Physical Computing
Physical computing is how the physical world is made to run inside a computer. A waving flag, a strand of hair, smoke curling off a flame, a bridge under load — each is turned into numbers a machine can step forward in time.
The core move is discretization: a continuous object becomes a finite set of points, and the laws of physics — forces, velocities, constraints — become arithmetic a machine repeats millions of times a second.
Most soft things start as a mass-spring system. Pin point masses together with springs that pull when stretched and push when squeezed, add gravity and a little damping, and a flat grid of points begins to drape, swing, and ripple like real cloth.
Time advances by integration. Knowing each point’s position and the forces on it, you take a small step forward — explicit Euler is simplest; Verlet and implicit schemes trade cost for stability so the simulation doesn’t blow up.
Fluids are the hard, beautiful case. The Navier–Stokes equations govern every wisp of smoke and breaking wave, and solving them on a grid or with particles is what turns code into water, fire, and moving air.
Stiffer matter calls for the finite element method: break a beam or a wing into small cells, solve how each one deforms under load, and stitch the answers into the stress and strain of the whole structure.
Aerodynamics is physical computing aimed at air. Stream a flow past a wing, resolve the pressure above and below, and the same equations that animate smoke predict lift, drag, and whether a shape will fly.
It is where mathematics, physics, and code meet a deadline. The world won’t simplify itself, so you choose what to approximate — and a good approximation, stepped fast enough, can be indistinguishable from the real thing.