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Numerical solutions of ODEs using modified Euler method - CSIR-NET Mathematical Sciences | Mathematics for IIT JAM, GATE, CSIR NET, UGC NET PDF Download

Modified Euler's Method :

The Euler forward scheme may be very easy to implement but it can't give accurate solutions. A  very small step size is required for any meaningful result.  In this scheme, since, the starting point of each sub-interval is used to find the slope of the solution curve,  the solution would be correct only if the function is linear. So an improvement over this is to take the arithmetic average of the slopes at xi  and xi+1(that is, at the end points of each sub-interval). The scheme so obtained is called modified Euler's method. It works first by approximating a value to yi+1 and then improving it by making use of average slope. 

yi+1 = yi+ h/2 (y'i + y'i+1)

= yi + h/2(f(xi, yi) + f(xi+1, yi+1))

If Euler's method is used to find the first approximation of yi+1 then 

yi+1 = yi + 0.5h(fi  + f(xi+1, y+ hfi))

Truncation error:

fi+1 = y'i+1  y'i + h y'' + h2yi'''' /2  + h3yiiv /3! + h4yiv /4! + . . .

By substituting these expansions in the Modified Euler formula gives

yi + h y' + h2yi'' /2  + h3yi''' /3! + h4yiiv /4! + . . . = yi+ h/2 (y'i + y'i + h y''h2yi'''' /2  + h3yiiv /3! + h4yiv /4! + . . . )

So the truncation error is: - h3yi''' /12 - h4yiiv /24 + . . .  that is, Modified Euler's method is of order two. 

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FAQs on Numerical solutions of ODEs using modified Euler method - CSIR-NET Mathematical Sciences - Mathematics for IIT JAM, GATE, CSIR NET, UGC NET

1. What is the modified Euler method for solving ODEs?
Ans. The modified Euler method, also known as the improved Euler method or Heun's method, is a numerical technique used to approximate the solutions of ordinary differential equations (ODEs). It is an extension of the Euler method and provides better accuracy by using a midpoint approximation in the calculation of the derivative.
2. How does the modified Euler method work?
Ans. The modified Euler method involves dividing the interval of interest into smaller subintervals and approximating the solution at each subinterval. It starts by taking an initial value and then using this value to estimate the slope at the beginning of the interval. Next, it uses this slope to predict the value at the midpoint of the interval. Finally, it uses this predicted value to estimate the slope at the midpoint, which is then used to update the initial value. This process is repeated iteratively until the desired accuracy is achieved.
3. What are the advantages of using the modified Euler method over the Euler method?
Ans. The modified Euler method offers improved accuracy compared to the Euler method. By incorporating a midpoint approximation, it reduces the error associated with the linear approximation used in the Euler method. This makes it more suitable for solving ODEs with non-linear or rapidly changing solutions. Additionally, the modified Euler method is still relatively simple to implement and computationally efficient.
4. Are there any limitations of the modified Euler method?
Ans. While the modified Euler method provides better accuracy than the Euler method, it is still a first-order numerical method. This means that it may not be able to accurately capture complex or rapidly changing solutions. It is also sensitive to the step size used in the approximation, and a very small step size may be required to achieve the desired accuracy. Additionally, the modified Euler method may not work well for stiff ODEs, which are ODEs with widely varying time scales.
5. Are there any alternative numerical methods for solving ODEs?
Ans. Yes, there are several alternative numerical methods for solving ODEs, depending on the specific requirements and properties of the ODE. Some commonly used methods include the Runge-Kutta methods (such as the classical fourth-order Runge-Kutta method), the Adams-Bashforth methods, the backward differentiation formulas, and the finite difference methods. Each method has its own advantages and limitations, and the choice of method depends on factors such as the order of accuracy desired, computational efficiency, and stability requirements.
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