Wake Research Articles

Spanwise flow control of bridge deck using Bayesian optimization technique

This study introduces a novel framework in bridge wind engineering, merging Bayesian optimization (BO) with computational fluid dynamics (CFD) to optimize spanwise control parameters for the Great Belt bridge deck. This study leverages the BO framework for an automated, data-driven adjustment of the blow-suction sinusoidal spanwise perturbation (SSP) parameters at the leading and trailing edges of bridge decks. The primary aim is to finely tune the SSP control, stimulating the secondary instability in the spanwise vortices in the wake flow field. This process effectively generates streamwise vortices to suppress the spanwise ones, significantly mitigating fluctuating aerodynamic forces and vortex-induced vibration of the bridge deck, improving its aerodynamic stability. The results demonstrate that the BO framework-driven SSP control method can efficiently reduce the aerodynamic forces while finding the optimal SSP wavelength. Furthermore, through the optimization of multi-parameter variables in SSP control, the optimal combination of amplitudes and wavelengths for the SSP are achieved. Additionally, it was found that blow-suction at the trailing edge of the bridge deck is more effective than at the leading edge.

Characterization of Wind Turbine Blade Deformation and Wake Flow Field with Different Numbers of Lay-Up Layers

The change in the composite lay-up method affects the blade stiffness, which in turn affects the structural dynamic and aerodynamic characteristics, but the influence law is not yet clear. In this paper, two-way fluid–structure coupling is used to study wind turbine blades with different numbers of lay-up layers. The analysis results show the following: (1) With the increase in the number of pavement layers, the maximum deformation of the blade tip decreases, the magnitude of the decrease also decreases gradually, and the growth trend of deformation along the blade spreading direction is gradually flattened. (2) The maximum stress–strain of the root of the blade gradually decreases, the tip of the blade is the opposite of the blade, the unevenness of the distribution of the stress–strain of the surface of the blade is gradually slowed down, and the concentration area is shifted back. (3) The different numbers of pavement layers affect the turbulence intensity of the blade in the flow field space. Herein, the spatial distribution trend of turbulence intensity in the flow field of wind turbine blades with different numbers of layers is basically the same, and the trend of turbulence intensity changes is gentle when the number of layers is increased. (4) The amount of the tip vortex in the wake stream of the wind turbine decreases, and the decay rate of the center vortex increases. A reasonable lay-up scheme can improve the deformation and stress of the blade, extend the service life of the blade, promote airflow mixing, and enhance the energy conversion efficiency.

STUDY OF AERODYNAMIC NOISE OF PROPELLER CONSIDERING THE INFLUENCE OF BOUNDARY SURFACE USING CFD METHOD

This article focuses on the aerodynamic and acoustic characteristics of both an isolated propeller model and a propeller - boundary surface model. The study uses the Reynolds-averaged Navier-Stokes (RANS) method combined with Computational Fluid Dynamics techniques to analyze the flow field and wake flow behind the propeller and to determine its basic aerodynamic coefficients. The pressure on the surface of the propeller and boundary surface is used as input for the noise calculations. An acoustic analogy method, based on the Farassat 1A formulation derived from the Ffowcs Williams-Hawkings (FW-H) equation, is employed to calculate the propagation of noise from the surfaces of the propeller and boundary surface to designated positions (microphones). The research results lead to some significant conclusions drawn by the authors.

Quantification analysis of high-speed train aerodynamics with geometric uncertainty of streamlined shape

Purpose This study aims to get a better understanding of the impact of streamlined high-speed trains (HSTs) with geometric uncertainty on aerodynamic performance, as well as the identification of the key parameters responsible for this impact. To reveal the critical parameters, this study creates a methodology for evaluating the uncertainty and sensitivity of drag coefficient induced by design parameters of HST streamlined shapes. Design/methodology/approach Bézier curves are used to parameterize the streamlined shape of HSTs, and there are eight design parameters required to fit the streamlined shape, followed by a series of steady Reynolds-averaged Navier–Stokes simulations. Combining the preparation work with the nonintrusive polynomial chaos method results in a workflow for uncertainty quantification and global sensitivity analysis. Based on this framework, this study quantifies the uncertainty of drag, pressure, surface friction coefficient and wake flow characteristics within the defined ranges of streamline shape parameters, as well as the contribution of each design parameter. Findings The results show that the change in drag reaches a maximum deviation of 15.37% from the baseline, and the impact on the tail car is more significant, with a deviation of up to 23.98%. The streamlined shape of the upper surface and the length of the pilot (The device is mounted on the front of a train’s locomotive and primarily serves to remove obstacles from the tracks, thereby preventing potential derailment.) are responsible for the dominant factors of the uncertainty in the drag for HSTs. Linear regression results show a significant quadratic polynomial relationship between the length of the pilot and the drag coefficient. The drag declines as the length of the pilot enlarges. By analyzing the case with the lowest drag, the positive pressure area in the front of pilot is greatly reduced, while the nose tip pressure of the tail is enhanced by altering the vortices in the wake. The counter-rotating vortex pair is significantly attenuated. Accordingly, exerts the impacts caused by geometric uncertainty can be found on the wake flow region, with pressure differences of up to 900 Pa. The parameters associated with the shape of the upper surface contribute significantly to the uncertainty in the core of the wake separation region. Originality/value The findings contribute to a better understanding of the impact of streamlined HSTs with geometric uncertainty on aerodynamic performance, as well as the identification of the key parameters responsible for this impact. Based on this study, future research could delve into the detailed design of critical areas in the streamlined shape of HSTs, as well as the direction of shape optimization to more precisely and efficiently reduce train aerodynamic drag under typical conditions.

Linear stability and spectral modal decomposition of three-dimensional turbulent wake flow of a generic high-speed train

Linear stability and spectral modal decomposition of three-dimensional turbulent wake flow of a generic high-speed train

Wind Turbine Wake Regulation Method Coupling Actuator Model and Engineering Wake Model

The wake effect is one of the main factors affecting the power generation of wind farms. Wake regulation is often used to reduce the wake interference between wind turbines. Accurate assessment of the wake flow of wind turbine is essential to wake regulation. Engineering wake models are widely used for rapid evaluation of the wake at present due to lower computational resource cost. However, the selection of empirical parameters of the wake model has significant influence on the prediction accuracy, especially in the case of yaw. The actuator model based on CFD simulation has less dependence on empirical parameters and higher simulation accuracy. However, the computational cost is too high for wake regulation for large wind farms. This paper proposed an improved wake regulation method that combines the advantages of the actuator line model (ALM) method and the engineering wake mode. The simulation results of the ALM is used to calibrate the empirical parameters of the engineering wake model. The calibrated wake model can be used to optimize the yaw angle of wind turbines during wake regulation. The accuracy of two models is compared using wind tunnel experimental data. The ALM results give better agreement to the experimental data. The Horns Rev wind farm case is used for the coupled method verification. The power generation increase using the engineering wake model is obviously greater than that of the ALM. After calibrating the wake model, the gap between the two power predictions is greatly narrowed, which proves the effectiveness of the proposed method. The proposed coupling method can be used to improve the credibility of the wake regulation with affordable computational cost.

Ventilation strategy for particulate matter control in subway stations

Particulate matter severely affects human health, and its migration is closely related to human walking and ventilation. It is essential to select an appropriate ventilation strategy to control the particulate matter caused by cluster passengers walking. In this study, cluster passengers walk in the narrow passage of a subway station. Large eddy simulation (LES) was used to study the influence of cluster passengers walking on the transmission of particulate matter under ventilation conditions involving upper exhaust and lower exhaust. The risk of passengers exposure was analyzed by comparing the exposure levels of particulate matter at different heights under the effect of human disturbance. The results show that the amount of particulate matter near the legs is greatest during human walking. Clustered passengers disturbance airflow induces particulate matter to rise to the breathing zone, which increases the risk of human exposure. Lower-side exhaust conditions are more conducive to the discharge and control of particulate matter. The disturbance of cluster passengers enhances the continuous transmission of particulate matter in the wake flow. This study is applicable to traffic hubs and other public places where passengers gather, the ventilation of the upper side exhaust has better control effect on particulate matter caused by passengers wake flow.

Numerical investigation of noise reduction of a pump-jet propulsor using porous metal

A novel strategy for noise reduction in pump-jet propulsor (PJP) is proposed through the design of porous metal trailing edges on stator blades. The interference between stator wake vortices and rotor blades is one of the primary mechanisms for noise generation in PJP. The goal is to use a porous medium to diminish the intensity of turbulent vortices behind the stator blades, control the interaction between these shedding vortices and the rotor blades downstream of the stator, and ultimately suppress the rotor noise generation source. Large eddy simulation and acoustic analogy analysis of the entire propulsion system based on the Ffowcs-Williams and Hawkings equation are performed. It is found that with the use of porous stator trailing edges, the wake flow pattern of the stator is notably altered, the strong impact of the turbulent vortices on the rotor blades is weakened, and the wall pressure fluctuations on the rotor blades and duct are significantly reduced. As a result, the far-field radiation noise and tonal noise are both effectively reduced, with the maximum reduction in total and tonal sound pressure levels reaching 3.8 dB and 12.53 dB, respectively, corresponding to percentage reductions of 6.0% and 21.69%. These findings demonstrate that porous media have great potential for practical engineering applications in PJP noise control.

Stiefel manifold interpolation for non-intrusive model reduction of parameterized fluid flow problems

Many engineering problems are parameterized. In order to minimize the computational cost necessary to evaluate a new operating point, the interpolation of singular matrices representing the data seems natural. Unfortunately, interpolating such data by conventional methods usually leads to unphysical solutions, as the data live on manifolds and not vector spaces. An alternative is to perform the interpolation in the tangent space to the Grassmann manifold to obtain interpolated spatial modes. Temporal modes are afterwards determined via the Galerkin projection of the high-fidelity model onto the interpolated spatial basis. This method, which is known for some fifteen years, is intrusive. Recently, Oulghelou and Allery (JCP, 2021) have proposed a non-intrusive approach (equation-free), but requiring the resolution of two low-dimensional optimization problems after interpolation. In this paper, a non-intrusive alternative based on Interpolation on the Tangent Space of the Stiefel Manifold (ITSSM) is presented. This approach has the advantage of not requiring a calibration phase after interpolation. To assess the method, we compare our results with those obtained using global POD on the one hand, and two methods based on Grassmann interpolation on the other. These comparisons are performed for two classical configurations encountered in fluid dynamics. The first corresponds to the one-dimensional non-linear Burgers' equation. The second example is the two-dimensional cylinder wake flow. We show that the proposed strategy can accurately reconstruct the physical quantities associated with a new operating point. Moreover, the estimation is fast enough to allow real-time computation.

Experimental study on the aerodynamic characteristics and wake flow feature of triangular prisms with various round corner radius

In this work, particle image velocimetry (PIV) and wind pressure measurements are employed in the wind tunnel to investigate triangular prisms with different rounded corner radius. The effect of rounded corner radius on wind pressure distribution, aerodynamic force, and wake flow characteristics are analyzed. Results indicate that the surface wind pressure can be effectively reduced through filleting treatment, with an average drag coefficient decrease of 52.7% as the corner shape transitions from sharp to round. The continuous increase of the radius of the rounded corner causes an accretion of the fluctuating lift coefficient, and a slow decrease of the drag coefficient. The modification of the corner radius has a limited impact on the vortex shedding frequency, but the shedding vortex tend to gather the leeward side. Additionally, statistical analysis of wake flow shows that an increment in the rounded corner radius leads to a significant reduction in the wake recirculation region, amounting to 20.16%. Concurrently, the peak values of turbulent kinetic energy and Reynolds stress exhibit a pattern of initial increase followed by a decrease. On the other hand, results of proper orthogonal decomposition suggest that the spatial distribution of vortex structures becomes increasingly compact with the enlargement of the rounded corner radius.

Flow topology and turbulent characteristics of cross flow over a wall bounded inline tube bundle with small pitch to diameter ratio

The characteristics of cross flow over tube bundles with small pitch to diameter ratios (S/D) are preferable for intermediate heat exchangers (IHXs) of High Temperature Gas-cooled Reactors (HTGRs) due to they can further improve the compactness of such heat exchangers. However, small S/D usually introduces more complex flow phenomena, such as biased wakes, main frequency disappearing in velocity spectrum, as well as the quasi-stable phenomenon. In the current investigation, the cross flow over an inline tube bundle (8 columns and 20 rows) with S/D = 1.25 was experimentally investigated in a low-speed wind tunnel using various measurement techniques including two-dimensional, two-component (2D2C) Particle Image Velocimetry (PIV), split hot film anemometry, surface pressure measurements and wind tunnel balances. Firstly, PIV was used to obtain the time averaged streamwise and transverse velocity fields (in z-normal plane). The direction of the turbulent wakes and transverse flows behind the tubes were investigated. It was found that at the middle spanwise plane (z = 0 mm), the wakes and transverse flows are both towards the nearby bounding wall. However, at planes closer to the end of the tubes, the directions of the wakes and transverse flows are away from the bounding walls (z=±200 mm). To further confirm this phenomenon, split hot films are used to measure the transverse flow direction at different streamwise and spanwise positions, revealing that the direction of the wakes and transverse flows remained consistent at different streamwise positions. Streamwise and spanwise velocity fields (in y-normal planes) measured using PIV demonstrates that there exists spanwise flow (z direction) in different transverse planes (y-normal planes) within the tube bundle. The spanwise and transverse flows form secondary flows in the plane normal to the flow direction (x-normal plane). The secondary flows are symmetrical about the z = 0 mm plane and y = 0 plane. Therefore, the streamlines within the tube bundle are in a helical shape. In the current surface pressure measurement, two sets of main frequencies corresponding to Sr = 0.047 and 0.112 were identified in the surface pressure spectrum. Moreover, transverse velocity sudden jumps were observed in specific regions from the reconstructed PIV results using Proper Orthogonal Decomposition (POD). This phenomenon was particularly prominent at the plane (z = 150 mm) where the wake and transverse flow directions transition.

Numerical investigation of turbulent wake thermal effects on surface ships

To investigate the evolutionary mechanism of the thermal wake of surface ships, this study has proposed a numerical method for the thermal effects of turbulent wake and computed the near-wake fields for three ship schemes. The study indicates that the thermal wake, formed by vortices produced by the ship's movement and the propeller's rotation, propagates in a fine, thread-like pattern, setting it apart from the characteristic V-shaped diffusion of the Kelvin wake. The diffusion of thermal wake is divided into three distinct stages: formation, growth, and maturity. The thermal wakes generated by ships with shaftless rim-driven systems exhibit significantly lower diffusion rates, extents, and intensities compared to those created by ships with propeller propulsion systems. In summer, the center of the thermal wake exhibits a cold peak that is significantly lower than the ambient temperature. A reduction in temperature of greater than 0.05 K was observed for the three design schemes. In contrast, a warm peak that is above the environmental temperature is present at the edge of the wake. As the speed of the ship increases, the duration of each stage of the thermal wake lengthens and the diffusion range expands. When the temperature gradient is larger, the thermal wake becomes more intense. The findings of this study have revealed the evolution mechanisms of thermal effects in the wake of surface ships, thereby contributing to the advancement of knowledge in the fields of hydrodynamics and thermodynamics.

Cylinder wake flow in confined channel and its active control by sweeping jets

Cylinder wake flow in confined channel and its active control by sweeping jets

A DATA DRIVEN METHOD FOR THE DERIVATION OF EXPLICIT ALGEBRAIC REYNOLDS STRESS MODELS APPLIED TO THE WAKE LOSSES OF LOW-PRESSURE TURBINE CASCADES

Abstract This paper introduces and validates a data-driven approach to improve the prediction of linear eddy viscosity models (LEVMs). The general approach is adopted in order to improve the wake mixing of low-pressure turbine (LPT) cascades. The approach follows the rationale applied in the derivation of explicit algebraic Reynolds stress models (EARSMs) by including additional second-order tensors in the Boussinesq assumption. The unknown scalar functions that determine the contributions of each second-order tensor to the Reynolds stresses are approximated as polynomials. A metamodel-assisted multi-objective optimization determines the value of each of the polynomial coefficients by minimizing the difference between the result of the EARSM simulation and reference data provided by a high fidelity large eddy simulation (LES). In this study, tailor made EARSMs are calibrated to improve the prediction of the kinetic energy loss distribution in the wake of the T106C LPT cascade. We investigated the influence of each polynomial coefficient of the EARSM on the results. The models generated by the approach reduced the deviations in total kinetic energy loss between the LES reference solution and the baseline model by approximately 70%. The turbulent quantities are analyzed to identify the physical correlations between the model inputs and the improvement. The transferability of the models to unseen test cases was assessed using the MTU-T161 LPT cascade. In summary, the suggested approach was able to generate tailor made EARSM models that reduce the deviations between RANS and LES for the mixing of turbulent wake flows.

Deep learning-based automated identification on vortex-induced vibration of long suspenders for the suspension bridge

Large amplitude vortex-induced vibration (VIV) of long suspenders, caused by vortex-shedding and wake flow, will decrease the service life of high-strength wires and its anchorage systems, hence listed as an essential monitoring indicator of the structural health monitoring system in the suspension bridges. Traditionally, a static vibration amplitude limitation is usually predefined and used to identify VIV from continuously monitored acceleration data of bridge suspenders. Due to the complexity of the starting vibration of the suspenders, it may not be able to flexibly adapt to the suspenders VIV under different conditions. In addition, transient but significant vibration events may not be captured since it relies only on static vibration amplitude limits without considering the temporal information of vibration. To address the above-mentioned issues, a novel framework to autonomously identify the suspenders VIV is proposed using the multimodal fusion techniques with deep neural networks. The main contributions of the methodology are: i) by calculating the wind field and vibration characteristic, two vibration response parameters are identified as indexes for the identification of suspenders VIV based on the significant difference method of big data analysis; ii) Two different modal information of time history images and power spectral density (PSD) sequences are used as inputs to the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) to extract the suspenders vibration response features from the time and frequency domain perspectives, respectively; and iii) The multimodal information is concentrated and enhanced by the multi-head attention (MHA) mechanism to achieve automated identification of the suspenders VIV. The proposed framework is validated with data collected from a full-scale long-span suspension bridge in comparison with the base model. The results show that the proposed framework can efficiently identify the full-cycle development process of the suspenders VIV. This study provides a convenient strategy for suspenders VIV identification, which can be used for bridge management and vibration mitigation device design.

An Efficient Ship Detection Method Based on YOLO and Ship Wakes Using High-Resolution Optical Jilin1 Satellite Imagery.

In this study, we propose a practical and efficient scheme for ship detection in remote sensing imagery. Our method is developed using both ship body detection and ship wake detection and combines deep learning and feature-based image processing. A deep convolutional neural network is used to achieve ship body detection, and a feature-based processing method is proposed to detect ship wakes. For better analysis, we model the sea region and evaluate the quality of the image. Generally, the wake detection result is used to assist ship detection and obtain the sailing direction. Conventional methods cannot detect ships that are covered by clouds or outside the image boundary. The method proposed in this paper uses the wake to detect such ships, with a certain level of confidence and low false alarm probability in detection. Practical aspects such as the method's applicability and time efficiency are considered in our method for real applications. We demonstrate the effectiveness of our method in a real remote sensing dataset. The results show that over 93.5% of ships and over 70% of targets with no visible ship body can be successfully detected. This illustrates that the proposed detection framework can fill the gap regarding the detection of sailing ships in a remote sensing image.

Numerical investigation on the impact of aerodynamic braking plates positioned at streamlined sections on the slipstream and wake flow of the high-speed train based on train-fixed reference frame

This paper studies the aerodynamic characteristics of high-speed trains (HSTs) featuring aerodynamic braking plates installed on the streamlined sections, employing the improved delayed detached eddy simulation (IDDES) method at Re = 5.0 × 105. The precision of the numerical simulation methodology has been validated through reduced-scale wind tunnel experiments. A comparative analysis has been conducted on the characteristics of slipstream, wake flow, and upper flow between the original configuration (OC) and the braking configuration (BC) of the HSTs. The findings reveal that the application of braking plates promotes significant separation phenomena around the HSTs, enhancing the slipstream velocity distribution. In the BC, compared to the OC, the maximum value of the time-averaged slipstream velocity has increased by approximately 134.9% and 76.8% at the trackside and platform positions, respectively. Additionally, the TSI value of the slipstream velocity shows increases of around 100.4% and 210.4% at the trackside and platform positions, respectively. Meanwhile, the turbulence fluctuations within the wake region have been enhanced, with the formation of a longitudinal vortex alongside the railway subgrade, whose core nearly covers the TSI positions. Notably, obvious shifts occur within the upper flow field, which significantly strengthens both flow turbulence and slipstream velocity, potentially influencing components on the upper surface of HSTs, such as the pantograph. The deployment of braking plates contributes to a significant increase in overall vehicle pressure drag, thereby enhancing the train's aerodynamic drag. Relative to the OC, the aerodynamic drag of the HST has increased by approximately 235.4% in the BC.

A Systematic Review of Ship Wake Detection Methods in Satellite Imagery

The field of maritime surveillance is one of great strategical importance from the point of view of both civil and military applications. The growing availability of spaceborne imagery makes it a great tool for ship detection, especially when paired with information from the automatic identification system (AIS). However, small vessels can be challenging targets for spaceborne sensors without relatively high resolution. Moreover, when faced with non-cooperative targets, hull detection alone is insufficient for obtaining critical information like target speed and heading. The wakes generated by the movement of ships can be used to solve both of these issues. Several interesting solutions have been developed over the years, based on both traditional and learning-based methodologies. This review aims to provide the first thorough overview of ship wake detection solutions, highlighting the key ideas behind traditional applications, then covering more innovative applications based on deep learning (DL), to serve as a solid starting point for present and future researchers interested in the field.

Wind turbine dynamic wake flow estimation (DWFE) from sparse data via reduced-order modeling-based machine learning approach

Wind turbine wake poses a significant challenge in wind farm operations, affecting power generation efficiency. This study introduces a Dynamic Wake Flow Estimation (DWFE) framework designed to predict wind turbine wake evolution from sparse measurement data. The framework integrates Gaussian Process Regression (GPR), Proper Orthogonal Decomposition (POD), and Long Short-Term Memory (LSTM) networks. Specifically, GPR plays a pivotal role in DWFE by enabling the transformation of flow fields discrete sensor signals into coherent, low-dimensional flow fields which is crucial for accurate flow field predictions, while POD aids in dimensionality reduction and LSTM forecasts temporal wake dynamics, improving both predictive accuracy and computational efficiency. Parametric analysis demonstrates that the robustness and adaptability of the framework improve prediction accuracy with increased sensor density and flexible POD modes. The DWFE framework demonstrates high accuracy in wake flow estimation even with limited data, effectively capturing dynamic wake behavior. Future work will extend this approach to various topographic and climatic conditions, optimizing computational efficiency, and improving interpretability. These advancements will expand the framework's applicability in wind energy and other engineering fields requiring precise flow prediction, emphasizing DWFE's potential in advancing wind farm design, operation and renewable energy optimization.

Experimental study on sound propagation caused by disturbance of wake flow on water surface boat

The research on underwater sound propagation generally assumes that the water is static. However, when a boat passes on the water surface, its wake can cause disturbance to the stable sound field. The main reason is that the wake changes the temperature and salinity distributions of seawater in the just field, thereby affecting propagation loss. This article conducts a time-frequency analysis of the sound signal propagated by the boat wake. Results show that the wake not only affects the propagation loss but also causes obvious fluctuations in the envelope of the received signal. This fluctuation indicates the frequency modulation of sound by the boat wake. These changes in sound propagation are not only related to the boat speed but also to the signal frequency.