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Rolling Down a Ramp Calculator

Find the speed of a rolling object at the bottom of a ramp.

Inputs

Results

Speed at bottom3.742927m/s
Speed if sliding (no friction)4.428691m/s

Chart

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How to use the rolling down a ramp calculator

Find the speed of a rolling object at the bottom of a ramp. Enter ramp height, shape in the fields above; the speed at bottom, speed if sliding (no friction) are computed instantly and plotted on the chart so you can see how the answer changes.

Common searches this calculator answers include “race of a ball and a cylinder”, “rolling without slipping speed”, “calculate rolling down a ramp”, “find speed at bottom”, “find speed if sliding”.

Formula

Speed at bottom (m/s) = √(2 × GRAV × h / (1+k))
Speed if sliding (no friction) (m/s) = √(2 × GRAV × h)

Variables

  • h — Ramp height (m)
  • k — Shape (—)

Worked example

With ramp height = 1 m, shape = Solid sphere, the calculator gives speed at bottom ≈ 3.742927 m/s; speed if sliding (no friction) ≈ 4.428691 m/s.

Frequently asked questions

What is the rolling down a ramp calculator used for?

Find the speed of a rolling object at the bottom of a ramp. It helps with questions such as “race of a ball and a cylinder”, “rolling without slipping speed”, “calculate rolling down a ramp”.

What is the formula for the rolling down a ramp calculation?

Speed at bottom (m/s) = √(2 × GRAV × h / (1+k)). Speed if sliding (no friction) (m/s) = √(2 × GRAV × h). Here h is ramp height (m), k is shape (—).

What inputs do I need for the rolling down a ramp calculator?

You need ramp height in m, shape in —. Each field is pre-filled with a typical example so you can see how the result responds as you edit the numbers.

How do I use the rolling down a ramp calculator?

Type values into the input fields. Results and the chart update instantly. Use Reset to restore the example values, Copy results to paste them elsewhere, or Share to copy a link that preserves your inputs.

Is the rolling down a ramp result exact?

Calculations use standard formulas and double-precision arithmetic, then display about seven significant figures. Real-world measurements carry uncertainty, so treat results as estimates unless your inputs are exact.

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