from rest. Numerically integrate to find velocity as a function of time. Make a figure with two subplots, with velocity vs. time on top and acceleration vs. time on bottom (see this example of pyplot.subplot, although you should label your axes). Why is the velocity data less noisy than the acceleration data?