fastSF: A parallel code for computing the structure functions of turbulence
Permanent link to this recordhttp://hdl.handle.net/10754/667082
MetadataShow full item record
AbstractTurbulence is a complex phenomenon in fluid dynamics involving nonlinear interactions between multiple scales. Structure functions are popular diagnostics in the study of statistical properties properties of turbulent flows (Frisch, 1995; Kolmogorov, 1941a, 1941b). Some of the earlier works comprising of such analysis are those of Gotoh et al. (2002), Ishihara et al. (2003), and Ishihara & Gotoh (2009) for three-dimensional (3D) hydrodynamic turbulence; Yeung et al. (2005) and Ray et al. (2008) for passive scalar turbulence; Biferale et al. (2004) for two-dimensional (2D) hydrodynamic turbulence; and Kunnen et al. (2008), Kaczorowski & Xia (2013), and Bhattacharya et al. (2019) for turbulent thermal convection. Structure functions are two-point statistical quantities; thus, an accurate computation of these quantities requires averaging over many points. However, incorporation of a large number of points makes the computations very expensive and challenging. Therefore, we require an efficient parallel code for accurate computation of structure functions. In this paper, we describe the design and validation of the results of fastSF, a parallel code to compute the structure functions for a given velocity or scalar field.
CitationSadhukhan, S., Bhattacharya, S., & Verma, M. (2021). fastSF: A parallel code for computing the structure functions of turbulence. Journal of Open Source Software, 6(57), 2185. doi:10.21105/joss.02185
SponsorsWe thank Roshan Samuel, Anando Chatterjee, Soumyadeep Chatterjee, and Manohar Sharma for helpful discussions during the development of fastSF. We are grateful to Jed Brown, Ilja Honkonen, and Chris Green for a careful review of our work and their useful suggestions. Our computations were performed on Shaheen II at KAUST supercomputing laboratory, Saudi Arabia, under the project k1416.
PublisherThe Open Journal
JournalJournal of Open Source Software
CollectionsPublications Acknowledging KAUST Support
Except where otherwise noted, this item's license is described as Authors of papers retain copyright and release the work under a Creative Commons Attribution 4.0 International License.