Bulletin of the American Physical Society
72nd Annual Meeting of the APS Division of Fluid Dynamics
Volume 64, Number 13
Saturday–Tuesday, November 23–26, 2019; Seattle, Washington
Session G19: Advances in LES Modeling II 
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Chair: Meng Wang, Notre Dame Room: 401 
Sunday, November 24, 2019 3:48PM  4:01PM 
G19.00001: Largeeddy simulation of turbulent flow over a body of revolution Di Zhou, Kan Wang, Meng Wang The turbulent flow over an axisymmetric body of revolution (BOR) at zero angle of attack is computed using largeeddy simulation (LES). The BOR consists of an elliptic nose, a cylindrical midsection and a 20$^{\mathrm{o}}$ tail cone, and has a lengthtodiameter ratio of 3.17. The Reynolds number based on the freestream velocity and the BOR length is $1.9\times 10^{6}$. Two simulations are carried out; one is a wallresolved LES, whereas the other employs a wall model on the nose and centerbody sections to reduce the computational cost. Velocity statistics from both simulations are in agreement with each other in the tailcone section where the boundary layer grows rapidly under adverse pressure gradient, indicating that the development of the tailcone turbulent boundary layer is insensitive to the detailed nearwall structures in the upstream boundary layer. They also agree reasonably well with the experimental data from Virginia Tech. The spacetime characteristics of pressure fluctuations on the tailcone surface are investigated. The pressure frequency spectra agree well with experimental measurements except at high frequencies, and the twopoint correlations show significant growth of length scales in the downstream direction. [Preview Abstract] 
Sunday, November 24, 2019 4:01PM  4:14PM 
G19.00002: Reynoldsstressconstraint large eddy simulation of turbulent flow over rough walls Wen Zhang, Minping Wan, Shiyi Chen In the large eddy simulation (LES) of turbulent flow, only the largescale fluid motions are resolved and the effect of smallscale fluctuations is incorporated using the subgridscale (SGS) models. When applying LES to investigate the turbulent flow over rough walls, the surface roughness is also filtered due to the relatively large grid spacing. The subgridscale roughness can have a great impact on the turbulent flow, and must be properly modeled. Although some efforts have been made, the LES of turbulent flow over rough walls still remains an open problem. Typically, the roughness effect is modeled by prescribing the instantaneous stress on the first grid point above the wall according to the equilibrium loglaw assumption. However this method tends to overestimate the mean stress. Instead of that, we propose that the effect of surface roughness can be effectively simulated by constraining the nearwall Reynolds stress, which is incorporated into the SGS stresses in the LES. The simulation results indicate that Townsendâ€™s Reynolds number similarity hypothesis is still valid at relatively low Reynolds number and relatively large roughness height, which is consistent with existing experimental results. [Preview Abstract] 

G19.00003: ABSTRACT WITHDRAWN 
Sunday, November 24, 2019 4:27PM  4:40PM 
G19.00004: Measurementaugmented large eddy simulations Yifan Du, Vincent Mons, Tamer Zaki Data assimilation techniques are adopted to improve the fidelity of largeeddy simulations (LES) by infusing them with measurement data. By exploiting knowledge of loworder flow statistics from experiments or theory, the resulting LES model provides a higher fidelity representation of the instantaneous flow that recovers those statistics. The approach starts with a definition of the cost functional which is proportional to the difference between the reference and predicted statistics, and the coefficients of the subgrid scale model are adjusted using ensemble variational optimization to minimize the cost functional. A proper orthogonal decomposition (POD) representation of the ensemble is adopted to improve robustness of the algorithm. Numerical experiments are performed in turbulent channel flow over a range of Reynolds numbers, and the results demonstrate the superiority of the dataassimilated LES approach over standard subgrid models. [Preview Abstract] 

G19.00005: ABSTRACT WITHDRAWN 
Sunday, November 24, 2019 4:53PM  5:06PM 
G19.00006: Artificial neural network mixed model for large eddy simulation of compressible isotropic turbulence. Chenyue Xie, Jianchun Wang, Hui Li, Minping Wan, Shiyi Chen The subgridscale (SGS) stress and the SGS heat flux of compressible isotropic turbulence are modeled by an artificial neural network(ANN) mixed model(ANNMM), which maintains both functional and structural performances. The functional form of the mixed model combining the gradient model and the Smagorinsky's eddy viscosity model is imposed and the ANN is used to calculate the model coefficients of the SGS anisotropy stress, SGS energy and SGS heat flux. It is shown that the ANNMM model can reconstruct the SGS terms more accurately than the gradient model in the \textit{a priori} test. Specifically, the ANNMM model almost recovers the average values of the SGS energy flux and SGS energy flux conditioned on the normalized filtered velocity divergence. In an \textit{a posteriori} analysis, the ANNMM model shows advantage over the dynamic Smagorinsky model (DSM) and dynamic mixed model (DMM) in the prediction of spectra of velocity and temperature, which almost overlap with the filtered DNS data while the DSM and DMM models suffer from the problem of the typical tilted spectral distribution. Besides, the ANNMM model predicts the PDFs of SGS energy flux much better than DSM and DMM models. [Preview Abstract] 

G19.00007: ABSTRACT WITHDRAWN 
Sunday, November 24, 2019 5:19PM  5:32PM 
G19.00008: Eulerian largeeddy simulation of deepsea hydrocarbon plume with multicomponent gas bubble dissolution. Chen Peng, Marcelo Chamecki, Charles Meneveau, Di Yang The multiphase hydrocarbon plume released from a deepsea oil spill usually contains a large amount of natural gas bubbles that provide the buoyancy force to raise the plume. The natural gas consists of various alkane compounds that can experience considerable dissolution in seawater in the deepsea environment. This gas dissolution effect causes the reduction of the total buoyancy force as the plume rises, strongly affecting the structure and dynamics of the hydrocarbon plume in the region near the release source. In this study, a fast Eulerian largeeddy simulation (LES) model is developed to model the effects of multicomponent gas bubble dissolution on the dynamics of the plume. The LES model is applied to simulate a subsea blowout from a depth of 700 meters, with an initial gas compound ratio of methane/ethane/propane $=$ 87.5/8.1/4.4. Both instantaneous flow field and statistical characteristics of the plumes will be presented in this talk. [Preview Abstract] 
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