Three-Dimensional Active Flow Control Drag Reduction Studies Over a Bluff Body Using a Coupled Lattice Boltzmann-Navier-Stokes Methodology

Author(s):  
Nandita Yeshala ◽  
Lakshmi Sankar
2020 ◽  
Vol 117 (42) ◽  
pp. 26091-26098
Author(s):  
Dixia Fan ◽  
Liu Yang ◽  
Zhicheng Wang ◽  
Michael S. Triantafyllou ◽  
George Em Karniadakis

We have demonstrated the effectiveness of reinforcement learning (RL) in bluff body flow control problems both in experiments and simulations by automatically discovering active control strategies for drag reduction in turbulent flow. Specifically, we aimed to maximize the power gain efficiency by properly selecting the rotational speed of two small cylinders, located parallel to and downstream of the main cylinder. By properly defining rewards and designing noise reduction techniques, and after an automatic sequence of tens of towing experiments, the RL agent was shown to discover a control strategy that is comparable to the optimal strategy found through lengthy systematically planned control experiments. Subsequently, these results were verified by simulations that enabled us to gain insight into the physical mechanisms of the drag reduction process. While RL has been used effectively previously in idealized computer flow simulation studies, this study demonstrates its effectiveness in experimental fluid mechanics and verifies it by simulations, potentially paving the way for efficient exploration of additional active flow control strategies in other complex fluid mechanics applications.


Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 872 ◽  
Author(s):  
Takatoshi Matsubara ◽  
Yoshiki Shima ◽  
Hikaru Aono ◽  
Hitoshi Ishikawa ◽  
Takehiko Segawa

An experimental investigation of active flow control on a three-dimensional (3D) curved surface bluff body was conducted by using a string-type plasma actuator. The 3D bluff body model tested in this study was composed of a quarter sphere and a half cylinder, and the Reynolds number based on the diameter of half cylinder was set at 1.3 × 104. The modulation drive was adopted for flow control, and the control effects of variations in dimensionless burst frequency (fm+) normalized by the width of the model and freestream velocity were studied. Velocity distributions analyzed by particle image velocimetry showed that the recirculation region behind the model shrank due to the flow control. The static pressure distributions on the back surface of the model tended to decrease under any fm+ set in this study, especially in the ranges of 0.40 ≤ fm+ ≤ 0.64. The drag coefficient reached its maximum value under the similar ranges of fm+. Although the aerodynamic wake sharpening was observed due to the flow control, the entrainment of separated flow into the back surface of the model was enhanced. This scenario of wake manipulation was considered to be responsible for increasing drag acting on the model.


2020 ◽  
pp. 0309524X2096139
Author(s):  
Fangrui Shi ◽  
Yingqiao Xu ◽  
Xiaojing Sun

In this paper, a three-dimensional numerical simulation of the aerodynamic performance of a horizontal axis wind turbine (HAWT) whose blades are equipped with a new active flow control concept called Co-Flowing Jet (CFJ) is carried out. Numerical results show that the use of CFJ over the blade suction surface can effectively delay flow separation, thus improving the net torque and power output of HAWT. Besides, this increment in the net power produced by the turbine is considerably higher than the power consumed by the CFJ. Thus, the overall efficiency of the HAWT can be greatly increased. Furthermore, influences of different CFJ operating parameters including location of injection port, jet momentum coefficient and slot length on the performance enhancement of a HAWT are also systematically studied and the optimal combination of these parameters to obtain the best possible turbine efficiency throughout a range of different wind speeds has been identified.


AIAA Journal ◽  
2014 ◽  
Vol 52 (10) ◽  
pp. 2165-2175
Author(s):  
Patrick R. Shea ◽  
Mark N. Glauser

Sign in / Sign up

Export Citation Format

Share Document