Evaluation of the proper coherence representation in random flow generation based methods

Hugo G. Castro*, Rodrigo R. Paz, Javier L. Mroginski, Mario A. Storti

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The interest in synthetic methods relies in the fact that reliability of methodologies such as large eddy simulations (LES) or direct numerical simulations strongly depends on how well the developed turbulence is characterized, which generally leads to computationally expensive simulations. Turbulence generation methods allow the initialization and up-keeping of the velocity fluctuations field to promote the observed/needed turbulence in the flow. In this work the methodology known as ‘modified discretizing and synthesizing random flow generation’ (MDSRFG) jointly with a LES method is analyzed for its use in the study of tall building aerodynamics. A comparison with other generation techniques, that are closely related by their features and their conceptual origins, is presented with particular emphasis on the correct representation of the coherence of the velocity field. Particularly, an expression for the coherency function for the MDSRFG is derived. After an analysis and revision of these generation methodologies, the turbulent air flow around a rectangular prismatic model is computationally simulated. A comparison of the results obtained from different methods is performed. The resulting wind loads on the model, along with the statistical characteristics of the flow, show that the MDSRFG technique allows to represent a field of spatially correlated velocities correctly.

Original languageEnglish (US)
Pages (from-to)211-227
Number of pages17
JournalJournal of Wind Engineering and Industrial Aerodynamics
Volume168
DOIs
StatePublished - Sep 2017

Keywords

  • Coherency
  • Computational fluid dynamics
  • Large eddy simulation
  • Turbulence synthesis
  • Wind loads

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Renewable Energy, Sustainability and the Environment
  • Mechanical Engineering

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