# Simulation of Laplace Equation in 3-D with mixed BC of Dirichlet-Neumann

I am simulating a Mixed-Boundary value (Dirichlet-Neumann) problem using Finite Difference Method on a unit 3-D cube such that the left, lower, and front plane have $u=u(x,y,z)=1$ (Dirichlet) and right, upper and back plane have $\frac{\partial u}{\partial n}=0$. I know that the true solution is $1$ everywhere and hence I have used the stopping condition as $err_\max < 0.00001$ where I find error like $err = 1.0 - u_\text{current}$. The problem converges when input is $16\times16\times16$ and $32\times32\times32$ but when input is $64\times64\times64$, the maximum error does not decrease below $0.000019$. Similarly when the problem size is $128\times128\times128$, the error does not decrease below $0.000040$. My question is : Is this an expected behaviour ?

• What about round-off error? Is it possible for $h \le 1/64$ he's representing the derivative of his constant solution well in exact arithmetic but is more susceptible to round-off error (e.g. cs.cornell.edu/~bindel/class/cs3220-s12/notes/lec22.pdf)? May 8 '15 at 14:10
• Round-off is, in double precision, no longer a concern today. It happens when you reach a level of $10^{-12}$ or so on your overall error norm, at which point you don't care any more about round-off. That's definitely not @gaurav's problem. May 8 '15 at 16:11
• @WolfgangBangerth thank you for answering, I changed a few conditions and ran the program, it stopped again at 0.000019 for 64x64x64 when I use float but converges when I use double. I think it had both the issues (1) Logical errors for Neumann condition and (2) Floating point round-off error. Thanks @Sumedh and @nicoguaro. May 9 '15 at 3:14
• But I still have my doubts as to why the same problem is not working with float data type ! May 9 '15 at 15:13