Differential Equation Calculator Step by Step

Euler's Method Differential Equation Approximator

Use this calculator to approximate the solution of a first-order ordinary differential equation (ODE) of the form dy/dx = A*x + B*y + C using Euler's Method.

Approximation Steps:

Enter values and click 'Calculate Approximation' to see the steps.

Understanding Euler's Method for Differential Equations

Differential equations are mathematical equations that relate a function with its derivatives. They are fundamental in modeling various phenomena in science, engineering, economics, and many other fields. Often, finding an exact analytical solution to a differential equation can be challenging or even impossible. In such cases, numerical methods provide a powerful way to approximate the solution.

What is Euler's Method?

Euler's Method is one of the simplest and most intuitive numerical methods for approximating the solution of a first-order ordinary differential equation (ODE) with a given initial value. A first-order ODE can be expressed in the form dy/dx = f(x, y), where f(x, y) is a function of x and y, and we are given an initial condition y(x₀) = y₀.

The core idea behind Euler's Method is to use the tangent line at the current point (x_n, y_n) to estimate the value of the function at the next point (x_{n+1}, y_{n+1}). The slope of the tangent line at (x_n, y_n) is given by f(x_n, y_n) (which is dy/dx at that point).

The Formula

The iterative formula for Euler's Method is:

yn+1 = yn + h * f(xn, yn)

where:

  • yn+1 is the approximated y-value at the next step.
  • yn is the current approximated y-value.
  • h is the step size (Δx), a small increment in x.
  • f(xn, yn) is the value of the derivative dy/dx at the current point (xn, yn).

The next x-value is simply xn+1 = xn + h.

How This Calculator Works

This calculator specifically approximates solutions for ODEs of the form dy/dx = A*x + B*y + C. You provide the coefficients A, B, and C, along with an initial condition (x₀, y₀), a step size h, and the desired number of steps. The calculator then iteratively applies Euler's Method, showing you the values of xn, yn, f(xn, yn), the change in y (h * f(xn, yn)), and the new yn+1 for each step.

Inputs Explained:

  • Coefficient A, B, C: These define the specific form of your differential equation dy/dx = A*x + B*y + C.
  • Initial x (x₀): The starting x-value for your approximation.
  • Initial y (y₀): The starting y-value corresponding to x₀ (your initial condition).
  • Step Size (h): The increment by which x changes in each step. Smaller step sizes generally lead to more accurate approximations but require more steps.
  • Number of Steps: How many iterations of Euler's Method you want to perform.

Limitations of Euler's Method

While simple, Euler's Method is a first-order method, meaning its accuracy is directly proportional to the step size h. Smaller step sizes yield better accuracy but increase computational effort. For more complex or highly accurate approximations, higher-order methods like Runge-Kutta methods are often preferred.

Example Calculation:

Let's approximate the solution to dy/dx = 0.1x + 0.5y + 1 with initial condition y(0) = 1, a step size h = 0.1, for 2 steps.

Given: A=0.1, B=0.5, C=1, x₀=0, y₀=1, h=0.1

Step 1: (n=0)

  • x₀ = 0
  • y₀ = 1
  • f(x₀, y₀) = A*x₀ + B*y₀ + C = 0.1*(0) + 0.5*(1) + 1 = 0 + 0.5 + 1 = 1.5
  • Δy = h * f(x₀, y₀) = 0.1 * 1.5 = 0.15
  • y₁ = y₀ + Δy = 1 + 0.15 = 1.15
  • x₁ = x₀ + h = 0 + 0.1 = 0.1

Step 2: (n=1)

  • x₁ = 0.1
  • y₁ = 1.15
  • f(x₁, y₁) = A*x₁ + B*y₁ + C = 0.1*(0.1) + 0.5*(1.15) + 1 = 0.01 + 0.575 + 1 = 1.585
  • Δy = h * f(x₁, y₁) = 0.1 * 1.585 = 0.1585
  • y₂ = y₁ + Δy = 1.15 + 0.1585 = 1.3085
  • x₂ = x₁ + h = 0.1 + 0.1 = 0.2

The calculator will display these steps in a clear table format.

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Step (n)xnynf(xn, yn)h * f(xn, yn) (Δy)yn+1
" + i + "" + currentX.toFixed(6) + "" + currentY.toFixed(6) + "" + fx_y.toFixed(6) + "" + deltaY.toFixed(6) + "" + nextY.toFixed(6) + "
"; resultDiv.innerHTML = tableHTML; }

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