An object-oriented implementation of the Classical Lamination Theory in Python.
Consider a C/PEEK drive shaft with a length of 1.25 m, a wall thickness of 2 mm, and a radius of 50 mm. The shaft has a [45/-45]s layup and is subjected to a torque of 500 Nm. We will determine the maximum angular deformation of the shaft.
from tompouce import Material, Laminate, torsion_shaft
from numpy import rad2deg, deg2rad
# Parameters
length = 1.25
radius = 50E-3
torque = 500.0
# Create a Material object using data from a json file
TC1200 = Material('materials/TC1200_UD.json')
# Create a Laminate object
ply_thickness = 0.5E-3
layup = [45.0, -45.0, -45.0, 45.0]
shaft = Laminate(deg2rad(layup), TC1200, ply_thickness)
# Create a Load object
load = torsion_shaft(torque, radius)
# Print the loads and deformations
shaft*loadWhich provides a summary of the loads and the resulting deformations:
Deformation Load Thermal Load
{ 0.00E+00} [ a a a | b b b ] ( { 0.00E+00} { 0.00E+00} )
{ 0.00E+00} [ a a a | b b b ] ( { 0.00E+00} { 0.00E+00} )
{ 4.54E-04} [ a a a | b b b ] ( { 3.18E+04} { 0.00E+00} )
{---------} = [---------------] ( {---------} + {---------} )
{ 0.00E+00} [ b b b | d d d ] ( { 0.00E+00} { 0.00E+00} )
{ 0.00E+00} [ b b b | d d d ] ( { 0.00E+00} { 0.00E+00} )
{ 0.00E+00} [ b b b | d d d ] ( { 0.00E+00} { 0.00E+00} )
The deformation can also be calculated and then used to determine the angular deformation:
# Calculate and print the deformation
_, d = shaft.loaddef(load)
angle = d[2]*length/radius
print(f"The angular deformation of the shaft is {rad2deg(angle):.2f} degrees.")The angular deformation of the shaft is 0.65 degrees.
Here you can find a small example gallery, which should give you a pretty good idea what tompouce can do and how things work.
You can install tompouce using pip:
pip install git+https://github.com/wjbg/tompouce.git
Alternatively, you can also clone or download this repository as zip file. Tompouce is reasonably well-documented - if I may say so - and the annotated examples should be sufficient to get you started.
There are many alternative implementations of the CLT in Python. One of these is my own wjbg/py.CLT, which follows a functional programming paradigm. For more alternatives, please check out this (non-exhaustive) list:
Free as defined in the MIT license.