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Rotational dynamics simulation

A rotational simulation uses the same update shape as linear motion: inputs create angular acceleration, angular acceleration updates angular velocity, and angular velocity updates angle.

Think like a programmer

Keep the rotational model in a pure update function and let the renderer display angle. This makes the zero-torque test and torque/inertia proportionality test independent of a spinning canvas.

Model checklist

Inputs
Torque, moment of inertia, angle, angular velocity, and time step.
State
Angle and angular velocity.
Rule
Update angular velocity from torque/inertia, then update angle.
Output
New angular state.
Check
Zero torque leaves angular velocity unchanged in the ideal model.

Torque updates angular motion

Change torque and moment of inertia. The same torque produces less angular acceleration for a harder-to-rotate body.

Torque 6 N·m; moment of inertia 2 kg·m²; angular acceleration 3.00 rad/s²; rotational energy at 3 rad/s 9.00 J.

Use the same state machine as translation

For a fixed-axis rigid rotor, declare positive angle and torque, then store unwrapped angle (\theta) and angular velocity (\omega). The ideal model is:

\[\alpha=\frac{\tau}{I}, \qquad \omega_{n+1}=\omega_n+\alpha_n\Delta t, \qquad \theta_{n+1}=\theta_n+\omega_{n+1}\Delta t.\]

The last form is a symplectic-style update: angular velocity changes before position. A screen may wrap (\theta) for a readable dial, but wrapping belongs only in display code; it must not erase accumulated turns from solver state.

Make torque inputs traceable to force and lever arm, with a stated sign convention. Keep inertia positive and in the correct units. If torque depends on angle or speed, compute it from the old state before the update and log it. Friction is an external transfer: record its torque and work instead of declaring angular momentum or mechanical energy conserved.

Validate the integrator, not the spinner

Use fixtures: zero torque keeps (\omega) constant, constant torque matches the analytic (\omega(t)=\omega_0+\tau t/I), doubling inertia halves angular acceleration, and reversing torque reverses the acceleration. For a conservative torsional spring, compare energy and phase at the same physical duration under smaller time steps. Record (\theta,\omega,\tau,I,\Delta t), energy terms, and any event handling at a fixed output cadence.

The scalar model has one rotation axis. A freely rotating three-dimensional body requires orientation, an inertia tensor, body/world transforms, and vector angular momentum. Do not interpret a stable 2D canvas as evidence for that richer system.

Try this experiment

Prediction: At the same torque, a larger inertia changes angular velocity more slowly.

Move the inertia control from 1 to 8. Use the displayed angular acceleration to predict which update will be smaller before reading it.

Where this model breaks

Long simulations can drift, and real rotation can include friction, flexible bodies, changing inertia, and 3D coupling. Validate against analytic and conservation cases before adding visual complexity.

Summary

Build a pure unwrapped angular state update, separate display wrapping, and test analytic torque cases, energy behavior, units, signs, and fixed-duration refinement before trusting the animation.

Glossary

Self-check

  1. Which state field does torque update first?
  2. What is the zero-torque test?
  3. What real effects can the ideal model omit?

Sources

Model contract

Treat the lesson as a small function before treating it as a fact to memorize. Give every value a unit, keep only the state needed for the next step, and make the output easy to inspect.

\[\text{observable output} = f(\text{inputs},\,\text{state})\]
Inputs
Quantities you set or measure, with units and useful bounds.
State
Values the program must retain to reproduce the next result.
Rule
The relationship or update that turns inputs and state into a result.
Check
A known limit, unit check, invariant, or measured result that can expose a bad model.

Implement the idea as a model

For Rotational Dynamics Simulation, write down the quantities you can control, the values your program must retain, and the result a reader could inspect. In Rotational Motion, the useful program is not the drawing: it is the smallest explicit model that makes a prediction you can test.

Guided experiment

Prediction: changing one declared input while holding the others fixed should change only the outputs that the model connects to that input. Choose one input, predict the direction of change, then check a limiting case such as zero, a symmetric arrangement, or a familiar low-speed or small-change approximation.

Where this model breaks

This lesson is a teaching model, not a complete simulator. Before using it outside the stated question, check which interactions, scales, uncertainties, boundary conditions, and measurement limits it leaves out.

Summary

Treat Rotational Dynamics Simulation as a contract: named inputs and units enter a rule, the rule produces an observable result, and a known limit or invariant checks whether the implementation deserves trust.

Glossary

  • Input: a measured value or chosen parameter supplied to a model.
  • State: the smallest set of values needed to continue or reproduce a model.
  • Validation: comparing an output with a known result, limit, invariant, or measurement.

Self-check

  1. Which values are inputs, and which values must remain state?
  2. What observable result would tell you the model is behaving as expected?
  3. Which assumption would you test first before applying the model to a real system?

Model review: turn Rotational Dynamics Simulation into a test

Use torque and inertia to update angular motion, then test the result against zero-torque and proportional-response cases.

  1. Name the inputs and units that the rotational motion model needs.
  2. Separate the state you must keep from values you can calculate when needed.
  3. Write one rule that maps the current state and inputs to an observable result.
  4. Choose a limiting case, unit check, invariant, or known result before trusting an output.
  5. State one assumption you would change before using this simplified model for a real decision.

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