A scientific computing environment for differential field simulation
This paper deals with the development of a scientific computing environment for differential field simulation. We mean a modelling and simulation environment based on partial differential equations and their numerical solution as powerful and widely used techniques for mathematical and computational investigation of application problems. We have been developing grid generation algorithms, numerical solvers of PDE systems, along with advanced visualization techniques, to numerically compute and evaluate field variables by exploiting user-friendly interaction. In this paper, we model the complete cycle of the visual computational simulation as reference framework and we illustrate advances in the environment development. We describe a few computational components by focusing on two fundamental substeps often concurring to simulation processes, the image segmentation and grid generation. We introduce differential equation systems, developed combination of computational methods and recent algorithmic advances. A few application results are detailed, and shown by figures, for segmentation test problems. (C) 2003 IMACS. Published by Elsevier Science B.V. All rights reserved.
grid generation image segmentation differential simulation finite difference approximation multigrid computation