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Programming for Aerospace Engineers

Learn Python by solving real aerospace problems, orbits, trajectories, and flight dynamics.

11 projects, 275 hands-on levels, run in your browser.

Syllabus

  • Foundations: code through aerospace: Never written code before? Start here. You will learn the absolute basics of Python, output, variables, types, decisions, loops, and functions, using rockets, orbits, and flight as your playground. By the end you are ready for Project 1.
  • Orbital Mechanics: Join the Aurora Relay flight-dynamics study. Build a reference-orbit table, investigate orbital energy, prepare a maneuver budget, forecast ground crossings, and finish with a numerical propagation report whose evidence you can defend.
  • Atmospheric Flight: Why aircraft fly and how the air changes with altitude. You'll pick up NumPy and Matplotlib while modelling the standard atmosphere, lift and drag, and a glider's performance.
  • Rocket Performance: What it takes to reach orbit. Work through the rocket equation, mass budgets, thrust, and staging, then design a two-stage rocket that makes orbit.
  • Signals & Telemetry: Spacecraft talk in signals. Sample a waveform, add and measure noise, filter it out, and use the FFT to find a hidden tone, the foundations of telemetry.
  • Trajectory Simulation: Numerically fly a spacecraft. Build state-vector integrators from Euler to Runge-Kutta 4, compare their accuracy, and check the conservation laws that prove a simulation is trustworthy.
  • Flight Data Analysis: Turn raw flight logs into insight. Load real CSV telemetry with pandas, explore and clean it, group it by flight phase, and produce a flight report.
  • Control Systems: Hold a spacecraft's attitude steady with feedback control. Build up a PID controller term by term, see why each one matters, and tune it to meet a spec.
  • Structures & Loads: Work out whether an aerospace structure survives its loads. Start with stress in a single rod, build through beam bending, buckling, and pressure vessels, then solve a whole truss with linear algebra.
  • Optimization: Let the computer find the answer. Use SciPy to solve equations that have no formula, fit models to data, and search design spaces for the best wing, the fastest cruise, and the lightest tank.
  • Mission Design: Connect rocket mass accounting, orbital transfer, departure and selected Mars capture into a preliminary mission model. Allocate reserves and optimize a two-stage in-space stack with explicit mass ledgers. The ascent allowance is a budget assumption, not a modeled launcher; ideal patched conics do not constitute a crewed or flight-qualified mission.

Key concepts

  • Circular orbital speed: The tangential speed of an ideal circular two-body orbit at center-to-center radius r is sqrt(mu/r). A different speed generally gives a noncircular trajectory…
  • Delta-v: A change in velocity, measured in m/s. An impulsive maneuver cost is the magnitude of its velocity change; mission budgets sum maneuver costs and stated allowa…
  • Dynamic pressure: q = rho v_air^2/2, a kinetic-pressure scale in pascals using air-relative speed. Aerodynamic forces scale as coefficient q*reference area. Max-Q need not be th…
  • Escape velocity: In the ideal two-body model, sqrt(2*mu/r) is the zero-specific-energy speed at radius r, without further propulsion. An inward path may still hit the central b…
  • Hohmann transfer: An ideal two-impulse transfer between circular coplanar orbits using an ellipse tangent to both. Outward transfers use two prograde burns; inward transfers use…
  • Kepler's laws: For ideal bound two-body motion: an orbit is an ellipse with the central body at a focus; the radius vector sweeps equal areas in equal times; and T^2 is propo…
  • Lift and drag: Drag opposes motion relative to the air; lift is perpendicular to that relative flow. Neither direction is necessarily vertical. Their magnitudes are coefficie…
  • Orbital period: The time for one full orbit. For a circular orbit of radius r about a body of gravitational parameter mu, T = 2 pi sqrt(r^3/mu).
  • Runge-Kutta (RK4): Classical fourth-order Runge-Kutta advances a state using four derivative evaluations per step. For smooth equations and sufficiently small steps, its global e…
  • Specific impulse (Isp): Thrust divided by propellant mass-flow rate and standard gravity: Isp = F/(mdot g0), in seconds. Effective exhaust velocity is Isp g0. Higher Isp gives more id…
  • Staging: Discarding spent hardware so later propulsion accelerates less mass. Compute each burn using the complete remaining stack. Staging can improve capability, but…
  • Tsiolkovsky rocket equation: Ideal delta-v = ve*ln(m0/mf) for constant effective exhaust velocity and no external-force losses. Initial and final masses include payload and retained hardwa…