Drag Coefficient Research Articles

Numerical simulation of drag on local particle cluster within a high void fraction environment in supercritical water

The drag of particle cluster within a high void fraction environment in supercritical water (SCW) is investigated by numerical simulation. The results show that the description pattern of particle drag in SCW is the same as that in constant property flow (CPF). The diffusion of pressure in the phenomenon of fluid flow around particle cluster caused that the variation pattern of drag coefficient is contrary to the classical conclusion. The normalized drag coefficient is mainly depending on the thermal properties. The internal flow characteristics of the particle cluster further confirm the effects of fluid flow around it. After separating the effects of thermal properties, the exponent -β representing the effects of void fraction in SCW is similar to that in CPF. A correlation for calculating the particle drag in SCW is developed based on this result.

Stability analysis of a uniform viscous transonic flow past a rotating circular cylinder

This work analyzes the transonic flow around a rotating circular cylinder. The combination of a uniform freestream flow and the flow due to the rotation of the cylinder (assuming clockwise rotation) generates a lift force (Robins-Magnus effect) that, for transonic flows, is conditioned by the presence of a shock wave on the upper side of the cylinder.Previous studies have focused primarily on incompressible flows, compressible flows at low Mach numbers, and hypersonic flows with detached shock waves. These works have barely considered the effect of the presence of the shock wave, its interaction with the wake of the cylinder and its impact in the aerodynamic coefficients.Two-dimensional numerical simulations have been carried out using the SU2 code. From these simulations, the value of the aerodynamic coefficients as a function of time and a set of snapshots of the fluid field have been obtained and analyzed using the POD and DMD techniques. This has allowed the identification of the dominant modes that characterize the time variations in the lift and drag coefficients acting on the circular cylinder for different values of the characteristic parameters of the problem.

Experimental and numerical study on vibration response, VIV mechanism and aerostatic coefficients of triple-separated decks under different vertical distances

In this study, aerodynamic interference effects (AIE) on the vibration response, aerostatic coefficient (AC) and vortex-induced vibration (VIV) mechanism of the triple-separated decks under different incoming wind directions and vertical distances were investigated via wind tunnel tests and numerical simulations, respectively. The test results show that the AIE increases the displacement of VIV, and the VIV responses reaches maximum value under S/H = −1.0 (S is the vertical distance between the centers of RB and HB decks, and H is the height of RB deck) when the RB deck is on the windward side (the maximum displacements of VIV are 193.86% and 37.30% higher than the case of single RB deck and S/H = 0.0, respectively). The pressure distribution and flow structure show that the scale of vortex that alternately shed off from the tail of the deck becomes stronger and the fluctuating pressure coefficient increases under AIE, which increase the VIV amplitude of the RB deck and cause the VIV of HB decks. The experimental and numerical results indicated that the aerostatic coefficients (AC) of the leeward girder are more affected by the AIE. The interference factor (IF) of drag coefficient (CD) is far less than 1.0 under the case of F-5 (S/H = 0.0).

Dynamic feature-based deep reinforcement learning for flow control of circular cylinder with sparse surface pressure sensing

This study proposes a self-learning algorithm for closed-loop cylinder wake control targeting lower drag and lower lift fluctuations with the additional challenge of sparse sensor information, taking deep reinforcement learning (DRL) as the starting point. The DRL performance is significantly improved by lifting the sensor signals to dynamic features (DFs), which predict future flow states. The resulting DF-based DRL (DF-DRL) automatically learns a feedback control in the plant without a dynamic model. Results show that the drag coefficient of the DF-DRL model is 25 % less than the vanilla model based on direct sensor feedback. More importantly, using only one surface pressure sensor, DF-DRL can reduce the drag coefficient to a state-of-the-art performance of approximately 8 % at Reynolds number $(Re) = 100$ and significantly mitigates lift coefficient fluctuations. Hence, DF-DRL allows the deployment of sparse sensing of the flow without degrading the control performance. This method also exhibits strong robustness in flow control under more complex flow scenarios, reducing the drag coefficient by 32.2 % and 46.55 % at $Re =500$ and 1000, respectively. Additionally, the drag coefficient decreases by 28.6 % in a three-dimensional turbulent flow at $Re =10\,000$ . Since surface pressure information is more straightforward to measure in realistic scenarios than flow velocity information, this study provides a valuable reference for experimentally designing the active flow control of a circular cylinder based on wall pressure signals, which is an essential step toward further developing intelligent control in a realistic multi-input multi-output system.

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

This research focuses mainly on the aerodynamic modelling and performance analysis of a model predictive controller for a hybrid fixed-wing vertical takeoff and landing of unmanned aerial vehicle. The aerodynamics, which comprises several aerodynamic characteristics including the lift, drag, and thrust coefficients, is modelled using Newton’s second law of motion. The force and moment equations were obtained, and they were then converted into matrix and state equation form, together with the transformation matrices. The essential equations with six degrees of freedom (6 DoF) and 12 state matrices including the control input and manipulating variables were obtained. The proposed model predictive controller (MPC) was designed using the optimal model predictive controller design parameters, such as a sampling time of 0.1, a prediction horizon of 15, a control horizon of 3 and additional controller settings. With a settling period of 3 s, an overshoot of 0.5865, and a steady state inaccuracy of 0.00785, the MATLAB simulation demonstrates that the system variables, including roll, pitch, and yaw, are stabilized. This MPC control is more effective in anticipating and optimizing the UAV than other control strategies. Eventually, the controller’s simulation on MATLAB Simulink demonstrates the controller’s ability to stabilize and control the system in a real-time application. Autonomous vertical takeoff and landing operations depend heavily on the mathematical model and architecture of the flight controller. Among the uses are inspection, monitoring, and rescue.

A critical review on scale-up strategies of biosurfactant production and its applications

Abstract Eco-friendly, biodegradable, microbially produced surfactants, known as biosurfactants, have been intensively studied for their ability as potential substitutes for their synthetic counterparts. Currently, the commercialization of biosurfactants compared to synthetic (chemical) surfactants remains an economic challenge due to high production costs and lower yields. This review details the challenges and better strategies for industrial scale-up of biosurfactant production and downstream processing techniques. An analysis of the use of low cost, renewable substrates, parameter optimization, strain improvement, bioreactor engineering is discussed. The role of various engineering factors that help in scale-up of biosurfactant production such as drag coefficient, Reynolds number, Enrichment ratio, Eӧtvӧs number have also been considered in this review article. The review article demonstrates the potential activity of integrated separation processes and applications of biosurfactants, bringing biosurfactants into mainstream commercialization.

Numerical investigation and comparison of the aerodynamic characteristics of non-pneumatic tire and pneumatic tire

A non-pneumatic tire, in which the tire pressure is replaced by an elastic support body, is called an airless tire with elastic support (ALTES). In this study, the differences in the aerodynamic characteristics between ALTES and pneumatic tire (PT) were comparatively investigated using URANS simulations based on the DrivAer model. It was found that the vehicle body drag coefficient of the vehicle equipped with ALTES was reduced by 27% compared to that of the vehicle equipped with PT and had a significant drag-reduction effect. The drag coefficient and moment coefficient of the ALTES wheels are 2 and 3.5 times those of the PT wheels, respectively, which offset the drag-reduction benefits. The drag coefficient and aerodynamic power loss of vehicles equipped with ALTES were 97–102% and 108.5%–114% of those of vehicles equipped with PT. It is reasonable and necessary to evaluate the aerodynamic performance of ALTES based on the aerodynamic power loss. By suppressing the wheel ventilation flow and reducing the wheel drag, the aerodynamic wheel cover can reduce the aerodynamic power loss of a vehicle equipped with ALTES by 12%, and the vehicle aerodynamic performance is comparable to that of a PT.

Theoretical evaluation of a hybrid buoyancy-compressed air energy storage system

Energy storage plays a pivotal role in the emerging green economy. This study, for the first time, presents the theoretical evaluation of a buoyancy power generator combining with the compressed air energy storage (CAES-BPG) system. A theoretical model that satisfies conservation laws and does not involve any adjustable parameters is developed for the calculation of system efficiency and power generation capacity. To accurately predict drag acting on the buoy, the low Reynolds number κ-ω SST model with a locally refined mesh (y+~1) is applied to fully resolve the viscosity affected regions including the viscous sublayers, whilst the surrounding flow is modelled by LES. The refined mesh moves passively with the buoy and does not change, whilst mesh in other regions undergoes smoothing and remeshing to accommodate the buoy's motion. Correlations of drag coefficients are then developed as a function of buoy shape, Reynolds number, and vessel-to-buoy size ratio. The aerofoil shape yielded a substantially smaller drag coefficient compared to the square, hex, and bullet shapes. System efficiency showed independency on buoy volume and shell material but decreased as the water level in the vessel increased, reaching 64 % for a water level of 1.5 m. Similarly, as the water level increased, the system output power decreased. The output power increased as the buoy volume increased, reaching ~22 kW for a buoy volume of 2 m3 at a water level of 1.5 m. This CAES-BPG system is highly automatic and fully green, and can operate continuously once compressed air is connected, showing great potential for implementation as an energy storage / utilisation system of small to medium capacities.

An improved drift model of dropped containers under wind and current effects

In the face of the increasing risk of Maritime accidents caused by global climate change, it is necessary to improve the accuracy of drift model of the dropped containers at seas for Maritime Search and Rescue (SAR). Sensitivity test on the classic drift model illustrates that immersion ratio (Ir) of container plays a dominate role in the drift trajectory of container compared to the drag coefficients. Inspired from it, a new scheme of variable Ir is proposed to improve the model by considering the water entering process of container in the study. Based on the stability analysis of four floating attitudes of intact empty container under strong wind condition, the variable Ir is estimated according to the orifice inflow theory and the Archimedes' principle of buoyancy. The new scheme is compared with the fixed Ir scheme from the simulation of the drift trajectory of the dropped container at Xiamen Bay of China. The result shows that error arisen from the fixed Ir would be accumulated as the time integral, but the new scheme of variable Ir can obviously improve the model accuracy for the long-time prediction of SAR. In addition, the drag coefficients of wind and water in the drift model of the dropped container are suggested to be 0.8 and 1.2, respectively.

Optimal deployment of dynamic wireless charging infrastructure for battery electric buses – a case study in Auckland, New Zealand

ABSTRACT Inductive power transfer (IPT) systems offer a promising solution to multiple major hurdles associated with electric vehicles, such as the lack of widespread charging infrastructure, driving range anxiety, and significant charging time. With the aid of IPT systems, dynamic wireless charging enables electric vehicles to be charged when running over the IPT power pads. The objective of this study is to minimise the overall cost of charging infrastructure by optimising the deployment of IPT transmitters and the battery size required to support charging for electric buses. A mixed-integer linear programming model is proposed and solved using the commercial solver Gurobi. Bus route information and the characteristics of electric buses, such as weight, drag coefficient and frontal area, are used as input to run the traffic simulation in SUMO to get time-varying velocity and acceleration data during bus operations. A bus route in Auckland, New Zealand, is used as a case study in the presented numerical experiments. A strong correlation between the velocity of the bus and the state of charge is identified. The largest cost component is the charging pad, followed by the battery.

Aerodynamic design optimization of a NACA 0012 airfoil: An introductory adjoint discrete tool for educational purposes

The adjoint method is a powerful tool in high-fidelity aerodynamic shape optimization, providing an efficient means to compute derivatives of a target function with respect to various design variables. This paper delves into the discrete adjoint method. It offers a theoretical exploration of its implementation as an innovative tool for calculating partial derivatives (sensitivities) related to objective functions and design variables, specifically applied to a subsonic NACA0012 airfoil. The study conducts a qualitative evaluation using a designated test case, considering specified Mach number and Reynolds number values of 0.297 and 6,667 million, respectively. The Spalart-Allmaras turbulence model is employed to enhance computational cost efficiency. The results affirm the efficacy of the introduced tool, DAFoam, showcasing its ability to generate optimal geometries. The achieved performance optimization is evidenced by minimizing the drag coefficient value (CD) to an impressive 0.0131. While this research does not delve into the post-processing of sensitivity calculations, it acknowledges the potential for future investigations. The primary objective and novelty of this study is to provide the elementary background of the state of the art test case (NACA0012) within the subsonic regime, introducing the pioneer discrete adjoint aerodynamic optimization methodology (DAFoam) with the potential to explore its higher order capabilities in other aerodynamic related studies. Furthermore, it caters the educational needs of both graduate students and engineers in this exciting field. By presenting this cutting-edge methodology, it contributes to future advancements for the aerodynamicists in terms of optimal solutions.

Effects of Reynolds Number on the Wake Characteristics of a Notchback Ahmed Body

Abstract This paper investigates the effects of Reynolds number on the wake characteristics of a notchback Ahmed body with effective backlight angle, βe=17.8 deg. The Reynolds number based on the body height was varied from 5×103 to 5×104. Prior to the Reynolds number investigation, a Reynolds-averaged Navier–Stokes (RANS) model assessment was performed using nine turbulence models consisting of one- and two-equation eddy-viscosity models and second moment closure models. The standard Spalart–Allmaras model was the only model that accurately predicted the asymmetric time-averaged wake topology, as reported in previous studies, for the βe=17.8 deg notchback Ahmed body at Re=5×104. The drag coefficient decreased with increasing Reynolds number, while the lift coefficient remained constant for Re≥1×104. The wake structure exhibited three regimes: symmetric (Re≤1×104), transitionally asymmetric (1×104<Re≤3.5×104), and fully asymmetric (Re>3.5×104) states. The wake asymmetry was attributed to an imbalance in entrainment from the sides and asymmetric separation from the roof and the C-pillars of the body. The tilting and stretching terms in the vorticity transport equation were used to provide insight into the source of asymmetry in the vorticity field around the body.

Boundary feedback control of Navier–Stokes equations around arbitrary bluff body with prescribed drag and lift coefficients

This paper presents a boundary feedback control method for the two- and three-dimensional Navier–Stokes equations around an arbitrary bluff body, with prescribed drag and lift coefficients. In order to determine the feedback control law, we consider an extended system coupling the equations governing the Navier–Stokes problem with an equation satisfied by the control on the bluff body, which is a part of the domain boundary. We utilize the artificial compressibility method, which approximates the Navier–Stokes equations in the limit, along with a priori estimation techniques, to establish a boundary control. Such a control law ensures that the prescriptions of the drag and lift coefficients are attained. Subsequently, a compactness result allows to let the compressibility parameter tend to zero. The application of the Faedo-Galerkin method is essential in reaching this result.

Large-Eddy Simulation of Low-Frequency Flow Oscillations for NACA0012 and Dynarig Sail at Large Attack Angles

Unmanned sailboats, harnessing wind for propulsion, offer great potential for extended marine research due to their virtually unlimited endurance. The sails typically operate at high attack angles, which contrasts with aircraft that maintain small angles to prevent stalling. Despite the reduction in lift during stalling, the resultant increase in drag contributes significantly to the sail’s thrust. However, the sail often experiences vortex shedding due to high attack angles, leading to low-frequency oscillations and erratic navigation. This study employs large-eddy simulations (LESs) on a 3D NACA0012 sail at a Reynolds number of 3.6 × 105, which is validated by experimental data. It observes the lift and drag coefficients across attack angles from 5 to 90 degrees and compares these with a Dynarig sail. The findings reveal that higher attack angles amplify fluctuations in lift and drag coefficients. Vortex shedding, resulting from flow separation, creates pressure changes and oscillations in aerodynamic forces. Fast Fourier transformation (FFT) analysis identifies dominant frequencies between 0.5 and 10 Hz, indicating low-frequency oscillations. The study’s insights into the impact of attack angle and sail type on the oscillation frequency are favorable for the design of unmanned sailboats, aiding in the prediction of wind-induced frequencies and optimal attack angle determination.

Optimization of automotive aerodynamic performance based on DOE

Based on a new-energy sedan as the research object, the Design of Experiments (DOE) optimization integrated grid deformation method was used to optimize and improve the aerodynamic performance of a certain development model. A three-dimensional flow field comparison analysis was conducted on the improved areas of the whole vehicle flow field, and wind tunnel tests were conducted for verification. Through CFD simulation and wind tunnel test verification, the accuracy of the CFD simulation method was verified. The engineering feasible DOE optimization recommended area for the whole vehicle was summarized. The optimal prediction results based on the DOE optimization method and the corresponding CFD simulation results were analyzed for reliability. The correlation between the optimization variables and the target function was analyzed, and 6 counts reduced the whole vehicle drag coefficient by adjusting the optimization variables within a small range. Finally, wind tunnel tests were used to verify the effectiveness of the optimized variable scheme. The results provide an important reference for the optimization design and development of vehicle aerodynamic performance.

Three-dimensional flow around and through a porous screen

We investigate the three-dimensional (3-D) flow around and through a porous screen for various porosities at high Reynolds number $Re = {O}(10^4)$ . Historically, the study of this problem has been focused on two-dimensional cases and for screens spanning completely or partially a channel. Since many recent problems have involved a porous object in a 3-D free flow, we present a 3-D model initially based on Koo & James (J. Fluid Mech., vol. 60, 1973, pp. 513–538) and Steiros & Hultmark (J. Fluid Mech., vol. 853, 2018 pp. 1–11) for screens of arbitrary shapes. In addition, we include an empirical viscous correction factor accounting for viscous effects in the vicinity of the screen. We characterize experimentally the aerodynamic drag coefficient for a porous square screen composed of fibres, immersed in a laminar air flow with various solidities and different angles of attack. We test various fibre diameters to explore the effect of the space between the pores on the drag force. Using PIV and hot wire probe measurements, we visualize the flow around and through the screen, and in particular measure the proportion of fluid that is deviated around the screen. The predictions from the model for drag coefficient, flow velocities and streamlines are in good agreement with our experimental results. In particular, we show that local viscous effects are important: at the same solidity and with the same air flow, the drag coefficient and the flow deviations strongly depend on the Reynolds number based on the fibre diameter. The model, taking into account 3-D effects and the shape of the porous screen, and including an empirical viscous correction factor that is valid for fibrous screens may have many applications including the prediction of water collection efficiency for fog harvesters.

Wake Structures and Hydrodynamic Characteristics of Flows around Two Near-Wall Cylinders in Tandem and Parallel Arrangements

To clarify the hydrodynamic interference characteristics of flows around multiple cylinders under the wall effect, the two-dimensional (2D) flows around the near-wall single, two tandem and parallel cylinders are simulated under different gap ratios (0.15 ≤ G/D ≤ 3.0) and spacing ratios (1.5 ≤ T/D ≤ 4.0) at a Reynolds number of Re = 6300. We also examine the wake patterns, the force coefficients, and the vortex-shedding frequency with emphases on the wall effect and effects of the two-cylinder interference. A critical wall gap of G/D = 0.6 is identified in the single-cylinder case where the wall can exert significant influences. The two near-wall tandem cylinders exhibit three wake states: stretching mode, attachment mode, and impinging mode. The force coefficients on the upstream cylinder are significantly affected by the wall for G/D ≤ 0.6. The downstream cylinder is mainly influenced by the upstream cylinder. For G/D > 0.6, the force coefficients on the two cylinders exhibit a similar variation trend. In the parallel arrangement, the two cylinders exhibit four wake states in different G/D and T/D ranges: double stretching mode, hetero-vortex scale mode, unilateral vortex mode, and free vortex mode. Moreover, the two parallel cylinders in the hetero-vortex scale or free vortex mode have two states: synchronous in-phase state and synchronous out-of-phase state. The mean drag coefficients on the two cylinders decrease, while the mean lift coefficients exhibit opposite variation trends, as the T/D grows.

Numerical study of aerodynamics drag and flow characteristics of the high-speed train head design

A native design of the Indonesian high-speed train has been developed as an improvement of the previous medium-speed train model. As the design speed is proposed to be increased from 160 km/h to 250 km/h, the nose shape and nose length of the train head were modified into a sharper and longer nose. In this study, numerical simulation of computational fluid dynamics was used to investigate the aerodynamic phenomena and flow behavior around the modified train head and carbodies. The CFD simulation was used as the verification of the shape design and a tool for rapid design changes and optimization. The model configuration is three cars on a real scale by ignoring other parts like the train window and door, pantograph, and train connecting. A k-ε turbulence model was used in the simulation. From this investigation, it is found that the coefficient of drag on the model is calculated to be 0.34. Meanwhile, an experimental wind tunnel test validates the result with a coefficient drag is 0.38 or 10% divergence from the numerical method.

Effects of Surface Turbulence Flux Parameterizations on the MJO: The Role of Ocean Surface Waves

Abstract This study investigates the sensitivity of the Madden–Julian oscillation (MJO) to changes to the bulk flux parameterization and the role of ocean surface waves in air–sea coupling using a fully coupled ocean–atmosphere–wave model. The atmospheric and ocean model components of the Energy Exascale Earth System Model (E3SM) are coupled to a spectral wave model, WAVEWATCH III (WW3). Two experiments with wind speed–dependent bulk algorithms (NCAR and COARE3.0a) and one experiment with wave-state-dependent flux (COR3.0a-WAV) were conducted. We modify COARE3.0a to include surface roughness calculated within WW3 and also account for the buffering effect of waves on the relative difference between air-side and ocean-side momentum flux. Differences in surface fluxes, primarily caused by discrepancies in drag coefficients, result in significant differences in MJO’s properties. While COARE3.0a has better convection–circulation coupling than NCAR, it exhibits anomalous MJO convection east of the date line. The wave-state-dependent flux (COR3.0-WAV) improves the MJO representation over the default COARE3.0 algorithm. Strong easterlies over the Pacific Ocean in COARE3.0a enhance the latent heat flux (LHFLX). This is responsible for the anomalous MJO propagation after the date line. In COR3.0a-WAV, waves reduce the anomalous easterlies, leading to a decrease in LHFLX and MJO dissipation after the date line. These findings highlight the role of surface fluxes in MJO simulation fidelity. Most importantly, we show that the proper treatment of wave-induced effects in bulk flux parameterization improves the simulation of coupled climate variability.

AI-based predictive approach via FFB propagation in a driven-cavity of Ostwald de-Waele fluid using CFD-ANN and Levenberg–Marquardt

The integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques into computational science has ushered in a new era of innovation and efficiency in various fields, with particular significance in computational fluid dynamics (CFD). Several methods based on AI and Machine Learning (ML) have been standardized in many fields of computational science, including computational fluid dynamics (CFD). This study aims to couple CFD with artificial neural networks (ANNs) to predict the fluid forces that arise when a flowing fluid interacts with obstacles installed in the flow domain. The momentum equation elucidating the flow has been simulated by adopting the finite element method (FEM) for a range of rheological and kinematic conditions. Hydrodynamic forces, including pressure drop between the back and front of the obstacle, surface drag, and lift variations, are measured on the outer surface of the cylinder via CFD simulations. This data has subsequently been fed into a Feed-Forward Back (FFB) propagation neural network for the prediction of such forces with completely unknown data. For all cases, higher predictivity is achieved for the drag coefficient (CD) and lift coefficient (CL) since the mean square error (MSE) is within ± 2% and the coefficient of determination (R) is approximately 99% for all the cases. The influence of pertinent parameters like the power law index (n) and Reynolds number (Re) on velocity, pressure, and drag and lift coefficients is also presented for limited cases. Moreover, a significant reduction in computing time has been noticed while applying hybrid CFD-ANN approach as compared with CFD simulations only.