TY - JOUR
T1 - Reconstruction of periodic unit cells of multimodal random particulate composites using genetic algorithms
AU - Kumar, Natarajan Chennimalai
AU - Matouš, Karel
AU - Geubelle, Philippe H.
N1 - Funding Information:
The authors would like to gratefully acknowledge the support from ATK/Thiokol (ATK-21316), with J. Thompson and Dr. I.L. Davis serving as program monitors, and from the Center for Simulation of Advanced Rockets (CSAR) under contract number B523819 by the U.S. Department of Energy as a part of its Advanced Simulation and Computing (ASC) program. We would also like to thank Dr. T.L. Jackson and his team for providing Rocpack and for helpful discussions.
PY - 2008/4
Y1 - 2008/4
N2 - We develop a procedure for characterization and reconstruction of periodic unit cells of highly filled, multimodal, particulate composites. Rocpack, a particle packing software, is used to generate the solid propellant microstructures and one- and two-point probability functions are used to describe its statistical morphology. The reconstruction is carried out using a parallel Augmented Simulated Annealing algorithm with a novel mutation operator based on a mass-spring system to eliminate overlap and improve the code performance. Results from the reconstruction procedure, for four-phase random particulate composites of 40-70% packing fraction, are detailed to demonstrate the capabilities of the reconstruction model. The presented results suggest good convergence and repeatability of the optimization scheme, even for high volume fractions, and good scalability of the algorithm.
AB - We develop a procedure for characterization and reconstruction of periodic unit cells of highly filled, multimodal, particulate composites. Rocpack, a particle packing software, is used to generate the solid propellant microstructures and one- and two-point probability functions are used to describe its statistical morphology. The reconstruction is carried out using a parallel Augmented Simulated Annealing algorithm with a novel mutation operator based on a mass-spring system to eliminate overlap and improve the code performance. Results from the reconstruction procedure, for four-phase random particulate composites of 40-70% packing fraction, are detailed to demonstrate the capabilities of the reconstruction model. The presented results suggest good convergence and repeatability of the optimization scheme, even for high volume fractions, and good scalability of the algorithm.
KW - Microstructure reconstruction
KW - Parallel genetic algorithm
KW - Particle packing
KW - Probability functions
KW - Solid propellant
UR - http://www.scopus.com/inward/record.url?scp=40449142607&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=40449142607&partnerID=8YFLogxK
U2 - 10.1016/j.commatsci.2007.07.043
DO - 10.1016/j.commatsci.2007.07.043
M3 - Article
AN - SCOPUS:40449142607
VL - 42
SP - 352
EP - 367
JO - Computational Materials Science
JF - Computational Materials Science
SN - 0927-0256
IS - 2
ER -