DocumentCode :
185335
Title :
Hybrid MPI-OpenMP parallel optimization for thermo-fluid problems
Author :
Depolli, M.
Author_Institution :
Dept. of Commun. Syst., Jozef Stefan Inst., Ljubljana, Slovenia
fYear :
2014
fDate :
26-30 May 2014
Firstpage :
367
Lastpage :
372
Abstract :
This article deals with the minimization of the energy transport through the isolated enclosure by means of obstructing the fluid flow. The differentially heated cavity is partially covered with non-permeable obstacles that affect the natural convection flow. We seek the optimal position and shape of the obstacles to minimize the heat flux through the domain with the minimal cumulative size of the obstacles, i.e. we maximize insulation with minimal material needed. The task is performed by evolutionary multi-objective optimization of a local thermo-fluid solver, which comprises energy transport and incompressible fluid dynamics. An effective parallel algorithm is presented, in which the physical model is solved by a local meshless numerical method on shared memory architecture, coupled by optimization algorithm that exploits the distributed computer parallelism.
Keywords :
computational fluid dynamics; evolutionary computation; mechanical engineering computing; message passing; minimisation; natural convection; distributed computer parallelism; energy transport; evolutionary multiobjective optimization; heat flux; heated cavity; hybrid MPI-OpenMP parallel optimization; incompressible fluid dynamics; local meshless numerical method; local thermo-fluid solver; minimization; natural convection flow; shared memory architecture; thermo-fluid problem; Computational modeling; Computers; Convergence; Heating; Optimization; Sociology; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on
Conference_Location :
Opatija
Print_ISBN :
978-953-233-081-6
Type :
conf
DOI :
10.1109/MIPRO.2014.6859592
Filename :
6859592
Link To Document :
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