Polar Double Integral Calculator
A polar double integral calculates the volume under a surface in polar coordinates. This calculator computes the integral of a function f(r,θ) over a specified region in the plane.
What is a Polar Double Integral?
In mathematics, a polar double integral extends the concept of single integrals to two dimensions using polar coordinates. It's used to calculate areas, volumes, and other quantities over regions defined in polar coordinates.
The integral is expressed as:
∫∫R f(r,θ) r dr dθ
where:
- f(r,θ) is the integrand function
- r is the radial coordinate
- θ is the angular coordinate
- R is the region of integration
Formula
The polar double integral formula is:
∫αβ ∫a(θ)b(θ) f(r,θ) r dr dθ
This represents the integral of f(r,θ) over a region bounded by:
- Angular limits α and β
- Radial limits a(θ) and b(θ)
Note: The factor r in the integrand accounts for the increasing area of polar coordinate "rectangles" as r increases.
How to Use the Calculator
- Enter the integrand function f(r,θ)
- Specify the angular limits (α and β)
- Enter the radial limits (a(θ) and b(θ))
- Click "Calculate" to compute the integral
The calculator will display the result and generate a visualization of the region and function.
Worked Example
Calculate the integral of f(r,θ) = r over the region where 0 ≤ θ ≤ π/2 and 0 ≤ r ≤ 1.
∫0π/2 ∫01 r * r dr dθ = ∫0π/2 ∫01 r² dr dθ
First compute the inner integral:
∫01 r² dr = [r³/3]₀¹ = 1/3
Then compute the outer integral:
∫0π/2 (1/3) dθ = (1/3)(π/2 - 0) = π/6
The result is π/6.
Applications
Polar double integrals are used in various fields including:
- Physics for calculating moments of inertia
- Engineering for analyzing stress distributions
- Computer graphics for rendering shapes
- Probability for calculating expected values
| Application | Description |
|---|---|
| Physics | Calculating moments of inertia and center of mass |
| Engineering | Analyzing stress distributions in materials |
| Computer Graphics | Rendering shapes and surfaces |
| Probability | Calculating expected values in probability distributions |