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Aerospace

Learn programming through orbits, flight, and numerical models. Choose Python for the flight and mission pathway, or Fortran for numerical methods and a sounding rocket simulation.

What helps

Familiarity with units and algebra will help you begin. Later projects draw on calculus, vectors, mechanics, and numerical methods.

Python pathway

Programming Foundations / Practice rooms / Track curriculum and enrollment

  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.

    • Kepler's Laws: 5 lessons
    • Velocity & Energy: 5 lessons
    • Maneuvers & Δv: 5 lessons
    • Tracking & Time: 5 lessons
    • Capstone: Orbit Propagator: 5 lessons

  2. 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.

    • NumPy Arrays: 5 lessons
    • The Standard Atmosphere: 5 lessons
    • Lift & Drag: 5 lessons
    • Drag Polar & L/D: 5 lessons
    • Capstone: Glide Performance: 5 lessons

  3. 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.

    • The Rocket Equation: 5 lessons
    • Mass & Propellant: 5 lessons
    • Thrust & Acceleration: 5 lessons
    • Staging: 5 lessons
    • Capstone: Design to Orbit: 5 lessons

  4. 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.

    • Sampling & Signals: 5 lessons
    • Noise & SNR: 5 lessons
    • Filtering: 5 lessons
    • Frequency & the FFT: 5 lessons
    • Capstone: Telemetry Pipeline: 5 lessons

  5. 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.

    • State Vectors & Euler: 5 lessons
    • Runge-Kutta 4: 5 lessons
    • Euler vs RK4: 5 lessons
    • Conservation Laws: 5 lessons
    • Capstone: Orbit Propagator: 5 lessons

  6. 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.

    • Loading Data: 5 lessons
    • Exploring: 5 lessons
    • Filtering & Cleaning: 5 lessons
    • Grouping: 5 lessons
    • Capstone: Flight Report: 5 lessons

  7. 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.

    • The Feedback Loop: 5 lessons
    • Proportional Control: 5 lessons
    • Derivative Damping: 5 lessons
    • Integral Action: 5 lessons
    • Tune a PID: 5 lessons

  8. 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.

    • Stress, Strain & Safety: 5 lessons
    • Beam Bending: 5 lessons
    • Column Buckling: 5 lessons
    • Pressure Vessels & Combined Stress: 5 lessons
    • Truss Solver: 5 lessons

  9. 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.

    • Root Finding: 5 lessons
    • Minimization: 5 lessons
    • Curve Fitting: 5 lessons
    • Multivariable Optimization: 5 lessons
    • Constrained Optimization: 5 lessons

  10. 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.

    • The Delta-V Budget: 5 lessons
    • Launch to Orbit: 5 lessons
    • The Interplanetary Transfer: 5 lessons
    • Arrival & Capture: 5 lessons
    • Mission Optimization: 5 lessons

Fortran pathway

Programming Foundations / Practice rooms / Track curriculum and enrollment

  1. Fortran for Numerics: Foundations

    Use real64 arithmetic, procedures, control flow and arrays to analyze flight data. Build a summary that retains the peak, mean, supersonic count and peak-flow classification. Distinguish physical assumptions from the numeric operations that implement them.

    • Numbers and Procedures: 5 lessons
    • Control Flow: 5 lessons
    • Arrays and Vectors: 5 lessons
    • Accumulation and Iteration: 5 lessons
    • Capstone: Flight Data Analyzer: 5 lessons

  2. Arrays and Whole-Array Geometry

    Work with matrix shapes, column-major indexing, sections, intrinsic operations and logical masks. Finish with a complete point-cloud rotation report containing transformed coordinates and before/after norms. Array syntax can support optimization; it does not guarantee speed.

    • Multidimensional Arrays: 5 lessons
    • Array Sections: 5 lessons
    • Array Intrinsics: 5 lessons
    • Masks and Selection: 5 lessons
    • Capstone: Transforming a Point Cloud: 5 lessons

  3. Procedures and Modules

    Build reusable Fortran procedures with pure and elemental attributes, optional and keyword arguments, explicit callback interfaces, recursion and generics. Compose addition, norm, normalization, dot product and angle cosine into a consistent vector library.

    • Pure and Elemental Procedures: 5 lessons
    • Flexible Interfaces: 5 lessons
    • Procedures as Arguments: 5 lessons
    • Recursion and Generic Interfaces: 5 lessons
    • Capstone: a Vector Library: 5 lessons

  4. Numerical Methods

    Implement bracketing, bounded root iteration, interpolation, quadrature and finite differences. Finish by applying the supplied callback to a root, slope and integral analysis. Input assumptions, failure values and numerical error are part of each method contract.

    • Bracketing and Bisection: 5 lessons
    • Newton's Method: 5 lessons
    • Interpolation: 5 lessons
    • Integration in Depth: 5 lessons
    • Capstone: Characterize a Function: 5 lessons

  5. Differential Equations and Dynamics

    Advance scalar and coupled ODE states with Euler and classical RK4. Model decay, cooling, an oscillator, a projectile with drag and a normalized two-body orbit. Retain trajectories and diagnostics so numerical error and invariant drift can be measured.

    • Euler's Method: 5 lessons
    • Runge-Kutta (RK4): 5 lessons
    • Systems of Equations: 5 lessons
    • Projectile Flight: 5 lessons
    • Orbital Mechanics: 5 lessons

  6. Linear Algebra: The Solver Core

    Build triangular solves, Gaussian elimination, partial pivoting, LU, Thomas, Jacobi and Gauss-Seidel methods. Compare complete solution vectors and residuals on the same system. No-pivot restrictions and iterative convergence conditions remain explicit.

    • Gaussian Elimination: 5 lessons
    • Pivoting for Stability: 5 lessons
    • LU Decomposition: 5 lessons
    • Tridiagonal Systems: 5 lessons
    • Iterative Methods: 5 lessons

  7. Finite Differences and CFD Kernels

    Build finite-difference heat, advection and Laplace kernels on uniform grids. Respect each scheme's stability interval, preserve boundary values and account for boundary fluxes. Finish with a full plate field and an explicit residual-based convergence report.

    • Finite Differences: 5 lessons
    • The Heat Equation: 5 lessons
    • Advection: 5 lessons
    • Laplace's Equation in 2D: 5 lessons
    • Capstone: Heat on a Plate: 5 lessons

  8. The Finite Element Method

    Assemble axial spring and bar elements, impose supports, solve displacements, and recover member forces, strains, stresses and reactions. Finish with a two-member stepped-bar analysis from material and geometry inputs. This is a small-strain, linear-elastic axial model.

    • The Spring Element: 5 lessons
    • Assembly: 5 lessons
    • Supports, Loads, and Solving: 5 lessons
    • Bar Elements and Stress: 5 lessons
    • Capstone: A Stepped Bar: 5 lessons

  9. Numerical Kernels and Performance Measurement

    Study memory traversal, array arithmetic, independent loops, reductions and scans. Compose row and column matrix-vector kernels into a repeated observable benchmark with complete outputs, errors, checksums and CPU-time status. Compiler and hardware evidence is needed before claiming speedup or parallel execution.

    • Memory and Cache: 5 lessons
    • Vectorization: 5 lessons
    • do concurrent: 5 lessons
    • Reductions and Scans: 5 lessons
    • Capstone: Verify and Measure a Numerical Kernel: 5 lessons

  10. Capstone: A Sounding Rocket

    Assemble a constant-mass, no-drag sounding-rocket model with an event-aligned RK4 history, five ascent metrics, axial strength and ideal Euler-buckling checks, and a configurable mission verdict. Preserve the full result behind the report. This educational model is not a validated flight or launch-safety analysis.

    • The Rocket and its Forces: 5 lessons
    • Simulating the Ascent: 5 lessons
    • Mission Performance: 5 lessons
    • Structural Integrity: 5 lessons
    • The Mission Report: 5 lessons