Improving Euler's Approximation for Differential Equations: Tips and Resources

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Discussion Overview

The discussion focuses on improving Euler's approximation methods for solving differential equations, including the improved Euler method, also known as Heun's method. Participants explore various aspects of these methods, their applications, and the nuances of their mathematical formulations.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants mention the "improved Euler method" as a predictor-corrector approach to enhance the accuracy of Euler's method.
  • One participant explains the steps involved in the improved Euler method, including the predictor and corrector phases, and discusses the significance of slopes at different points.
  • There is a discussion about notation, particularly regarding the representation of derivatives and the meaning of the vertical line in expressions.
  • Another participant inquires about the applications of Euler and improved Euler methods beyond solving differential equations, seeking to understand their broader utility.
  • One participant notes that these methods are particularly useful for initial value problems and highlights their role in computational fluid dynamics, especially concerning the Navier-Stokes equations.
  • There is mention of the limitations of Euler methods compared to higher-order methods like the 4th-order Runge-Kutta method, which are noted to be more accurate.
  • A later reply introduces a mathematical expression related to fluid mechanics, discussing the stress tensor and its dependence on various factors, including viscosity.
  • Participants share resources, including PDF documents, for further study on the topic.

Areas of Agreement / Disagreement

Participants express varying levels of familiarity with the topic, and while some agree on the basic principles of the improved Euler method, there is no consensus on its applications or the relative accuracy of different numerical methods. The discussion remains unresolved regarding the broader implications and uses of these methods.

Contextual Notes

Some participants express uncertainty about specific mathematical notations and their implications. The discussion includes assumptions about the applicability of methods to different types of differential equations and the conditions under which they are used.

Who May Find This Useful

This discussion may be useful for students and professionals interested in numerical methods for differential equations, particularly in fields such as engineering and computational fluid dynamics.

Pattielli
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Would you please tell me how to improve Euler's approximation to be better in solving differerential equations ? Can you give me some links to this?

Thank you,
 
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It is literally called the "improved Euler method," the "improved Euler-Cauchy method," or sometimes "Heun's method." It's known as a predictor-corrector method.

I assume you are familiar with the regular Euler method. Recall for Euler's method we are given:

[tex]y'=f(x,y)[/tex]
[tex]y(x_0)=y_0[/tex]

The function [itex]f(x,y)[/itex] tells us the slope of the function at every point, important for 'shooting' from station to station (point to point).

The first step in the improved Euler method is the "predictor" step, and it's identical to the regular Euler method:

[tex]y^\ast_{n+1}=y_n+hf(x_n,y_n)[/tex]

h is the step size. The asterisk denotes the prediction of [itex]y_{n+1}[/itex]. With this prediction, we have two slopes to consider in 'shooting' toward the next station. First is the slope of the current station we used previously:

[tex]y'|_n=f(x_n,y_n)[/tex]

And then the slope at the predicted point:

[tex]y'|_{n+1}=f(x_{n+1},y^\ast_{n+1})[/tex]

We can "correct" our aim by averaging these two slopes and using that as our slope to find the next point:

[tex]y_{n+1}=y_n+\frac{1}{2}h[f(x_n,y_n)+f(x_{n+1},y^\ast_{n+1})][/tex]

There you have it.
 
I'm a little slack on differential equations, so perhaps you can shed some light. On the RHS, what's that line?
 
Thank you,

Chrono, what is RHS ?
 
RHS = right hand side

I don't see anything funky on the right hand side. Do you mean this:

[tex]y'|_{n+1}[/tex]

If so, the vertical line doesn't really mean anything other than y' evaluated at n+1. It's a notation quirk I picked, I'm not sure if it's exactly correct.
 
TALewis said:
RHS = right hand side

I don't see anything funky on the right hand side. Do you mean this:

[tex]y'|_{n+1}[/tex]

If so, the vertical line doesn't really mean anything other than y' evaluated at n+1. It's a notation quirk I picked, I'm not sure if it's exactly correct.

That's what I mean. That's the left hand side, isn't it? I don't know what I was thinking when I said that. So would it mean the same without the line there?
 
The line doesn't really mean anything here. It's just how I chose to say "the slope at this station" and "the slope at the next station." Here's another example of the notation:

[tex]\tau_w = \left.\mu\frac{du}{dy}\right|_{y=0}[/tex]

This, from fluid mechanics, says the shear stress caused by a fluid at a wall ([itex]\tau_w[/itex]) is equal to the fluid's dynamic viscosity ([itex]\mu[/itex]) times the derivative of the fluid velocity parallel to the wall (u) with respect to the perpendicular distance from the wall (y), evaluated at the wall ( y = 0 ).
 
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I would like to have three other questions...Please help.
Would you please tell me about Euler and improved Euler methods' applications ?
How can they be in use for what purpose but just solve the differential equations ? An even when they are used for their main purpose, what do people want to learn from their approximations ?

Thank you very much
 
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The Euler and improved Euler can be used to find approximate numerical solutions to differential equations of the form

[tex]y'=f(x,y)[/tex]

where the initiial point of the function is given. That is to say, it is applicable to initial value problems (although it can be applied to boundary value problems through a shooting method). I'm not sure about applications of the method to problems not related to this differential equation.

In practice, we would use a numerical method like the improved Euler method to solve a differential equation where no analytical solution exists. That is to say, there are only a handful of differential equations that can be solved through calculus and algebraic manipulation to give a closed form result.

For example, the field of computational fluid dynamics (CFD) is concerned in part with numerical solutions to the Navier-Stokes equations, which govern fluid flow. The Navier-Stokes equations are a system of nonlinear, second order, partial differential equations with variable coefficients. Here is the NS equation for the x-direction:

[tex] \begin{align*}<br /> \rho\left(\frac{\partial u}{\partial t} + u\frac{\partial u}{\partial x} + v\frac{\partial u}{\partial y} + w\frac{\partial u}{\partial z}\right) =\\<br /> -\frac{\partial p}{\partial x} + \rho g_x + \mu\left(\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} + \frac{\partial^2 u}{\partial z^2}\right)<br /> \end{align}[/tex]

There are few analytical solutions to these Navier-Stokes equations. They must be solved by numerical methods in most cases.

In the case of a differential equation that cannot be solved "by hand," the numerical solution produced by method such as Euler's can provide as much information to an engineer as an exact solution. I can plot a numerical solution, numerically differentiate or integrate it, to a degree of numerical precision limited only by my time and computing power.

In practice, however, the Euler and improved Euler are not as accurate as the 4th-order Runge-Kutta method, which is another predictor-corrector "marching" method that's used more often with better results.
 
  • #10
Just a minor comment here regarding variable coefficients:
Under the assomption of small deformation rates, incompressibility of the fluid, and the validity of Newton's stress/strain rate relationship, it is quite common to express the
stress tensor P as
[tex]P=-pI+\mu(\nabla{\vec{v}}+(\nabla{\vec{v}})^{T})[/tex]

where p is the pressure, [tex]\mu[/tex] the possibly variable dynamic viscosity coefficient, whereas [tex]\vec{v}[/tex] (I is the identity matrix).
In the case of a constant viscosity coefficient, the momentum equation gains the form
indicated by TALewis, in general however, we'll have the force per unit volume terms:
[tex]-\nabla{p}+\nabla\cdot(\mu(\nabla{\vec{v}}+(\nabla{\vec{v}})^{T}))[/tex]
 
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  • #11
Thank you very much, :sm:
 
  • #12
hi
i am studying this stuff at the moment and have some very useful pdf documents explaining this stuff.
let me know if you are interested and i will send you a copy
 
  • #13
Okay, I am waiting for a copy from you
Thank you very much in advance,
 

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