Python for Mechanical Engineers

Learn to use Python loops, including for loops with range, to print squares of numbers from 0 to 10 and perform simple accumulations like sums and products.

Explore while loops in python through a summing example: initialize sum, increment i, update sum, print running totals, and apply break conditions; compare with for loops and touch on Newton-Rapson.

Learn to define and call Python functions to compute geometric expressions, such as cube volume and cylinder area, by passing parameters and returning results.

Explore NumPy and other numerical libraries in Python, install and import them in Jupyter, and perform basic operations like sine, cosine, and matrix math.

Explore numpy in mechanical engineering: generate equally spaced numbers with linspace and arange, perform elementwise operations like x squared, and practice matrix addition and dot products.

Plot data with matplotlib in Python using pyplot. Create x and y data, add titles, labels, legends, axis limits, and plot multiple series with styles on one figure.

Create and customize figures and axes in Matplotlib, setting size, dpi, and plotting data with labels. Arrange side-by-side or inset axes and zoom by adjusting coordinates and axis limits.

Master grid spec layouts in Matplotlib to arrange three subplots in a 2x2 grid, customize figure and axis backgrounds, enable grid lines, and manage legends.

Create 2D contour plots of z=f(x,y) with numpy and matplotlib, building x and y grids, using contour and contourf, color maps, levels, and color bars.

Create 3D surface plots from z data in matplotlib using a mesh grid, 3D axes, color maps, and color bars.

Explore projectile motion fundamentals, derive x and y velocity components and time of flight, and plot trajectories for multiple launch angles using numpy and matplotlib.

Demonstrates how to build a shear force and bending moment diagram for a simply supported beam under a uniform load by computing reactions, V(x), M(x), and plotting with fill-between shading.

Compute shear force and bending moment diagrams for a simply supported beam with a distributed load, calculate reactions, and plot the SFD and BMD using a Python program.

Develop a Python program to compute the slider-crank kinematics, including displacement, velocity, and acceleration as the crank rotates, using theta, omega, radius, and connecting rod length, with SciPy derivative functions.

Learn to solve ordinary differential equations in the vibration context using scipy odeint, defining the equation, initial conditions, dependent and independent variables, and integrating over x with plotting.

Explore the quarter car suspension model with two masses, and derive the mass, damping, and stiffness matrices to solve the equations of motion for road disturbances in Python.

This lecture derives the complete equation of motion for a two-degree-of-freedom quarter car suspension, converts it to a state-space form, and outlines a numerical integration approach for displacement and velocity.

Program a quarter car suspension model in Python using numpy to simulate a sinusoidal road surface with amplitude and frequency, and compute vehicle and wheel displacements and velocities.

Model the quarter car suspension response to a road with a single bump using a time-limited forcing function, and examine how stiffness, damping, and velocity shape peak displacement.

Explore how to analyze the diesel cycle with a Python program by plotting a pressure-volume diagram using inputs like bore diameter, stroke length, compression ratio, inlet pressure, and temperatures.

Explore the temperature distribution in a 2D square plate by solving with finite difference under boundary conditions, using Python to iterate and visualize results.

Demonstrates a program to plot flow around a cylinder using streamlines, radial and tangential velocity components, converted to Cartesian, with a circular patch and interior masking.

Plot the pressure distribution around a cylinder in a Python script using flow velocity, cylinder radius, and fluid density to compute and visualize pressure with a jet colormap.

Explore finding the minima of a function with SciPy's optimize in Python, define a cost function, choose initial guesses, and plot to see how starting values influence the solution.

This lecture demonstrates solving a linear programming problem using the simplex method. It shows converting constraints to ≤ form and obtaining the minimum objective value for x1, x2, x3.

Learn symbolic mathematics in Python for mechanical engineers using the sympy library to represent equations as symbols, perform polynomials, calculus, limits, differentiation, integration, series, and solve systems and matrices.

Develop a Python Tkinter GUI for a simply supported beam SFD and BMD calculator, with labeled inputs for beam length, point load, and distance from the left, plotting with Matplotlib.

Create a Tkinter graphical user interface that displays shear force and bending moment diagrams for a beam using Matplotlib figures and canvases, with grid layout and labeled axes.