How can the stability of this numerical method be proven?

In summary, the conversation is about seeking help with a stability proof for a numerical method involving the equation u'(t)=u^2. The notation and equations used are confusing and do not make sense, but it involves calculating the product of iterations (u^{n+1})*(u^n). The speaker is struggling and asks for assistance.
  • #1
juaninf
27
0
Please anyone help me with stability proof this next numerical method [tex]\dfrac{u^{n+1} - u^{n}}{\vartriangle t} = (u^{n+1}u^n)[/tex]I am trying make :

[tex]
\begin{equation*}
\begin{split}
u_2^{n+1} - u_1^{n+1} & = \displaystyle\frac{u_2^{n}}{1-\vartriangle tu_2^{n}} - \displaystyle\frac{u_1^{n}}{1-\vartriangle tu_1^{n}} \\
& = \displaystyle\frac{u_2^{n}-u_1^{n}}{(1-\vartriangle tu_1^{n})(1-\vartriangle tu_2^{n})}\\
& \geq{\displaystyle\frac{u_2^{n}-u_1^{n}}{e^{-\vartriangle t(u_2^{n}+u_1^{n})}}}\\
\end{split}
\end{equation*}
[/tex]

but I not have more idea :( please help me
 
Last edited:
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  • #2
Your notation is confusing. I don't know what the right side of your first equation is supposed to mean.
 
  • #3
product [tex]
\dfrac{u^{n+1} - u^{n}}{\vartriangle t} = (u^{n+1}u^n)
[/tex] this numerical method is from [tex]u'(t)=u^2[/tex]
 
  • #4
I don't know what (un+1un) is supposed to mean!
 
  • #5
is product of iterations [tex](u^{n+1})*(u^n)[/tex]
 
Last edited:
  • #6
On the face of it the first equation doesn't make any sense. Dimensionally, it looks completely wrong.
 

FAQ: How can the stability of this numerical method be proven?

What are numerical methods used for?

Numerical methods are used to solve mathematical problems that cannot be solved analytically. They involve using algorithms and computer programs to approximate the solution to a mathematical problem.

What is the difference between analytical and numerical methods?

Analytical methods involve solving mathematical problems using algebraic and calculus techniques to find an exact solution. Numerical methods, on the other hand, use algorithms and approximations to find an approximate solution.

How accurate are numerical methods?

The accuracy of numerical methods depends on the method used and the precision of the input data. Some methods, such as the Taylor series method, can provide very accurate results. However, as with all approximations, there is always some degree of error involved.

What are some common numerical methods?

Some common numerical methods include the Newton-Raphson method for finding roots of equations, the Euler and Runge-Kutta methods for solving differential equations, and the Simpson's rule for numerical integration.

How are numerical methods validated?

Numerical methods are validated by comparing the results obtained from the method with known analytical solutions or experimental data. They can also be tested for convergence, stability, and consistency, to ensure that they provide accurate and reliable results.

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