Most models converge more reliably with relative tolerances, which is the default in AFT Impulse’s Tolerance Panel. But some models converge much better with absolute tolerance. This usually means that there is at least one element of the model that is close to the real answer in absolute terms but does not lock in on a relative (percentage) basis.

If a model will not converge with relative tolerance, you can try changing to absolute tolerance. Even better, try the option to converge on either absolute or relative, which will offer the most flexibility.

Related Blogs

Having model convergence problems? Start here!