DocumentCode
356955
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
Volume
2
fYear
2000
fDate
2000
Firstpage
1297
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location
La Jolla, CA
Print_ISBN
0-7803-6375-2
Type
conf
DOI
10.1109/CEC.2000.870801
Filename
870801
Link To Document