Python model for a torsional spring-brake assembly using the capstan (belt-friction) effect. Computes static and dynamic performance metrics for a cylindrical spring with friction-based braking — relevant to rotational damping and actuator design.
Given geometry and material parameters, the model computes:
- Mass and moment of inertia from cylindrical geometry and material density
- Torsional spring constant from material properties
- Capstan ratio: Force amplification from friction and wrap angle (F_out / F_in = e^(mu * theta))
- Brake torque: Friction torque accounting for wrap angle and normal force
- Dynamic response: Time to stop, time to restore, switching frequency
- Reflected inertia and net force calculations
python "spring model.py"Default parameters: height = 0.1 m, aluminum density, mu = 0.2.
| Parameter | Symbol | Default |
|---|---|---|
| Height | h | 0.1 m |
| Material density | rho | Al |
| Friction coeff. | mu | 0.2 |
| Wrap angle | theta | varies |
Output prints computed torque, forces, capstan ratio, and brake performance metrics.
MIT