Control effect of micro vortex generators on attached cavitation instability

Schmidt, Steffen J.; Likhachev, Dmitriy S.

doi:10.1063/1.5099089

Cited by 45 publications

(9 citation statements)

References 51 publications

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“…In another study, Che and coauthors analyzed the instability of the attached cavitation produced with mVGs. 186 This study confirmed that these mVGs are an effective passive control for attached cavitation dynamics and changed the surface wall's vicinity's flow dynamics. The results also emphasized again that the mVGs could increase the cavity length and induce counter-rotating streamwise vortices.…”

Section: Physics Of Fluidssupporting

confidence: 72%

“…In this study, Che et al 186 interpret two types of Rayleigh-Taylor (R-T) and K-H instabilities, while cavity shedding and re-entrant jet interactions happened over a smooth hydrofoil and hydrofoil with mVGs. Re-entrant jets are generated by exposing cavity closure to an adverse pressure gradient.…”

Section: Physics Of Fluidsmentioning

confidence: 79%

“…Che et al 186 presented evidence that reverse flow beneath the attached cavities, which were linked to R-T and K-H instabilities, were suppressed. The mVGs were shown to influence partial cavity oscillations, transitional cavity oscillations, and transition between these two instabilities.…”

Section: Physics Of Fluidsmentioning

confidence: 99%

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Cavitation control using passive flow control techniques

et al. 2021

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Passive flow control techniques, and particularly vortex generators have been used successfully in a broad range of aero-and hydrodynamics applications to alter the characteristics of boundary layer separation. This study aims to review how such techniques can mitigate the extent and impact of cavitation in incompressible flows. This review focuses first on vortex generators to characterize key physical principles. It then considers the complete range of passive flow control technologies, including surface conditioning and roughness, geometry modification, grooves, discharge, injection, obstacles, vortex generators, and bubble generators. The passive flow control techniques reviewed typically delay and suppress boundary layer separation by decreasing the pressure gradient at the separation point. The literature also identifies streamwise vortices that result in the transfer of momentum from the free stream to near-wall low energy flow regions. The area of interest concerns hydraulic machinery, whose performance and life span are particularly susceptible to cavitation. The impact on performance includes a reduction in efficiency and fluctuations in discharge pressure and flow, while cavitation can greatly increase wear of bearings, wearing rings, seals, and impeller surfaces due to excessive vibration and surface erosion. In that context, few studies have also shown the positive effects that passive controls can have on the hydraulic performance of centrifugal pumps, such as total head and efficiency. It is conceivable that a new generation of design in hydraulic systems may be possible if simple design features can be conceived to maximize power transfer and minimize losses and cavitation. There are still, however, significant research gaps in understanding a range of impact factors such as manufacturing processes, lifetime, and durability, and essentially how a static design can be optimized to deliver improved performance over a realistic range of operating conditions.

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Section: Physics Of Fluidssupporting

confidence: 72%

Section: Physics Of Fluidsmentioning

confidence: 79%

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Cavitation control using passive flow control techniques

et al. 2021

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“…Realistic actuation mechanisms, such as plasma actuators (Sato et al, 2015), suction mechanisms (Wang et al, 2016), transverse motion (Li & Aubry, 2003), periodic oscillations (Lu et al, 2011), oscillating foils (Bao & Tao, 2013), air jets (Zhu et al, 2019), or Lorentz forces in conductive media (Breuer et al, 2004), are also discussed in details, as well as limitations imposed by real-wold systems (Belson et al, 2013). Similarly, a lot of experimental work has been performed, with the goal of controlling either the cavitation instability (Che et al, 2019), the vortex flow behind a conical forebody (Meng et al, 2018), or the flow separation over a circular cylinder (Jukes & Choi, 2009a,b). arXiv:1906.10382v2 [physics.comp-ph] 12 Aug 2019 ACCELERATING DRL OF AFC: MULTI-ENV APPROACH AUGUST 13, 2019 Finally, while most of the literature has focused on complex, closed-loop control methods, some open-loop methods have also been discussed, both in simulations (Meliga et al, 2010) and in experiments (Shahrabi, 2019).…”

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confidence: 99%

Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach

2019

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Deep Reinforcement Learning (DRL) has recently been proposed as a methodology to discover complex Active Flow Control (AFC) strategies [Rabault, J., Kuchta, M., Jensen, A., Réglade, U., & Cerardi, N. (2019): "Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control", Journal of Fluid Mechanics, 865, 281-302]. However, while promising results were obtained on a simple 2D benchmark flow at a moderate Reynolds number, considerable speedups will be required to investigate more challenging flow configurations. In the case of DRL trained with Computational Fluid Dynamics (CFD) data, it was found that the CFD part, rather than training the Artificial Neural Network, was the limiting factor for speed of execution. Therefore, speedups should be obtained through a combination of two approaches. The first one, which is well documented in the literature, is to parallelize the numerical simulation itself. The second one is to adapt the DRL algorithm for parallelization. Here, a simple strategy is to use several independent simulations running in parallel to collect experiences faster. In the present work, we discuss this solution for parallelization. We illustrate that perfect speedups can be obtained up to the batch size of the DRL agent, and slightly suboptimal scaling still takes place for an even larger number of simulations. This is, therefore, an important step towards enabling the study of more sophisticated Fluid Mechanics problems through DRL.

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“…Finally, the selected spectrum band is taken as the envelope spectrum, and demodulated signals can be obtained by inverse Fourier Transform (FT), so the feature extraction from the envelope spectrum can detect the hidden non-stationarities of measured signals. Here, Kurtosis is used to describe the degree of steepness of a random distribution, as defined in Equation (2). It has been widely used to detect the impact fault in rotating machinery [20][21][22][23][24][25][26].…”

Section: Autogram Compared With the Kurtogrammentioning

confidence: 99%

An Adaptive Autogram Approach Based on a CFAR Detector for Incipient Cavitation Detection

Chu

Wang

et al. 2020

Sensors

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Cavitation failure often occurs in centrifugal pumps, resulting in severe harm to their performance and life-span. Nowadays, it has become crucial to detect incipient cavitation ahead of cavitation failure. However, most envelope demodulation methods suffer from strong noise and repetitive impacts. This paper proposes an adaptive Autogram approach based on the Constant False Alarm Rate (CFAR). A cyclic amplitude model (CAM) is presented to reveal the cyclostationarity and autocorrelation-periodicity of pump cavitation-caused signals. The Autogram method is improved for envelope demodulation and cyclic feature extraction by introducing the character to noise ratio (CNR) and CFAR threshold. To achieve a high detection rate, CNR parameters are introduced to represent the cavitation intensity in the combined square-envelope spectrum. To maintain a low false alarm, the CFAR detector is combined with the CNR parameter to obtain adaptive thresholds for different data along with sensor positions. By carrying out various experiments of a centrifugal water pump from Status 1 to 10 at different flow rates, the proposed approach is capable of cavitation feature extraction with respect to the CAM model, and can achieve more than a 90% detection rate of incipient cavitation and maintain a 5% false alarm rate. This paper offers an alternative solution for the predictive maintenance of pump cavitation.

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Control effect of micro vortex generators on attached cavitation instability

Cited by 45 publications

References 51 publications

Cavitation control using passive flow control techniques

Cavitation control using passive flow control techniques

Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach

An Adaptive Autogram Approach Based on a CFAR Detector for Incipient Cavitation Detection

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