A Parallel Computational–Statistical Framework for Simulation of Turbulence: Applications to Data-Driven Fractional Modeling

Author:

Akhavan-Safaei Ali1ORCID,Zayernouri Mohsen2ORCID

Affiliation:

1. Departments of Mechanical Engineering & Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI 48824, USA

2. Departments of Mechanical Engineering & Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA

Abstract

In this work, an open-source computational–statistical platform to obtain synthetic homogeneous isotropic turbulent flow and passive scalar transport is presented. A parallel implementation of the well-known pseudo-spectral method in addition to the comprehensive record of the statistical and small-scale quantities of the turbulent transport are offered for executing on distributed memory CPU-based supercomputers. The user-friendly workflow and easy-to-run design of the developed package are disclosed through an extensive and step-by-step example. The resulting low- and high-order statistical records vividly verify a well-established and fully developed turbulent state as well as the seamless statistical balance of conservation laws. The post-processing tools provided in this platform would allow the user to easily construct multiple important transport quantities from primitive turbulent fields. The programming codes for this tool are accessible through GitHub (see Data Availability Statement).

Funder

MURI/ARO award

ARO Young Investigator Program (YIP) award

NSF award

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

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