2020/03/02 by V. V. Grigoriev, Vasiliy V. Grigoriev, Oleg Iliev +4
Computer Science · Engineering · Environmental Science · #65M32 #76D05 #76R50 #76S05 #86A22 #Advanced Mathematical Modeling in Engineering #Advanced Numerical Methods in Computational Mathematics #Computational Engineering #FOS: Computer and information sciences #Finance #Groundwater flow and contamination studies #Heat Transfer and Optimization #Lattice Boltzmann Simulation Studies #and Science (cs.CE) #cs.CE #msc:65M32 #msc:76D05 #msc:76R50 #msc:76S05 #msc:86A22
paper · pdf · doi:10.48550/arxiv.2003.02653
28 pages, 27 figures. arXiv admin note: substantial text overlap with arXiv:1912.03889
arxiv created 2020/03/02 · openalex publication_date 2020/03/02 · arxiv updated 2020/03/06 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
This paper discusses an optimization method called Modified Bee Colony algorithm (MBC) based on a particular intelligent behavior of honeybee swarms. The algorithm was checked in a few benchmarks like Shekel, Rozenbroke, Himmelblau and Rastrigin functions, then was applied to parameter identification for reactive flow problems in periodic porous media. The simulation results show that the performance and efficiency of MBC algorithm are comparable to the other parameter identification methods and strategies, at the same time it is able to better capture local minima for the considered class of problems. The proposed identification approach is applicable for different geometries (random and periodic) and for a range of process parameters. In this paper the potential of the approach is demonstrated in identifying parameters of Langmuir isotherm for low Peclet and high Damkoler numbers reactive flow in a 2D periodic porous media with circular inclusions. Finite element approximation in space and implicit time discretization are exploited.