Investigation of Suction Flow Control on Centrifugal Compressor with Vaned Diffuser

In this study, the effect of suction flow control on a centrifugal compressor at operation and stall flow rates was investigated using computational fluid dynamics (CFD). The compressor geometry was reconstructed from available open source profile data and the CFD analyses have been performed on this geometry using the appropriate mesh. To validate the CFD results, the compressor performance line was acquired and compared with the experimental results obtained at the design rotational speed. Then, suction flow control was employed at various suction slot positions with different suction flow rates to improve the performance of the compressor at operation and stall flow rates. As a result of the suction flow control trials, 0.85% increase in pressure ratio and 0.8% increase in adiabatic efficiency were achieved while the compressor was running at operation flow rate. The performance improvements corresponding to the stall flow rate of the compressor were 2.5% increase in pressure ratio and 2% increase in adiabatic efficiency.

Conceptual Design of a Novel Unmanned Ground Effect Vehicle (UGEV) and Flow Control Integration Study

In this study, the conceptual design of an unmanned ground effect vehicle (UGEV), based on in-house analytical tools and CFD calculations, followed by flow control studies, is presented. Ground effect vehicles can operate, in a more efficient way, over calm closed seas, taking advantage of the aerodynamic interaction between the ground and the vehicle. The proposed UGEV features a useful payload capacity of 300 kg and a maximum range of 300 km cruising at 100 kt. Regarding the aerodynamic layout, a platform which combines the basic geometry characteristics of the blended wing body (BWB), and box wing (BXW) configurations is introduced. This hybrid layout aims to incorporate the most promising features from both configurations, while it enables the UGEV to operate under adverse flight conditions of the atmospheric boundary layer of the earth. In order to enhance the performance characteristics of the platform, both passive and active flow control techniques are studied and incorporated into the conceptual design phase of the vehicle. For the passive flow control techniques, the adaptation of tubercles and wing fences is evaluated. Regarding the active flow control techniques, a wide range of morphing technologies is investigated based on performance and integration criteria. Finally, stability studies are conducted for the proposed platform.

Enhancement of dynamic performance of wave energy converter by introducing a flow control

The stabilization of power take-off (PTO) is imperative especially under circumstances of fluctuating input wave energy. In this paper, a flow control valve is introduced to optimize the transient process of the hydraulic PTO, which can contribute to a quicker adjustment and a stronger stability. Under variations of input power and load torque in transient process, an open-loop control method and a closed-loop control method are proposed as the opening law of the above valve, and the hydraulic motor speed, the pressure at the accumulator inlet and the generated power are chosen as indicators to examine the regulation performance. Then, the synergic effect of the flow control valve and the accumulator in the transient process is discussed. The effectiveness of the two presented control methods on the fluctuation suppression is respectively tested and compared in both regular wave and irregular wave situations via simulation. To validate the practical effectiveness of the proposed methods, field experiments are conducted. The results demonstrate that the open-loop control can only improve the damping ability of the hydraulic PTO in the speed raising stage, while the closed-loop control can improve the stability both in the speed raising stage and in the load increasing stage.

Intelligent Network Traffic Control Based on Deep Reinforcement Learning

This paper studies the problems of load balancing and flow control in data center network, and analyzes several common flow control schemes in data center intelligent network and their existing problems. On this basis, the network traffic control problem is modeled with the goal of deep reinforcement learning strategy optimization, and an intelligent network traffic control method based on deep reinforcement learning is proposed. At the same time, for the flow control order problem in deep reinforcement learning algorithm, a flow scheduling priority algorithm is proposed innovatively. According to the decision output, the corresponding flow control and control are carried out, so as to realize the load balance of the network. Finally, experiments show, the network traffic bandwidth loss rate of the proposed intelligent network traffic control method is low. Under the condition of random 60 traffic density, the average bisection bandwidth obtained by the proposed intelligent network traffic control method is 4.0mbps and the control error rate is 2.25%. The intelligent network traffic control method based on deep reinforcement learning has high practicability in the practical application process, and fully meets the research requirements.

Flow Control in Wings and Discovery of Novel Approaches via Deep Reinforcement Learning

In this review we summarize existing trends of flow control used to improve the aerodynamic efficiency of wings. We first discuss active methods to control turbulence, starting with flat-plate geometries and building towards the more complicated flow around wings. Then, we discuss active approaches to control separation, a crucial aspect towards achieving high aerodynamic efficiency. Furthermore, we highlight methods relying on turbulence simulation, and discuss various levels of modelling. Finally, we thoroughly revise data-driven methods, their application to flow control, and focus on deep reinforcement learning (DRL). We conclude that this methodology has the potential to discover novel control strategies in complex turbulent flows of aerodynamic relevance.

Real Time Flow Control System for Precise Gas Feed in COIL

This paper reports development of a real time flow control system for precise, controlled and uniform gas feed to a flowing medium Chemical Oxygen Iodine Laser (COIL). The optimal operation of this prominent laser depends upon the desired supply of gas constituents such as nitrogen (N2), chlorine (Cl2) and iodine (I2) to achieve adequately mixed laser gas. The laser also demands real time variation of flow rates during gas constituent transitions in order to maintain stabilized pressures in critical subsystems. Diluent nitrogen utilized for singlet oxygen transport is termed as primary buffer gas and that for iodine transport is termed as secondary buffer gas (with main and bypass components). Also, nitrogen in precise flows is used for mirror blowing, nozzle curtain, cavity bleed and diffuser startup. A compact hybrid data acquisition system (Hybrid DAS) for precise flow control using LabVIEW 2014 platform has been developed. The supported flow ranges may vary from few mmole.s-1 to few hundred mmole.s-1. The estimated relative uncertainty in the largest gas component i.e. primary buffer gas feed is nearly 0.7%. The implementation of in-operation variation using flow ramp enables swift stabilization of singlet oxygen generator pressures critical for successful COIL operation. The performance of Hybrid DAS is at par with fully wired DAS providing the crucial benefit of remote field operation at distances of nearly 80m in line of sight and 35m with obstacles