Analysis and experimental study on resistance-increasing behavior of composite high efficiency autonomous inflow control device

Bottom water coning is the main reason to reduce the recovery of horizontal bottom water reservoir. By water coning, we mean the oil-water interface changes from a horizontal state to a mound-shaped cone and breaks through to the wellbore. Autonomous inflow control device(AICD) is an important instrument maintain normal production after bottom water coning, however, the resistance increasing ability of the swirl type AICD is insufficient at present, which seriously affects the water control effect. Aiming this problem, this paper designs a multi-stage resistance-increasing and composite type AICD. The separation mechanism of oil-water two phases in this structure, the resistance form of oil-water single phase and the resistance-increasing principle of water phase are analyzed. Establishing the dual-phase multi-stage separation and resistance-increasing model, and verified by measuring the throttling pressure drop and oil-water volume fraction of the AICD, it is found that the composite type AICD has the effect of ICD and AICD at the same time, which can balance the production rate of each well section at the initial stage of production, delay the occurrence of bottom water coning. In the middle and later stages of production, water-blocking can be effectively increased to achieve water control and stable production.After structural sensitivity analysis, the influence law of various structural parameters on the water control performance of composite AICD was obtained. The simulation calculation results show that,compared with the existing swirl type AICD, composite AICD has higher sensitivity to moisture content,the water phase throttling pressure drop is increased by 4.5 times on average. The composite AICD is suitable for the entire stage of horizontal well production.

Research on passenger flow control at metro transfer stations based on real-time flow calculation of streamlines

Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processesand the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transferstation streamlines.Design/methodology/approach – The synthesis of stochastic process theory with streamline analysisengenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passengerflow data procured from monitoring systems within the transfer station, a gradient descent optimizationtechnique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorizedpassenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm isimplemented to allocate the intra-station categorized passenger flows across various streamlines, ascertainingthe traffic volume for each.Findings – Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation softwareis engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposedpassenger flow estimation model. The derived solutions are instrumental in formulating a crowd controlstrategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowdmanagement interventions that offer insights for the orchestration of passenger flow and operationalgovernance within metro stations.Originality/value – The construction of an estimation methodology for the real-time streamline traffic flowaugments the model’s dataset, supplanting estimated values derived from surveys or historical datasets withreal-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow managementwithin metro stations.

Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.

Mathematical Modeling and Control Algorithm Development for Bidirectional Power Flow in CCS-CNT System

As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.

Model Predictive Control Strategy of Multi-Port Interline DC Power Flow Controller

There are issues with flexible DC transmission system such as a lack of control freedom over power flow.In order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power grid.In recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability.This work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance.Initially,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control objectives.Sub module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC strategy.Finally,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.

Autonomous Multi-Factor Energy Flows Controller (AmEFC): Enhancing Renewable Energy Management with Intelligent Control Systems Integration

The transition to sustainable energy systems is one of the defining challenges of our time, necessitating innovations in how we generate, distribute, and manage electrical power. Micro-grids, as localized energy hubs, have emerged as a promising solution to integrate renewable energy sources, ensure energy security, and improve system resilience. The Autonomous multi-factor Energy Flow Controller (AmEFC) introduced in this paper addresses this need by offering a scalable, adaptable, and resilient framework for energy management within an on-grid micro-grid context. The urgency for such a system is predicated on the increasing volatility and unpredictability in energy landscapes, including fluctuating renewable outputs and changing load demands. To tackle these challenges, the AmEFC prototype incorporates a novel hierarchical control structure that leverages Renewable Energy Sources (RES), such as photovoltaic systems, wind turbines, and hydro pumps, alongside a sophisticated Battery Management System (BMS). Its prime objective is to maintain an uninterrupted power supply to critical loads, efficiently balance energy surplus through hydraulic storage, and ensure robust interaction with the main grid. A comprehensive Simulink model is developed to validate the functionality of the AmEFC, simulating real-world conditions and dynamic interactions among the components. The model assesses the system’s reliability in consistently powering critical loads and its efficacy in managing surplus energy. The inclusion of advanced predictive algorithms enables the AmEFC to anticipate energy production and consumption trends, integrating weather forecasting and inter-controller communication to optimize energy flow within and across micro-grids. This study’s significance lies in its potential to facilitate the seamless incorporation of RES into existing power systems, thus propelling the energy sector towards a more sustainable, autonomous, and resilient future. The results underscore the potential of such a system to revolutionize energy management practices and highlight the importance of smart controller systems in the era of smart grids.

Groundwater flow through fractured rocks and seepage control in geotechnical engineering: Theories and practices

Groundwater flow through fractured rocks has been recognized as an important issue in many geotechnical engineering practices.Several key aspects of fundamental mechanisms,numerical modeling and engineering applications of flow in fractured rocks are discussed.First,the microscopic mechanisms of fluid flow in fractured rocks,especially under the complex conditions of non-Darcian flow,multiphase flow,rock dissolution,and particle transport,have been revealed through a com-bined effort of visualized experiments and theoretical analysis.Then,laboratory and field methods of characterizing hydraulic properties(e.g.intrinsic permeability,inertial permeability,and unsaturated flow parameters)of fractured rocks in different flow regimes have been proposed.Subsequently,high-performance numerical simulation approaches for large-scale modeling of groundwater flow in frac-tured rocks and aquifers have been developed.Numerical procedures for optimization design of seepage control systems in various settings have also been proposed.Mechanisms of coupled hydro-mechanical processes and control of flow-induced deformation have been discussed.Finally,three case studies are presented to illustrate the applications of the improved theoretical understanding,characterization methods,modeling approaches,and seepage and deformation control strategies to geotechnical engi-neering projects.

Reinforcement learning for wind-farm flow control:Current state and future actions

Wind-farm flow control stands at the forefront of grand challenges in wind-energy science.The central issue is that current algorithms are based on simplified models and,thus,fall short of capturing the complex physics of wind farms associated with the high-dimensional nature of turbulence and multiscale wind-farm-atmosphere interactions.Reinforcement learning(RL),as a subset of machine learning,has demonstrated its effectiveness in solving high-dimensional problems in various domains,and the studies performed in the last decade prove that it can be exploited in the development of the next generation of algorithms for wind-farm flow control.This review has two main objectives.Firstly,it aims to provide an up-to-date overview of works focusing on the development of wind-farm flow control schemes utilizing RL methods.By examining the latest research in this area,the review seeks to offer a comprehensive understanding of the advancements made in wind-farm flow control through the application of RL techniques.Secondly,it aims to shed light on the obstacles that researchers face when implementing wind-farm flow control based on RL.By highlighting these challenges,the review aims to identify areas requiring further exploration and potential opportunities for future research.

Theoretical Analysis and Numerical Simulation of the Static and Dynamic Characteristics of Hydrostatic Guides Based on Progressive Mengen Flow Controller

The oil film thickness of oil hydrostatic guide with constant pressure supply based on capillary restrictor is greatly affected by load, and this kind of hydrostatic guide is usually applied to the machine tools with moderate load. The static and dynamic characteristics of the guide have been studied by using some theoretical, numerical and experimental approaches, and some methods and measures have been proposed to improve its performances. The hydrostatic guide based on progressive mengen（PM） flow controller is especially suitable for the heavy numerical control（NC） machine tools. However, few literatures about the research on the static and dynamic characteristics of the hydrostatic guides based on PM flow controller are reported. In this paper, the formulae are derived for analyzing the static and dynamic characteristics of hydrostatic guides with rectangle pockets and PM flow controller according to the theory of hydrostatic bearing. On the basis of the analysis of hydrostatic bearing with circular pocket, some equations are derived for solving the static pressure, volume pressure and squeezing pressure which influence the dynamic characteristics of hydrostatic guides with rectangle pocket. The function and the influencing factors of three pressures are clarified. The formulae of amplitude-frequency characteristics and dynamic stiffness of the hydrostatic guide system are derived. With the help of software MATLAB, programs are coded with C＋＋ language to simulate numerically the static and dynamic characteristics of the hydrostatic guide based on PM flow controller. The simulation results indicate that the sensitive oil volume between the outlet of the PM flow controller and the guide pocket has the greatest influence on the characteristics of the guide, and it should be reduced as small as possible when the field working condition is met. Choosing the oil with a greater viscosity is also helpful in improving the dynamic performance of hydrostatic guides. The research work has instructing significance for analyzing and designing the guide with PM flow controller.

A Genetic Based Fuzzy Q-Learning Flow Controller for High-Speed Networks

For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference is introduced in order to facilitate generalization in large state space, and the genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.

Flow control performance evaluation of a tri-electrode sliding discharge plasma actuator

Tri-electrode sliding discharge(TED)plasma actuators are formed by adding a direct current(DC)exposed electrode to conventional dielectric barrier discharge(DBD)plasma actuators.There are three TED modes depending on the polarity and amplitude of the DC supply:DBD discharge,extended discharge and sliding discharge.This paper evaluates the electrical,aerodynamic and mechanical characteristics of a TED plasma actuator based on energy analysis,particle image velocimetry experiments and calculations using the Navier-Stokes equation.The flow control performances of different discharge modes are quantitatively analyzed based on characteristic parameters.The results show that flow control performance in both extended discharge and sliding discharge is more significant than that of DBD,mainly because of the significantly higher(up to 141%)body force of TED compared with DBD.However,conductivity loss is the primary power loss caused by the DC polarity for TED discharge.Therefore,power consumption can be reduced by optimizing the dielectric material and thickness,thus improving the flow control performance of plasma actuators.

Experimental investigation of dynamic stall flow control using a microsecond-pulsed plasma actuator

To alleviate the performance deterioration caused by dynamic stall of a wind turbine airfoil,the flow control by a microsecond-pulsed dielectric barrier discharge(MP-DBD) actuator on the dynamic stall of a periodically pitching NACA0012 airfoil was investigated experimentally.Unsteady pressure measurements with high temporal accuracy were employed in this study,and the unsteady characteristics of the boundary layer were investigated by wavelet packet analysis and the moving root mean square method based on the acquired pressure.The experimental Mach number was 0.2,and the chord-based Reynolds number was 870 000.The dimensionless actuation frequencies F+ were chosen to be 0.5,1,2,and 3,respectively.For the light dynamic regime,the MP-DBD plasma actuator plays the role of suppressing flow separation from the trial edge and accelerating the flow reattachment due to the high-momentum freestream flow being entrained into the boundary layer.Meanwhile,actuation effects were promoted with the increasing dimensionless actuation frequency F+.The control effects of the deep dynamic stall were to delay the onset and reduce the strength of the dynamic stall vortex due to the accumulating vorticity near the leading edge being removed by the induced coherent vortex structures.The laminar fluctuation and Kelvin-Helmholtz(K-H) instabilities of transition and relaminarization were also mitigated by the MP-DBD actuation,and the alleviated K-H rolls led to the delay of the transition onset and earlier laminar reattachment,which improved the hysteresis effect of the dynamic stall.For the controlled cases of F+=2,and F+=3,the laminar fluctuation was replaced by relatively low frequency band disturbances corresponding to the harmonic responses of the MP-DBD actuation frequency.

Traffic flow of connected and automated vehicles at lane drop on two-lane highway: An optimization-based control algorithm versus a heuristic rules-based algorithm

This paper investigates traffic flow of connected and automated vehicles at lane drop on two-lane highway. We evaluate and compare performance of an optimization-based control algorithm(OCA) with that of a heuristic rules-based algorithm(HRA). In the OCA, the average speed of each vehicle is maximized. In the HRA, virtual vehicle and restriction of the command acceleration caused by the virtual vehicle are introduced. It is found that(i) capacity under the HRA(denoted as C_(H)) is smaller than capacity under the OCA;(ii) the travel delay is always smaller under the OCA, but driving is always much more comfortable under the HRA;(iii) when the inflow rate is smaller than C_(H), the HRA outperforms the OCA with respect to the fuel consumption and the monetary cost;(iv) when the inflow rate is larger than C_(H), the HRA initially performs better with respect to the fuel consumption and the monetary cost, but the OCA would become better after certain time. The spatiotemporal pattern and speed profile of traffic flow are presented, which explains the reason underlying the different performance. The study is expected to help for better understanding of the two different types of algorithm.

Numerical Investigation of Flow Separation Control over an NACA0018 Airfoil Using Sweeping Jet Actuator

As an active flow control technology and with the advantages of no moving components, the Sweeping jet actuator has become a hotspot in the field of flow control. However, the linear relationship between oscillation frequency and momentum coefficient in a sweeping jet actuator makes it difficult to determine the dominant factors that affect control effectiveness. Decoupling the oscillation frequency and momentum coefficient, as well as determining the control mechanism, is the focus of studying the sweeping jet actuator. In this study, a novel sweeping jet actuator is designed using synthetic jets instead of feedback channels and applied to the flow separation control of NACA0018 airfoil. This article studies the control effect under three oscillation frequencies of F+ = f × c/U∞ = 1, 10, 100 and three momentum coefficients of Cμ = 0.45%, 0.625%, 0.9%. The numerical results indicate that all three oscillation frequencies have good control effects on flow separation, and the control effect is best when F+ = 1, with the maximum lift coefficient increasing by approximately 14% compared to the other two cases. And the sweeping jet actuator has a better ability to control flow separation as the momentum coefficient increases. By decoupling the characteristics of the sweeping jet actuator and conducting numerical analysis of the flow control effect, it will promote its better engineering application in the field of flow control. .

Neuro-Fuzzy Based Interline Power Flow Controller for Real Time Power Flow Control in Multiline Power System

This article investigates the power quality enhancement in power system using one of the most famous series converter based FACTS controller like IPFC (Interline Power Flow Controller) in Power Injection Model (PIM). The parameters of PIM are derived with help of the Newton-Raphson power flow algorithm. In general, a sample test power system without FACTs devices has generated more reactive power, decreased real power, more harmonics, small power factor and poor dynamic performance under line and load variations. In order to improve the real power, compensating the reactive power, proficient power factor and excellent load voltage regulation in the sample test power system, an IPFC is designed. The D-Q technique is utilized here to derive the reference current of the converter and its D.C link capacitor voltage is regulated. Also, the reference voltage of the inverter is arrived by park transformation technique and its load voltage is controlled. Here, a sample 230 KV test power system is taken for study. Further as the conventional PI controllers are designed at one nominal operating point they are not competent to respond satisfactorily in dynamic operating conditions. This can be circumvented by a Fuzzy and Neural network based IPFC and its detailed Simulink model is developed using MATLAB and the overall performance analysis is carried out under different operating state of affairs.

A grouping strategy for reinforcement learning-based collective yawcontrol of wind farms

Reinforcement learning(RL)algorithms are expected to become the next generation of wind farm control methods.However,as wind farms continue to grow in size,the computational complexity of collective wind farm control will exponentially increase with the growth of action and state spaces,limiting its potential in practical applications.In this Letter,we employ a RL-based wind farm control approach with multi-agent deep deterministic policy gradient to optimize the yaw manoeuvre of grouped wind turbines in wind farms.To reduce the computational complexity,the turbines in the wind farm are grouped according to the strength of the wake interaction.Meanwhile,to improve the control efficiency,each subgroup is treated as a whole and controlled by a single agent.Optimized results show that the proposed method can not only increase the power production of the wind farm but also significantly improve the control efficiency.

袋型阻尼密封动力学特性双控制体Bulk Flow模型

为快速准确预测袋型阻尼密封泄漏特性和动力学特性,针对传统单控制体Bulk Flow模型预测精度低、无法预测交叉动力系数的问题,提出了袋型阻尼密封双控制体Bulk Flow模型和动力学特性数值预测方法,并开发了计算程序。首先,依据边界层理论,将袋型密封腔室划分为两个控制体,推导了控制体的连续性、周向动量和能量方程,引入Swamee-Jain和Takahashi方程,计算流体-壁面间和流体-流体间的周向黏性摩擦力;其次,采用牛顿-拉夫森算法和摄动分析法分别求解0阶和1阶控制方程,获得各刚度、阻尼动力特性系数;然后,通过与袋型阻尼密封泄漏量和动力特性系数的实验值、单控制体Bulk Flow模型和非定常计算流体动力学(CFD)数值结果进行比较,验证了模型和方法的准确性和可靠性;最后,研究了转子转速(10 000、15 000、20 000 r/min)和预旋比(0.067、0.724、0.997)对袋型阻尼密封动力学特性的影响。结果表明:所发展的模型和方法具有计算速度快、预测精度高(泄漏量预测误差小于6%,动力特性系数预测误差小于38%)的优点;转子转速和进口预旋的增大均会导致袋型阻尼密封有效阻尼显著减小,穿越频率显著增大,易诱发轴系失稳。

A New Device for Gas-Liquid Flow Measurements Relying on Forced Annular Flow

A new measurement device,consisting of swirling blades and capsule-shaped throttling elements,is proposed in this study to eliminate typical measurement errors caused by complex flow patterns in gas-liquid flow.The swirling blades are used to transform the complex flow pattern into a forced annular flow.Drawing on the research of existing blockage flow meters and also exploiting the single-phase flow measurement theory,a formula is introduced to measure the phase-separated flow of gas and liquid.The formula requires the pressure ratio,Lockhart-Martinelli number(L-M number),and the gas phase Froude number.The unknown parameters appearing in the formula are fitted through numerical simulation using computational fluid dynamics(CFD),which involves a comprehensive analysis of the flow field inside the device from multiple perspectives,and takes into account the influence of pressure fluctuations.Finally,the measurement model is validated through an experimental error analysis.The results demonstrate that the measurement error can be maintained within±8%for various flow patterns,including stratified flow,bubble flow,and wave flow.

Design of Poiseuille Flow Controllers Using the Method of Inequalities

This paper investigates the use of the method of inequalities （MoI） to design output-feedback compensators for the problem of the control of instabilities in a laminar plane Poiseuille flow. In common with many flows, the dynamics of streamwise vortices in plane Poiseuille flow are very non-normal. Consequently, small perturbations grow rapidly with a large transient that may trigger nonlinearities and lead to turbulence even though such perturbations would, in a linear flow model, eventually decay. Such a system can be described as a conditionally linear system. The sensitivity is measured using the maximum transient energy growth, which is widely used in the fluid dynamics community. The paper considers two approaches. In the first approach, the MoI is used to design low-order proportional and proportional-integral （PI） controllers. In the second one, the MoI is combined with McFarlane and Glover＇s H∞ loop-shaping design procedure in a mixed-optimization approach.

Binary ABR flow control over ATM networks with uncertainty using discrete-time variable structure controller

A binary available bit rate （ABR） scheme based on discrete-time variable structure control （DVSC） theory is proposed to solve the problem of asynchronous transfer mode （ATM） networks congestion in this paper. A discrete-time system model with uncertainty is introduced to depict the time-varying ATM networks. Based on the system model, an asymptotically stable sliding surface is designed by linear matrix inequality （LMI）. In addition, a novel discrete-time reaching law that can obviously reduce chatter is also put forward. The proposed discrete-time variable structure controller can effectively constrain the oscillation of allowed cell rate （ACR） and the queue length in a router. Moreover, the controller is self-adaptive against the uncertainty in the system. Simulations are done in different scenarios. The results demonstrate that the controller has better stability and robustness than the traditional binary flow controller, so it is good for adequately exerting the simplicity of binary flow control mechanisms.