🔬 Honours Astrodynamics & Symplectic AI Research

About the NanoDynamics Orbital Engine

NanoDynamics combines analytical Keplerian mechanics, high-order numerical perturbation integrators, Symplectic Hamiltonian Physics-Informed Neural Networks (PINNs), and physical ESP32-S3 microcontroller Hardware-in-the-Loop (HIL) validation.

1. J2–J4 Zonal Harmonics & Drag

Full Earth oblateness perturbations (J2, J3, J4), exponential & NRLMSISE-00 atmospheric drag, solar radiation pressure (SRP), and third-body Moon/Sun gravitational attraction integrated via adaptive RK45 and Velocity Verlet schemes.

a_total = -μ·r/|r|³ + a_J2..J4 + a_drag(ρ, Cd, A/m) + a_SRP + a_3body

2. Symplectic Hamiltonian PINNs

Standard neural networks suffer from secular energy drift over multi-orbit rollouts. Our Symplectic Hamiltonian Projection guarantees conservation of specific mechanical energy within <10⁻⁶ relative drift while accelerating inference by 40×.

E = ½|v|² - μ/|r| = const • v_proj = v_nn · √(2(E₀ + μ/|r_next|)) / |v_nn|

3. ESP32-S3 Hardware-in-the-Loop & Breakup Cascades

Real-time orbital state vectors stream over ESP-NOW / USB-Serial to physical ESP32-S3 nodes running quantized C++ PINN inference, paired with NASA Standard Breakup Model Keplerian debris cloud propagation.

HIL RTT < 1.8 ms • NORAD SATCAT + Asterank Mining Catalog Integrated
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