Curso OpenFOAM: Introdução I

Curso apresentado como parte de disciplina SME0255 - Simulação Computacional de Fluidos - Instituto de Ciências Matemáticas e de Computação - Universidade de São Paulo

Instrutor: Jonas Laerte Ansoni
Idioma de aplicação: Português
Duração:

Tópicos:

Material:

Slides utilizados nas aulas não serão disponibilizados para download.
Casos específicos de exemplos de aplicação e materiais adicionais serão disponibilizados.

Referências de material OpenFOAM:
Joel Guerreo's OpenFOAM material (University of Genova):
http://www.dicat.unige.it/guerrero/openfoam.html

Material de apoio:
Linux: http://linuxcommand.org/
Linux commands list pdf: Download
Useful alias definitions: Download

PyFoam Download

VirtualBox image file curso difusão ICMC (Lubuntu + OF2.3.1 + pyFoam) 1,8GB
md5sum: 8b090c95c5e05ee3fe13db5171805fd1  ofcurso.vdi.xz

Download

VirtualBox image file (Downlaod imagem Lubuntu + OF3.x):
http://www.ara.bme.hu/~hernadi/OpenFOAM/virtualbox.html

Geometria Channels: geometria.step

Geometria e malha (fina) Channels OpenFOAM: Mesh_1_wall.unv

Mesh_coarse.stl/unv/med (~404 000 vol tetrahedrons) NETGEN 

Mesh_coarse2.stl/unv/med (~200 000 vol tetrahedrons) NETGEN

Download

Malha .msh Download

Publication: Journal article

Download

Abstract

The increase in the use of biofuels raised new challenges to engineering problems. In this context, the optimization of chemical reactors, particularly bioreactors and photobioreactors, is crucial to improve the production of biofuels in a sustainable manner. This paper reports the development of an optimization method and its application to the design of a continuous flow bioreactor envisaged to be used in industrial fermentation processes. Mass and momentum conservation equations are simulated via CFD and specific a posteriori performance parameters, determined from the flow solution, are fed into a multiobjective evolutionary algorithm to obtain corrections to the parameters of the geometrical configuration of the reactor. This heuristics is iterated to obtain an optimized configuration vis-à-vis the flow aspects portrayed by the performance parameters, such as the shear stress and the residence time variations. An open source computer package (PyCFD-O) was developed to perform CFD simulations and the optimization processes automatically. First, it calls the pre-processor to generate the computational geometry and the mesh. Then it performs the simulations using OpenFOAM, calculates the output parameters and iterates the procedure. The PyCFD-O package has proved reliable and robust in a test case, a ∼1 m3 continuous fermentation reactor. The multiobjective optimization procedure actually corresponds to search for the Pareto frontier in the solution space characterized by its geometric parameters and the associated performance parameters (dispersion o residence times and shear stresses). Optimal design configurations were obtained representing the best tradeoff between antagonistic objectives, i.e. the so-called non-dominant solutions.

Keywords
Multiobjective optimization; Computational fluid dynamics; Bioreactor; Shear stress; Residence time distribution; Open source code