Title :
Evolution of mesh refinement rules for impact dynamics
Author :
Howard, Daniel ; Roberts, Simon C.
Author_Institution :
Software Evolution Centre, Defence Evaluation & Res. Agency, Malvern, UK
Abstract :
Genetic programming (GP) was used in an experiment to investigate the possibility of learning rules that trigger adaptive mesh refinement. GP detected mesh cells that required refinement by evolving a formula involving cell quantities such as material densities. Various cell variable combinations were investigated in order to identify the optimal ones for indicating mesh refinement. The problem studied was the high speed impact of a spherical ball on a metal plate
Keywords :
evolutionary computation; impact (mechanical); learning (artificial intelligence); mechanical engineering computing; partial differential equations; adaptive mesh refinement; genetic programming; high speed impact; impact dynamics; material densities; mesh cells; mesh refinement rule evolution; metal plate; rule learning; spherical ball; Adaptive mesh refinement; Equations; Genetic engineering; Genetic programming; Moment methods; Physics computing; Software systems; Structural engineering; Systems engineering and theory; Testing;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870801
