Title :
A density driven mesh generator guided by a neural network
Author :
Lowther, D.A. ; Dyck, D.N.
Author_Institution :
Dept. of Electr. Eng., McGill Univ., Montreal, Que., Canada
fDate :
3/1/1993 12:00:00 AM
Abstract :
A neural network guided mesh generator is described. The mesh generator uses density information provided by the neural network to determine the size and placement of elements. This system is coupled with an adaptive meshing and solving process, and is shown to have major computational benefits compared with adaptation alone. The novel mesh generator is faster than conventional meshing approaches and allows the solver to take fewer adaptive steps in generating an optimum solution. It provides a method of hiding the meshing process from the user in a totally automatic system
Keywords :
finite element analysis; learning (artificial intelligence); neural nets; adaptive meshing; density driven mesh generator; density information; neural network; optimum solution; solving process; totally automatic system; Control systems; Design engineering; Design methodology; Error correction; Finite element methods; Geometry; Learning systems; Mesh generation; Neural networks; Solid modeling;
Journal_Title :
Magnetics, IEEE Transactions on