Investigation on the flow characteristics of a novel multi‐blade combined agitator by time‐resolved particle image velocimetry and large eddy simulation

AIChE Journal ◽  
2020 ◽  
Vol 66 (8) ◽  
Author(s):  
Yan Xu ◽  
Bin Wu ◽  
Peicheng Luo
Author(s):  
Martin Wosnik ◽  
Qiao Qin ◽  
Damien T. Kawakami ◽  
Roger E. A. Arndt

A Large Eddy Simulation (LES) approach for cavitating flow, based on a virtual single-phase, fully compressible cavitation model which includes the effects of incondensable gas, has been shown to be capable of capturing the complex dynamical features of highly unsteady cavitating flows of two-dimensional hydrofoils. Here the LES results are compared to Time-Resolved Particle Image Velocimetry (TR-PIV) in the wake of a cavitating NACA 0015 hydrofoil, with particular attention to the predicted vortex shedding mechanisms. Despite some difficulty with obtaining vector fields from vortical clouds of vaporous-gaseous bubbles with cross-correlation techniques, the initial results seem promising in that they confirm the existence of a primary vortex pair (type A-B). In addition to TR-PIV, the cavitation cloud shedding was also documented with phase-locked, time-resolved photography and high speed volume-illuminated video, both with simultaneous imaging of side and plan views of the foil. All three experimental techniques confirm the need for fully three-dimensional simulations to properly describe the unsteady, three-dimensional cavitation cloud shedding mechanism.


2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Puxuan Li ◽  
Steve J. Eckels ◽  
Garrett W. Mann ◽  
Ning Zhang

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.


2020 ◽  
pp. 146808742093459 ◽  
Author(s):  
Insuk Ko ◽  
Federico Rulli ◽  
Stefano Fontanesi ◽  
Alessandro d’Adamo ◽  
Kyoungdoug Min

Large-eddy simulation has been increasingly applied to internal combustion engine flows because of their improved potential to capture the spatial and temporal evolution of turbulent flow structures compared with Reynolds-averaged Navier Stokes simulation. Furthermore, large-eddy simulation is universally recognized as capable of simulating highly unsteady and random phenomena, which drive cycle-to-cycle variability and cycle-resolved events such as knocks and misfires. To identify large-scale structure fluctuations, many methods have been proposed in the literature. This article describes the application of several analysis methods for the comparison between different datasets (experimental or numerical) and the identification of large-structure fluctuations. The reference engine is the well-known TCC-III single-cylinder optical unit from the University of Michigan and GM Global R&D center; the analyses were carried out under motored engine conditions. A deep analysis of in-cylinder gas dynamics and flow structure evolution was performed by comparing the experimental results (particle image velocimetry of the velocity fields) with a dataset of consecutive large-eddy simulation cycles on four different cutting planes at engine-relevant crank angle positions. Phase-dependent proper orthogonal decomposition was used to obtain further conclusions regarding the accuracy of the simulation results and to apply conditional averaging methods. A two-point correlation and an analysis of the tumble center are proposed. Finally, conclusions are drawn to be used as guidelines in future large-eddy simulation analyses of internal combustion engines.


2005 ◽  
Vol 4 (1-2) ◽  
pp. 93-115 ◽  
Author(s):  
Jérôme Boudet ◽  
Nathalie Grosjean ◽  
Marc C. Jacob

A large-eddy simulation is carried out on a rod-airfoil configuration and compared to an accompanying experiment as well as to a RANS computation. A NACA0012 airfoil (chord c = 0.1 m) is located one chord downstream of a circular rod (diameter d = c/10, Red = 48 000). The computed interaction of the resulting sub-critical vortex street with the airfoil is assessed using averaged quantities, aerodynamic spectra and proper orthogonal decomposition (POD) of the instantaneous flow fields. Snapshots of the flow field are compared to particle image velocimetry (PIV) data. The acoustic far field is predicted using the Ffowcs Williams & Hawkings acoustic analogy, and compared to the experimental far field spectra. The large-eddy simulation is shown to accurately represent the deterministic pattern of the vortex shedding that is described by POD modes 1 & 2 and the resulting tonal noise also compares favourably to measurements. Furthermore higher order POD modes that are found in the PIV data are well predicted by the computation. The broadband content of the aerodynamic and the acoustic fields is consequently well predicted over a large range of frequencies ([0 kHz; 10 kHz]).


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