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Carry out one step of the Euler method and of the improved Euler method using the step size \(h=0.1 .\) Suppose that a local truncation error no greater than 0.0025 is required. Estimate the step size that is needed for the Euler method to satisfy this requirement at the first step. $$ y^{\prime}=\left(y^{2}+2 t y\right) /\left(3+t^{2}\right), \quad y(0)=0.5 $$

Short Answer

Expert verified
Using the Euler method, the first step approximation for the given differential equation is approximately y₁ ≈ 0.5083. For the Improved Euler method, the first step approximation is y₁ ≈ 0.5084. To achieve a local truncation error no greater than 0.0025, the step size required for the Euler method is approximately h ≈ 0.023.

Step by step solution

01

(1) Euler Method - First Step

Start with the differential equation \(y'(t) = \frac{y^2 + 2ty}{3+t^2}\), and apply the Euler method: $$y_{n+1} = y_n + hf(t_n, y_n),$$ where h = 0.1, \(f(t_n, y_n)\) is the value of the differential equation at the point \((t_n, y_n)\), and \((t_0, y_0) = (0, 0.5)\). First, calculate the value of the differential equation at the initial point, \(f(t_0, y_0) = f(0, 0.5) = \frac{(0.5)^2 + 2(0)(0.5)}{3 + (0)^2} = \frac{0.25}{3}\). Next, apply the Euler method with h = 0.1: $$y_1 = y_0 + 0.1\cdot f(t_0, y_0) = 0.5 + 0.1\cdot \frac{0.25}{3} \approx 0.5083.$$
02

(2) Improved Euler Method - First Step

Now, apply the Improved Euler method (also known as Heun's method). The formula for the improved Euler method is: $$y_{n+1} = y_n + \frac{h}{2}\left( f(t_n, y_n) + f(t_{n+1}, y_n+hf(t_n, y_n)) \right).$$ Use the previous result, \(f(t_0, y_0) = \frac{0.25}{3}\), and calculate \(f(t_1, y_1) = f(0.1, 0.5083) \approx \frac{(0.5083)^2 + 2(0.1)(0.5083)}{3 + (0.1)^2}\). Finally, apply the Improved Euler Method: $$y_1 \approx 0.5 + \frac{0.1}{2}\left( \frac{0.25}{3} \right) \approx 0.5084$$.
03

(3) Determine step size for required local truncation error

A local truncation error no greater than 0.0025 is required. The local truncation error for the Euler method can be estimated as: $$\text{Local Truncation Error} \approx \frac{hL}{2}|y(t_1) - y_0|,$$ where L is the Lipschitz constant. First, we need to find L. To do so, compute the partial derivative of the differential equation with respect to y: $$\frac{\partial f}{\partial y} = \frac{2y (3 + t^2) - 2yt (y^2 + 2ty)}{(3+t^2)^2}$$. Notice that the maximum value of the denominator occurs when t = 0, that is: $$(3+t^2)^2 \geq 3^2 = 9$$. Now, we estimate the maximum value of the numerator. Since \(y_0 = 0.5\), \(t=0\), we can find it as follows: $$\max_{0\leq y \leq y_1} |2y (3 + t^2) - 2yt (y^2 + 2ty)| \leq |2y_1 (3 + 0) - 2y_1^2|$$. So, we can estimate L as: $$L \leq \frac{|2y_1 (3) - 2y_1^2|}{9}$$. Now, plug L into the formula for the local truncation error and solve for h: $$0.0025 \geq \frac{hL}{2}|y_1 - y_0| \Rightarrow h \leq \frac{0.005}{L|y_1-y_0|}$$. Use the previous result and plug in the estimated L to find the appropriate step size h: $$h \leq \frac{0.005}{\frac{|2y_1 (3) - 2y_1^2|}{9}|y_1-y_0|} \approx 0.023$$. As such, the step size required to satisfy the local truncation error requirement is approximately h ≈ 0.023.

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Most popular questions from this chapter

Carry out one step of the Euler method and of the improved Euler method using the step size \(h=0.1 .\) Suppose that a local truncation error no greater than 0.0025 is required. Estimate the step size that is needed for the Euler method to satisfy this requirement at the first step. $$ y^{\prime}=\sqrt{t+y}, \quad y(0)=3 $$

In each of Problems 1 through 6 find approximate values of the solution of the given initial value problem at \(t=0.1,0.2,0.3,\) and \(0.4 .\) Compare the results with those obtained by using other methods and with the exact solution (if available). (a) Use the Runge-Kutta method with \(h=0.1\) (b) Use the Runge-Kutta method with \(h=0.05\) $$ y^{\prime}=\left(t^{2}-y^{2}\right) \sin y, \quad y(0)=-1 $$

Consider the initial value problem \(x^{\prime}=f(t, x, y)\) and \(y^{\prime}=g(t, x, y)\) with \(x\left(t_{0}\right)=x_{0}\) and \(y\left(t_{0}\right)=y_{0} .\) The generalization of the Adams-Moulton predictor-corrector method of Section 8.4 is $$ \begin{array}{l}{x_{n+1}=x_{n}+\frac{1}{24} h\left(55 f_{n}-59 f_{n-1}+37 f_{n-2}-9 f_{n-3}\right)} \\ {y_{n+1}=y_{n}+\frac{1}{24} h\left(55 g_{n}-59 g_{n-1}+37 g_{n-2}-9 g_{n-1}\right)}\end{array} $$ and $$ \begin{array}{l}{x_{n+1}=x_{n}+\frac{1}{24} h\left(9 f_{n+1}+19 f_{n}-5 f_{n-1}+f_{n-2}\right)} \\ {y_{n+1}=y_{n}+\frac{1}{24} h\left(9 g_{n+1}+19 g_{n}-5 g_{n-1}+g_{n-2}\right)}\end{array} $$ Determine an approximate value of the solution at \(t=0.4\) for the example initial value problem \(x^{\prime}=x-4 y, y^{\prime}=-x+y\) with \(x(0)=1, y(0)=0\). Take \(h=0.1 .\) Correct the predicted value once. For the values of \(x_{1}, \ldots, y_{3}\) use the values of the exact solution rounded to six digits: \(x_{1}=1.12883, x_{2}=1.32042, x_{3}=1.60021, y_{1}=-0.110527, y_{2}=\) \(-0.250847,\) and \(y_{3}=-0.429696\)

Consider the initial value problem $$ y^{\prime}=-10 y+2.5 t^{2}+0.5 t, \quad y(0)=4 $$ (a) Find the solution \(y=\phi(t)\) and draw its graph for \(0 \leq t \leq 5\). (b) The stability analysis in the text suggests that for this problem the Euler method is stable only for \(h<0.2 .\) Confirm that this is true by applying the Euler method to this problem for \(0 \leq t \leq 5\) with step sizes near \(0.2 .\) (c) Apply the Runge-Kutta method to this problem for \(0 \leq t \leq 5\) with various step sizes. What can you conclude about the stability of this method? (d) Apply the backward Euler method to this problem for \(0 \leq t \leq 5\) with various step sizes. What step size is needed in order that the error at \(t=5\) is less than \(0.01 ?\)

(a) Find a formula for the solution of the initial value problem, and note that it is independent of \(\lambda\). (b) Use the Runge-Kuta method with \(h=0.01\) to compute approximate values of the solution for \(0 \leq t \leq 1\) for various values of \(\lambda\) such as \(\lambda=1,10,20,\) and 50 , and 50 , inters of the (c) Explain the differences, if any, between the exact solution and the numerical approximations. \(y^{\prime}-\lambda y=1-\lambda t, \quad y(0)=0\)

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