The setup of inlet conditions for a large eddy simulation (LES) is a complex and important problem. Normally, there are two methods to generate the inlet conditions for LES, i.e., synthesized turbulence methods and precursor simulation methods. This study presents a new method for determining inlet boundary conditions of LES using particle image velocimetry (PIV). LES shows sensitivity to inlet boundary conditions in the developing region, and this effect can even extend into the fully developed region of the flow. Two kinds of boundary conditions generated from PIV data, i.e., steady spatial distributed inlet (SSDI) and unsteady spatial distributed inlet (USDI), are studied. PIV provides valuable field measurement, but special care is needed to estimate turbulent kinetic energy and turbulent dissipation rate for SSDI. Correlation coefficients are used to analyze the autocorrelation of the PIV data. Different boundary conditions have different influences on LES, and their advantages and disadvantages for turbulence prediction and static pressure prediction are discussed in the paper. Two kinds of LES with different subgrid turbulence models are evaluated: namely dynamic Smagorinsky–Lilly model (Lilly model) and wall modeled large eddy simulation (WMLES model). The performances of these models for flow prediction in a square duct are presented. Furthermore, the LES results are compared with PIV measurement results and Reynolds-stress model (RSM) results at a downstream location for validation.
Skip Nav Destination
Article navigation
July 2018
Research-Article
A Method of Measuring Turbulent Flow Structures With Particle Image Velocimetry and Incorporating Into Boundary Conditions of Large Eddy Simulations
Puxuan Li,
Puxuan Li
Institute for Environmental Research,
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: puxuanli@ksu.edu
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: puxuanli@ksu.edu
Search for other works by this author on:
Steve J. Eckels,
Steve J. Eckels
Institute for Environmental Research,
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: eckels@ksu.edu
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: eckels@ksu.edu
Search for other works by this author on:
Garrett W. Mann,
Garrett W. Mann
Institute for Environmental Research,
Mechanical and Nuclear
Engineering Department,
Kansas State University,
Manhattan, KS 66506
e-mail: gmann@ksu.edu
Mechanical and Nuclear
Engineering Department,
Kansas State University,
Manhattan, KS 66506
e-mail: gmann@ksu.edu
Search for other works by this author on:
Ning Zhang
Ning Zhang
Department of Chemical, Civil
and Mechanical Engineering,
McNeese State University,
Lake Charles, LA 70609
e-mail: nzhang@mcneese.edu
and Mechanical Engineering,
McNeese State University,
Lake Charles, LA 70609
e-mail: nzhang@mcneese.edu
Search for other works by this author on:
Puxuan Li
Institute for Environmental Research,
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: puxuanli@ksu.edu
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: puxuanli@ksu.edu
Steve J. Eckels
Institute for Environmental Research,
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: eckels@ksu.edu
Mechanical and Nuclear Engineering
Department,
Kansas State University,
Manhattan, KS 66506
e-mail: eckels@ksu.edu
Garrett W. Mann
Institute for Environmental Research,
Mechanical and Nuclear
Engineering Department,
Kansas State University,
Manhattan, KS 66506
e-mail: gmann@ksu.edu
Mechanical and Nuclear
Engineering Department,
Kansas State University,
Manhattan, KS 66506
e-mail: gmann@ksu.edu
Ning Zhang
Department of Chemical, Civil
and Mechanical Engineering,
McNeese State University,
Lake Charles, LA 70609
e-mail: nzhang@mcneese.edu
and Mechanical Engineering,
McNeese State University,
Lake Charles, LA 70609
e-mail: nzhang@mcneese.edu
1Corresponding author.
Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received January 23, 2017; final manuscript received November 22, 2017; published online March 16, 2018. Assoc. Editor: Daniel Livescu.
J. Fluids Eng. Jul 2018, 140(7): 071401 (11 pages)
Published Online: March 16, 2018
Article history
Received:
January 23, 2017
Revised:
November 22, 2017
Citation
Li, P., Eckels, S. J., Mann, G. W., and Zhang, N. (March 16, 2018). "A Method of Measuring Turbulent Flow Structures With Particle Image Velocimetry and Incorporating Into Boundary Conditions of Large Eddy Simulations." ASME. J. Fluids Eng. July 2018; 140(7): 071401. https://doi.org/10.1115/1.4039256
Download citation file:
Get Email Alerts
Cited By
Related Articles
Large Eddy Simulation of the Flow Behavior in a Simplified Helical Coil Steam Generator
J. Fluids Eng (February,2019)
Experimental Study of Suction Flow Control Effectiveness in a Serpentine Intake
J. Fluids Eng (October,2017)
On Flux-Limiting-Based Implicit Large Eddy Simulation
J. Fluids Eng (December,2007)
Optimization of Low-Pressure Turbine Blade by Means of Fine Inspection of Loss Production Mechanisms
J. Turbomach (April,2025)
Related Chapters
Cavitating Structures at Inception in Turbulent Shear Flow
Proceedings of the 10th International Symposium on Cavitation (CAV2018)
Antilock-Braking System Using Fuzzy Logic
International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-China 2011), Volumes 1–3
An Investigation of Tip-Vortex Turbulence Structure using Large-Eddy Simulation
Proceedings of the 10th International Symposium on Cavitation (CAV2018)