Computational Thinking and Modeling Laminar Air Drag with Code

Abstract

This presentation for CAST 2022 in Dallas discusses how computational thinking practices can impact physics learning when students write computer programming code to model air drag. The model produces data that students use to compare the results of a direct video measurement activity about air drag. The datasets are then analyzed using a Google Notebook (Jupyter Notebook) running python to compare laminar versus turbulent flows. Here is a live version of the slides: https://docs.google.com/presentation/d/e/2PACX-1vQrRzuUaj9V_jTBj-IJ8WTJ3ck1Ye3HIo3tjFzLen-od37qX_uNSbFsTUvpDc838rgR27VNuI2kZL1Q/pub?start=false&loop=false&delayms=3000

Full text

Computational Thinking and
Modeling Laminar Air Drag with
Code
James Newland - Bellaire HS - University of Houston College of Education
https://jimmynewland.com/

Computational Thinking (CT) In Science Classes
Taxonomy of CT in Math and Science from Weintrop, et al., (2016).
CT is defined for
this project as
using data and
modeling practices
to explore a
physical system or
phenomenon using
computer
programming.

The Euler-Cromer Modeling Paradigm
With Euler-Cromer modeling, variable accumulation allows for state changes. Usually time is
iterated and there is simple visualization (Cromer, 1981). Note, p5js calls the draw function
automatically.

Accelerate the blob STEMcoding example

Modeling Laminar Flow with STEMcoding - live version - code version
●Model developed using Newton’s 2nd
law from AP Physics C: Mechanics
Curriculum
●Needs to happen late in AP Physics C:
Mechanics course
●Likely needs follow students
practicing derivation problems first

Euler-Cromer: Updating State Variables (Position, Velocity, and Acceleration)

Model Single Box with Drag

Model 6 Boxes of Varying Mass

Finding Terminal Velocity from Model
The code generates actual data
from the model for the students
to use for further analysis and
visualization. (Javascript console
in the browser)

Finding Terminal Velocity from Model
Fluid Flow
around a Cube
from Schröder
et al., 2020 Data Reduction Google Colab Notebook

Laminar Flow Test
Air drag can be
modeled as laminar
or turbulent
Laminar
Turbulent
Data Reduction Google Colab Notebook

Falling Coffee Filters activity from Pivot Interactives
●STEMcoding activity
happens on one day.
●Pivot Interactives activity
happens on another day.
●Then on a third day,
students can use a
pre-built Google Colab
(Jupyter Notebook) to
compare their model and
their real-world drag
analysis.
(blank student Google Colab notebook)

Google Colab (Jupyter Notebook) Analysis Python Code

References & Code
●Cromer, A. (1981). Stable solutions using the Euler approximation. American Journal of
Physics, 49(5), 455–459. https://doi.org/10.1119/1.12478
●Newland, J. (2020). jimmynewland/colabnotebooks: Google Colab Notebooks.
https://doi.org/10.5281/ZENODO.4318058
●Orban, C. M., & Teeling-Smith, R. M. (2020). Computational Thinking in Introductory
Physics. The Physics Teacher, 58(4), 247–251. https://doi.org/10.1119/1.5145470
●Schröder, A., Willert, C., Schanz, D., Geisler, R., Jahn, T., Gallas, Q., & Leclaire, B. (2020). The
flow around a surface mounted cube: a characterization by time-resolved PIV, 3D
Shake-The-Box and LBM simulation. Experiments in Fluids, 61(9), 1–22.
https://doi.org/10.1007/s00348-020-03014-5
●Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016).
Defining Computational Thinking for Mathematics and Science Classrooms. Journal of
Science Education and Technology, 25(1), 127–147.
https://doi.org/10.1007/s10956-015-9581-5
●Wijaya, P. A., Fauzi, U., & Latief, F. D. E. (2019). A simple determination of air drag using
video tracker and modifiable projectile launcher. Physics Education, 54(5).
https://doi.org/10.1088/1361-6552/ab26eb
●Ye, Q., & masso, evelyn. (2021, March 18). p5js Home. https://p5js.org/