TY - JOUR
T1 - Multi-scale high-performance fluid flow
T2 - Simulations through porous media
AU - Perović, Nevena
AU - Frisch, Jérôme
AU - Salama, Amgad
AU - Sun, Shuyu
AU - Rank, Ernst
AU - Mundani, Ralf Peter
N1 - Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Computational fluid dynamic (CFD) calculations on geometrically complex domains such as porous media require high geometric discretisation for accurately capturing the tested physical phenomena. Moreover, when considering a large area and analysing local effects, it is necessary to deploy a multi-scale approach that is both memory-intensive and time-consuming. Hence, this type of analysis must be conducted on a high-performance parallel computing infrastructure. In this paper, the coupling of two different scales based on the Navier–Stokes equations and Darcy's law is described followed by the generation of complex geometries, and their discretisation and numerical treatment. Subsequently, the necessary parallelisation techniques and a rather specific tool, which is capable of retrieving data from the supercomputing servers and visualising them during the computation runtime (i.e. in situ) are described. All advantages and possible drawbacks of this approach, together with the preliminary results and sensitivity analyses are discussed in detail.
AB - Computational fluid dynamic (CFD) calculations on geometrically complex domains such as porous media require high geometric discretisation for accurately capturing the tested physical phenomena. Moreover, when considering a large area and analysing local effects, it is necessary to deploy a multi-scale approach that is both memory-intensive and time-consuming. Hence, this type of analysis must be conducted on a high-performance parallel computing infrastructure. In this paper, the coupling of two different scales based on the Navier–Stokes equations and Darcy's law is described followed by the generation of complex geometries, and their discretisation and numerical treatment. Subsequently, the necessary parallelisation techniques and a rather specific tool, which is capable of retrieving data from the supercomputing servers and visualising them during the computation runtime (i.e. in situ) are described. All advantages and possible drawbacks of this approach, together with the preliminary results and sensitivity analyses are discussed in detail.
KW - Hierarchical data structure
KW - High-performance computing
KW - Interactive data exploration
KW - Multi-grid-like solver
KW - Multi-scale approach
KW - Parallel computing
KW - Porous media
UR - http://www.scopus.com/inward/record.url?scp=84997818351&partnerID=8YFLogxK
U2 - 10.1016/j.advengsoft.2016.07.016
DO - 10.1016/j.advengsoft.2016.07.016
M3 - Article
AN - SCOPUS:84997818351
SN - 0965-9978
VL - 103
SP - 85
EP - 98
JO - Advances in Engineering Software
JF - Advances in Engineering Software
ER -