Flow Control Scheme Research Articles

Intermittent Flow Control Schemes for Heat Stress Mitigation in Lactating Sows on a Floor Cooling Pad

The Purdue hog cooling pad has previously been demonstrated to mitigate heat stress in lactating sows by conductively transferring heat from a sow to cool water running through an integral heat exchanger. Coolant effectiveness, which describes how much heat is removed per volume of water flushed through the cooling pad, is used to compare the operation under varying conditions. Past studies have indicated that the intermittent flow of cooling water achieves a greater coolant effectiveness than continuous flow operational schemes. An electronic control system was implemented with the current cooling pad design to allow for the automated control of a solenoid valve to create the intermittent flow conditions. All testing was performed using 18 ± 1 °C inlet water. Potential control schemes were categorized into two groups, temporal and temperature threshold. The temporal schemes opened the solenoid for 30 s, enough time to flush the entire contents of the cooling coils, before closing for 3, 6, or 9 min. The temperature threshold control schemes utilized feedback from thermal probes embedded beneath the surface of the cooling pad to open the solenoid for 30 s, when a maximum surface temperature was detected. Trigger temperatures of 28.0, 29.5, or 31.0 °C were used. The temperature threshold control schemes achieved greater heat transfer rates (348, 383, 268 W) compared to the temporal control schemes (324, 128, 84 W). The cooling effectiveness for all control schemes ranged from 46.6 to 64.7 kJ/L. The tested intermittent flow control schemes in this study achieved greater cooling effectiveness than continuous flow systems from previous studies (time: 51 kJ/L; temperature: 61 kJ/L; steady: 5.8 kJ/L), although the temporal control schemes exhibited lower heat transfer rates (time: 180 W; temperature: 330 W; steady: 305 W).

Simulation-based adaptive optimization for passenger flow control measures at metro stations

Effective passenger flow control measures are essential for the safe operation of metro stations. Existing in-station control measures include adjusting the operation mode of escalators and setting up temporary fences. However, in practice, metro operators often adopt fixed operation modes during fixed periods, indicating that the current passenger flow control measures at metro stations are overly rigidified. Therefore, developing an adaptive control strategy to constantly balance the wildly fluctuating passenger flow and optimize the operation performance is a key issue in current research. In this study, transportation efficiency and congestion risk are selected as evaluation objectives for passenger transportation risk, and passenger flow feature, station structure, and passenger flow control measures are considered key influential factors. Subsequently, an adaptive optimization method integrating simulation and data interpolation is proposed. The software Legion is used to conduct 150 orthogonal simulations, and prediction models for passenger transportation risk are obtained by performing data interpolation on the simulation results. Finally, taking a certain metro station as a case study, the optimal passenger flow control strategy under any passenger flow composition is obtained by scenario acquisition, risk identification, and adaptive decision-making. The results show that setting up temporary fences can reduce the passenger density near the fare gates, while adjusting the running direction of escalators can reduce overcrowding on the platform. Under varying passenger flow composition, the optimal strategy for the current scenario can be obtained, controlling passenger transportation risk within an acceptable range and providing assistance for metro operators in decision-making.

The optimization algorithm of intelligent transportation systems based on reinforcement learning

With the acceleration of urbanization and the increase in traffic load, traditional traffic management methods struggle to cope with the complexity of modern traffic conditions. Intelligent Transportation Systems (ITS), utilizing modern information technology and artificial intelligence, have improved the efficiency and safety of transportation systems. Reinforcement Learning (RL), as an adaptive optimization method, can dynamically adjust traffic signals and flow control strategies through trial and error and reward mechanisms, optimizing traffic flow management and signal control. This paper investigates the optimization algorithms of intelligent transportation systems based on reinforcement learning, including their design, application, and performance evaluation. Research indicates that RL optimization algorithms can significantly enhance the organizational performance of transportation systems, increasing the efficiency and flexibility of traffic management. Empirical analysis verifies the effectiveness of the algorithm, and future improvement directions are proposed.

Effects of Perforated Plates on Shock Structure Alteration for NACA0012 Cascade Configurations

To alleviate the shock boundary layer interaction adverse effects, various active or passive flow control strategies have been investigated in the literature. This research sheds light on the behavior of perforated plates as passive flow control techniques applied to NACA0012 airfoils in cascade configurations. Two identical perforated plates with shallow cavities underneath are accommodated on the upper and lower surfaces of each airfoil in the cascade arrangement. Six different cascade arrangements, including a baseline configuration with no control applied, are additively manufactured, with different perforated plate orifice sizes in the range of 0.5–1.2 mm. A high-speed wind tunnel with Schlieren optical diagnosis and wall static pressure taps is used to investigate the changes in the shock waves pattern triggered by the perforated plates. Steady 3D density-based numerical simulations in Ansys FLUENT are conducted for further analysis and validation. In the cascade configuration, the perforated plates alter the shock structure, and the strong normal shock wave is replaced by a weaker X-type shock structure. Eventually, a 1% penalty in overall total pressure loss is induced by the perforated plates because of the negative loss balance between the reduced shock losses and the enhanced viscous losses. Further studies on perforated plate geometrical features are needed to improve this outcome in a cascade arrangement.

Enhancing stability and performance of flexible membrane structures in wake flows through jet flow control

This study investigates jet flow control on flexible membrane structures placed in the wake of a stationary cylinder to enhance performance and stability. Flexible membranes, found in both nature and engineering, often face nonlinear disturbances where passive deformation is insufficient. Inspired by adaptive fish fins, we explore active flow control strategies using a high-fidelity fluid–structure interaction solver to simulate the dynamics of a flexible membrane downstream of a cylinder. High-momentum jet flows with different momentum coefficients are applied at membrane leading edge to modulate the boundary layer flow features. Numerical simulation results reveal that jet flow control can weaken the wake interference effect on the membrane dynamics, resulting in lift improvement and flow-induced vibration suppression. The flow separation within the boundary layer is suppressed by high-momentum jet flows, thereby enhancing lift performance and stability. The reason of the flow-induced vibration suppression is attributed to the redistribution of the vibration energy in high-order structure modes excited by jet flows. Our results demonstrate that jet control has great potential for optimizing the performance and stability of flexible membrane structures in complex flow environments, providing valuable insights into the design of next-generation intelligent underwater vehicles and ships with flexible membrane propulsion systems.

Comparative Analysis of Two Robust Strategies for an Angular Velocity Control System

In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and structured singular value (Mu) controllers have been designed. The multiplicative uncertainty was analyzed to assess the robustness of the feedback control system where six parameters were considered uncertain within a range of +10%. The robust stability and performance requirements of the closed-loop angular velocity control system were assessed in the frequency domain. The time response of the system showed that the system is stable with both (RPID) and (Mu) controllers. The Mu controller can handle parametric uncertainty without requiring pure integral term which is a significant advantage over the (RPID) controller. On the other hand, the (RPID) controller could achieve robust performance, making it much suitable for systems that require high levels of performance and robustness. In summary, the the (RPID) and Mu controller is a more comprehensive solution for ensuring the best performance of a system. The results for each (RPID) and Mu-controllers showed no oscillations, zero percent overshoot. Each of the (RPID) and Mu-controllers meets the robustness needs. Index Terms— Pump, valve, inlet throttling valve, angular velocity control, robust control, Mu synthesis, D-K iteration, RPID controller .

The Response of Turbulent Channel Flow to Standing Wave-like Wall Motion

The effect of wall deformations on wall turbulence is a topic of fundamental importance for the advancement of flow control strategies aimed at reducing the frictional drag. Dynamic wall deformations in the form of wall-normal of in-plane oscillations represents an area that is yet to be fully explored, and that can open a new realm of drag control strategies, as well as provide fresh insights into the structure of wall turbulence. In this study, we present several results from direct numerical simulations aimed at understanding the response of wall turbulence to standing wave-like wall motion, arranged in a checkerboard pattern. More specifically, here we target a low Reynolds number turbulent channel flow, featuring standing wave-like dynamic wall deformations on both bottom and top walls, with parameterizations in terms of the frequency of oscillations, roughness height, and spacing. We quantify the effect that this type of wall motion can have on the skin friction drag, various turbulent statistics, and turbulent flow structures. In addition, taking advantage of the periodicity and the symmetry of the flow, an improved phase-averaging procedure is introduced, which enhances the smoothness of the data. The results show that this type of dynamic wall deflection can have a significant effect on the turbulent flow in proximity to the wall, and that the variation of the spatial wavenumbers of the wall deflections can make a big difference. A slight total drag reduction, in the order of 2%, was observed for some combinations of wavenumbers and frequencies, especially for the highest streamwise wavenumber case.

A comprehensive study of recent studies on the efficiency of axial flow turbines with an investigation on blade profile modifications in stator and rotor assemblies

Axial flow turbines are crucial in energy production and propulsion across diverse applications. As global energy needs rise, optimizing turbine efficiency is paramount. This review delves into the aerodynamic design of turbine blades, specifically examining blade profile modifications in both stator and rotor assemblies of state-of-the-art models proposed in the studies from 2019 to 2024. The focus is on mitigating performance discrepancies between idealized simulations and real-world applications, which present significant challenges such as inconsistencies in computational fluid dynamics (CFD) predictions and manufacturing constraints. Key findings from this review highlight a potential efficiency gain of 1%–3% through optimal blade designs that reduce incidence losses, secondary flows, and tip vortex formation. Advanced modeling techniques, including high-fidelity, multi-objective optimization with machine learning, are evolving to better predict and enhance turbine performance. However, gaps remain in system-level integration and the limited experimental data restricts comprehensive validation of these new designs. The insights from this review will aid the research community by identifying critical areas for future investigation, such as integrating blade aerodynamics with heat transfer and structural mechanics. Further, it emphasizes the need for exploring combinations of passive and active flow control strategies to fully harness the benefits of blade profile enhancements. These efforts are crucial for achieving substantial improvements in turbine efficiency, which are essential for meeting the growing demands for sustainable and efficient energy production.

Numerical investigation of drag reduction effects on a track bicycle fork using wings with a wavy leading edge

AbstractReynolds‐averaged Navier–Stokes (RANS) and large‐eddy simulations (LES) of the flow around wings with a wavy leading edge (WLE) are conducted in order to assess the capabilities of a passive flow control strategy for drag reduction. The intended application is indoor track cycling with controlled flow conditions. A section of a single fork rod is investigated in order to make the numerical simulations feasible. The present study reveals that net drag reduction is possible by a nonsinusoidal modification of the leading edge of the wing. However, the drag reduction effect remains limited to a few percent. While RANS and LES yield the same drag coefficient for a reference case, RANS underestimates the drag reduction effect for a longer wing and the WLE cases, but exhibits otherwise a qualitatively similar trend as the LES. With the aid of RANS, an optimal geometry is obtained defined by the wavelength‐to‐chord length ratio of and the amplitude‐to‐chord length ratio of . Corresponding LES results give an indication of the origin of drag reduction by a hampered vortex shedding. The generation of smaller and more streamwise oriented vortical flow structures at the trailing edge and behind the WLE wing is correlated with significantly reduced lift fluctuations and drag reduction.

Optimizing Aerofoil Design: A Comprehensive Analysis of Aerodynamic Efficiency through CFD Simulations and Wind Tunnel Experiments

This study explores the aerodynamic properties of different aerofoil shapes and their performance under varying flow conditions to identify the most efficient design based on lift-to-drag ratio, stall behaviour, and overall aerodynamic efficiency. Using Computational Fluid Dynamics (CFD) simulations, several aerofoil profiles were analysed at different angles of attack and flow speeds. These simulations were validated through wind tunnel experiments, offering a comprehensive understanding of aerofoil performance in real-world scenarios. The combination of CFD analysis and wind tunnel testing enabled a thorough assessment of each aerofoil shape, leading to the discovery of a specific aerofoil with a high lift-to-drag ratio and stable performance at high angles of attack. These results have significant implications for the design of wings and blades in aerospace and aeronautical applications, improving fuel efficiency and performance in both aviation and wind energy sectors. Additionally, dynamic roughness shows potential in reducing separation bubbles, but further investigation is needed to assess its effectiveness at higher angles of attack and elevated Reynolds numbers. Understanding the scalability and practical application of dynamic roughness in real-world scenarios is essential. Current research on surface modifications like dimples and riblets lacks optimized configurations for varying conditions. More research is needed to understand the interaction between surface geometries and the boundary layer, particularly at higher angles of attack and Reynolds numbers. Combining experimental and numerical methods can provide a comprehensive understanding of flow control techniques. The limited research on applying flow control strategies to wind turbine blades indicates a significant opportunity to improve wind energy efficiency. Future studies should focus on optimizing multiple techniques and addressing practical challenges, such as durability, cost-effectiveness, and integration into existing systems. Investigating the cost-effectiveness and durability of these modifications for long-term use will be vital for their successful adoption in the industry. Expanding research to include the effects of environmental factors like temperature and humidity will offer a more complete understanding of flow control in various operating conditions. By addressing these gaps, advancements in aerodynamic performance can be achieved, benefiting the aerospace and wind energy sectors.

A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system

Predictive real-time control (RTC) strategies are usually more effective than reactive strategies for the intelligent management of urban stormwater storage systems. However, it remains a challenge to ensure the practicality of RTC strategies that use accessible, non-idealized predictive information while improving their efficiency for successive rainfall events instead of specific phases. This study developed a predictive fuzzy logic and rule-based control (PFL-RBC) approach to address the continuous control of individual storage systems. This approach incorporates total rainfall depth forecast information with an intra-storm fuzzy logic system to optimize peak flow control and several rule-based strategies for pre-storm water detention, reuse, and release control. Computational experiments were conducted using a storage tank case study to test the proposed approach under various rainfall conditions and storage sizes. The results showed that PFL-RBC outperformed static rule-based control in infrequent design storms and realistic continuous rainfall events, reducing flood peaks and volumes by 55 %∼87 % and 7 %∼20 %, respectively, and significantly increasing water detention time and reuse volume. Meanwhile, PFL-RBC required less predictive information to achieve a 6 %∼15 % advantage in peak flow control compared to optimized model predictive control. More importantly, PFL-RBC was reliable in the face of input uncertainty, with <25 % performance loss for water quantity control when the realistic forecast error ranged from -50 % to +50 %. These findings suggest that the proposed approach has great potential to enhance the efficiency and practicality of stormwater storage operations.

Passive flow control of a Francis turbine operating in sand-laden rivers for mitigating sediment erosion

In a typical Francis turbine operating in sand-laden rivers, owing to its complicated geometry and variable operating conditions, vortex structures appear and cause severe erosion damage to turbine components. Here, we present a bioinspired method to mitigate severe sediment erosion on Francis turbines. The proposed method includes a passive flow control strategy using biomimetic convex domes for the inter-blade vortex, a major contributor to severe sediment erosion on the turbine runner. The effects of biomimetic convex domes on sediment erosion are investigated through numerical simulations and experiments. The results indicate that biomimetic convex domes significantly reduce the impact velocity and accretion rate of the particles, eventually reducing sediment erosion by at least 50 %. The mechanism underlying the effect of convex domes on sediment erosion is their inhibition of the development of the inter-blade vortex. The convex domes induce small-scale vortices from the blade boundary layer. When located in the nascent region of the inter-blade vortex, the small-scale vortex effectively inhibits its formation. Moreover, convex domes placed in severe erosion areas can accelerate the dissipation process of the inter-blade vortex.

Numerical Investigation of Aero-Optical Distortions from High-Speed Turbulent Boundary Layers

Wall-modeled large-eddy simulations of turbulent boundary-layer flows over a flat plate at Mach 3.5, 7.87, and 13.64 were carried out, and the aero-optical distortions resulting from density fluctuations were investigated. The conditions for the Mach 3.5 case match those of a direct numerical simulation in the literature. The Mach 7.87 conditions are representative of the Hypersonic Wind Tunnel at Sandia National Laboratories, and the Mach 13.64 conditions match those of the Arnold Engineering Development Complex Hypervelocity Tunnel 9. The wall-modeled large-eddy simulations were validated using available experimental and DNS reference data. The normalized root-mean-square optical path difference for all three cases is in good agreement with respective data obtained from reference direct numerical simulations and experiments (within 1.53% for M∞=3.5, 1.25% for M∞=7.87, and 12% for M∞=13.64, compared to numerical data). Above M∞=5.0, the normalized path difference obtained from the simulations is above the value predicted by a semi-analytical relationship by Notre Dame University. With increasing Mach number, the bulk contribution to the total optical distortion shifts toward the boundary-layer edge. In addition, a proper orthogonal decomposition reveals that the nature of the dominant density fluctuations, which are located near the boundary-layer edge, changes from three-dimensional to two-dimensional. Understanding how the coherent structures contribute to the optical path difference may pave a way toward devising active flow control strategies geared toward a reduction of the optical path difference.

Comparison study of two control strategies for the small pressurized water reactor

The control strategy has a significant impact on the control performance of the reactor system. This paper investigates the feedwater flow and steam flow control strategies for small pressurized water reactors. First, the mathematical model of the SPWR Nuclear Steam Supply System is introduced. Second, a dual-constant control strategy was proposed, and the feedwater flow rate and steam pressure control systems under the two control modes were designed. Moreover, a steam bypass control system was designed to avoid excessive steam pressure under the feedwater flow control mode, and the reactor power and pressurize control systems were introduced. Simulation results indicate that the two control modes both meet the SPWR control requirements. However, the feedwater flow control mode has better reactor coolant temperature and steam pressure control performances during the load rejection transient, owing to the timely discharge of heat from the reactor coolant system through the steam bypass system.

A digital twin-based traffic light management system using BIRCH algorithm

Urban transportation networks are vital for the economic and environmental well-being of cities and they are faced with the integration of Human-Driven Vehicles (HVs) and Connected and Autonomous Vehicles (CAVs) challenge. Most of the traditional traffic management systems fail to effectively manage the dynamic and complex flows of mixed traffic, mainly because of large computational requirements and the restrictions that control models of traffic lights directly based on extensive and continuous training data. Most of the times, the operational flexibility of CAVs is severely compromised for the safety of HVs, or CAVs are given high priority without taking into account the efficiency of HVs leading to lower performance, especially at low CAV penetration rates. On the other hand, the existing adaptive traffic light approaches were usually partial and could not adapt to the real-time behaviors of the traffic system. Some systems operate with inflexible temporal control plans that cannot react to variations in traffic flow or use adaptive control strategies that are based on a limited set of static traffic conditions. This paper presents a novel traffic light control approach utilizing the BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) clustering algorithm combined with digital twins for a more adaptive and efficient system. The BIRCH is effective in processing large datasets because it clusters data points incrementally and dynamically into a small set of representatives. The suggested method does not only enable better simulation and prediction of traffic patterns but also makes possible the real-time adaptive control of traffic signals at signalized intersections. It also improves traffic flow, reduces congestion, and minimizes vehicle idling time by adjusting the green and red light durations dynamically based on both real-time and historical traffic data. This approach is assessed under different traffic intensities, which include low, moderate, and high, while efficiency, fuel consumption, and the number of stops are being compared with the traditional and the existing adaptive traffic management systems.

Learning active flow control strategies of a swept wing by intelligent wind tunnel

An intelligent wind tunnel using an active learning approach automates flow control experiments to discover the aerodynamic impact of sweeping jets on a swept wing. A Gaussian process regression model is established to study the jet actuator’s performance at various attack and flap deflection angles. By selectively focusing on the most informative experiments, the proposed framework was able to predict 3,721 wing conditions from just 55 experiments, significantly reducing the number of experiments required and leading to faster and cost-effective predictions. The results show that the angle of attack and flap deflection angle are coupled to affect the effectiveness of the sweeping jet. Meanwhile, increasing the jet momentum coefficient can contribute to lift enhancement; a momentum coefficient of 3% can increase the lift coefficient by at most 0.28. Additionally, the improvement effects are more pronounced when actuators are placed closer to the wing root.

A Networked Meta-Population Epidemic Model with Population Flow and Its Application to the Prediction of the COVID-19 Pandemic.

This article addresses the crucial issues of how asymptomatic individuals and population movements influence the spread of epidemics. Specifically, a discrete-time networked Susceptible-Asymptomatic-Infected-Recovered (SAIR) model that integrates population flow is introduced to investigate the dynamics of epidemic transmission among individuals. In contrast to existing data-driven system identification approaches that identify the network structure or system parameters separately, a joint estimation framework is developed in this study. The joint framework incorporates historical measurements and enables the simultaneous estimation of transmission topology and epidemic factors. The use of the joint estimation scheme reduces the estimation error. The stability of equilibria and convergence behaviors of proposed dynamics are then analyzed. Furthermore, the sensitivity of the proposed model to population movements is evaluated in terms of the basic reproduction number. This article also rigorously investigates the effectiveness of non-pharmaceutical interventions via distributively controlling population flow in curbing virus transmission. It is found that the population flow control strategy reduces the number of infections during the epidemic.

A Mixed Traffic Flow Capacity Vehicle Flow Control Strategy Combining Vehicle Networking Technology and Autonomous Driving Technology

A Mixed Traffic Flow Capacity Vehicle Flow Control Strategy Combining Vehicle Networking Technology and Autonomous Driving Technology

Transition delay in a Mach 6 boundary layer using steady blowing and suction strips

Direct numerical simulations (DNS) were carried out to investigate flow control for transition delay using steady blowing/suction strips at the wall of a flared cone at Mach 6 and zero angle of attack. For the numerical investigations of the transition control strategy, the flared cone geometry and the flow conditions of the experiments in the Boeing/Air Force Office of Scientific Research (AFOSR) Mach 6 Quiet Tunnel (BAM6QT) at Purdue University were chosen. For the DNS, transition was initiated by introducing random disturbances at the inflow of the computational domain, emulating ‘natural’ transition in wind-tunnel experiments caused by free-stream noise. In both wind-tunnel experiments and numerical simulations, streamwise ‘hot’ streaks were found on the surface of the flared cone, which are caused by a nonlinear interaction of an axisymmetric second-mode wave and a pair of oblique waves of the same frequency (‘fundamental resonance’). The objective of the flow control strategy proposed here is to delay the transition onset, and thus mitigate the negative consequences associated with the nonlinear transition stages, i.e. the development of hot streaks and large wall-pressure amplitudes that were observed in experiments and DNS. Our previous so-called ‘controlled’ transition simulations have shown that flow control using steady blowing and suction strips can lead to a significant delay of the hot streak development on the surface of the flared cone. The simulation results presented in this paper show that this flow control strategy remains effective, even in a natural transition scenario characterized by broadband disturbances.

Deflection and control of the mixing region in membraneless vanadium micro redox flow batteries: Modeling and experimental validation

Membraneless micro redox flow batteries operate within the laminar flow regime to mitigate the convective mixing between catholyte and anolyte. The absence of an ion-exchange membrane reduces manufacturing costs and overall cell resistance, thereby enhancing battery performance. However, it also poses a new challenge: the precise control of the thin mixing layer established between the two co-flowing electrolytes. Undesired displacements of the mixing region lead to increased crossover losses and significant liquid transfer between tanks. This work addresses the deflection of the mixing region under varying flow conditions, considering electrolyte viscosity variations due to the changes in the local state of charge arising during battery operation. This is achieved through a combination of mathematical analysis, numerical simulations, and experimental results. The conservation equations and non-dimensional parameters governing the problem are first written and discussed. The model is then integrated numerically incorporating different inlet and outlet boundary conditions to simulate the effect of various flow control strategies. Next, the numerical results are validated against experimental realizations of the flow. Finally, three case studies are presented and discussed. This work highlights the relevance of variable viscosity in the operation of co-laminar membraneless micro redox flow batteries, and proposes for the first time feasible control methods to mitigate undesired disturbances in the hydraulic circuit, thereby minimizing crossover losses.