Drag Prediction Research Articles

Geometrically compatible integrated design method for conformal rotor and nacelle of distributed propulsion tilt-wing UAV

The inner rotors of distributed propulsion tilt-wing Unmanned Aerial Vehicles (UAVs) are often folded in the cruising state and deployed in vertical take-off and landing to cope with the huge difference in thrust requirements. However, the blades of the conventional rotor have poor conformality with the nacelle profile, which will greatly increase the drag of the UAV after folding. This paper proposes an integrated method for the design of rotor and nacelle considering geometric compatibility to reduce the drag of the folded rotor and nacelle, so as to further improve the aerodynamic efficiency in cruise while ensuring the rotor efficiency in the vertical flight mode. A geometric mapping model based on nacelle design parameters and rotor design parameters is established, and a parametric model and aerodynamic optimization model of the outer arc airfoil family are developed. In addition, a rotor performance analysis model and a neural network response surface model for nacelle drag prediction that meet the requirements of confidence level are established. Based on the oblique inflow blade element momentum theory method, numerical simulation method, and genetic algorithm, an integrated optimization framework of the design of the conformal rotor and nacelle is built. Then, a geometrically compatible integrated optimization for the rotor and nacelle is carried out with the objective of maximizing energy efficiency in the full mission profile. Finally, a conformal rotor and nacelle design solution is obtained, which satisfies geometric compatibility and thrust constraints while providing high thrust efficiency and low cruising drag. A comparison of the results of the integrated design and the conventional rotor optimization design shows that the drag of the conventional rotor is 3.45 times that of the conformal integrated design in the cruising state, which proves the effectiveness and necessity of the proposed method.

Numerical analysis of unsteady flow features around a realistic Estate vehicle with hybrid RANS/LES methods

A comparative study is conducted to analyze the flow around a realistic Peugeot Estate car (308 SW) using RKE and SST RANS models, as well as DDES hybrid RANS/LES approach. The authors used previous work on 25° Ahmed bodies to establish the best grid and DDES parameters for external aerodynamics prediction. The aim of this work is to extend and transpose the numerical methodology to a realistic car. Numerical and physical characteristics related to the simulation of this complex flow are therefore carefully investigated. The numerical results are compared to in-house experiments carried out in S2A Stellantis Wind Tunnel. Two grids with 115 and 185 million elements, based on 20 prism layers cells near the wall, are used to compare the three turbulence models. Even with a smaller grid size in the wake and underbody, the predictions of drag and lift coefficients are almost identical. Moreover, refining the near-wall region from 20 to 30 prism layers has no effect on drag coefficient and flow prediction. Consequently, the grid with 20 prism layers and 115M cells is used as reference grid in this work. Then, the flow features between RKE, SST and SST DDES models are compared to two-dimensional (2D) and three-dimensional (3D) experimental results. RANS gives better agreement on aerodynamics forces. However, DDES reproduces accurately the specific three-dimensional topology of the flow around the car, in the wake and the underbody when RANS results are globally wrong.

On the Effectiveness of Scale-Averaged RANS and Scale-Resolved IDDES Turbulence Simulation Approaches in Predicting the Pressure Field over a NASCAR Racecar

Racecar aerodynamic development requires well-correlated simulation data for rapid and incremental development cycles. Computational Fluid Dynamics (CFD) simulations and wind tunnel testing are industry-wide tools to perform such development, and the best use of these tools can define a race team’s ability to compete. With CFD usage being limited by the sanctioning bodies, large-scale mesh and large-time-step CFD simulations based on Reynolds-Averaged Navier–Stokes (RANS) approaches are popular. In order to provide the necessary aerodynamic performance advantages sought by CFD development, increasing confidence in the validity of CFD simulations is required. A previous study on a Scale-Averaged Simulation (SAS) approach using RANS simulations of a Gen-6 NASCAR, validated against moving-ground, open-jet wind tunnel data at multiple configurations, produced a framework with good wind tunnel correlation (within 2%) in aerodynamic coefficients of lift and drag predictions, but significant error in front-to-rear downforce balance (negative lift) predictions. A subsequent author’s publication on a Scale-Resolved Simulation (SRS) approach using Improved Delayed Detached Eddy Simulation (IDDES) for the same geometry showed a good correlation in front-to-rear downforce balance, but lift and drag were overpredicted relative to wind tunnel data. The current study compares the surface pressure distribution collected from a full-scale wind tunnel test on a Gen-6 NASCAR to the SAS and SRS predictions (both utilizing SST k−ω turbulence models). CFD simulations were performed with a finite-volume commercial CFD code, Star-CCM+ by Siemens, utilizing a high-resolution CAD model of the same vehicle. A direct comparison of the surface pressure distributions from the wind tunnel and CFD data clearly showed regions of high and low correlations. The associated flow features were studied to further explore the strengths and areas of improvement needed in the CFD predictions. While RANS was seen to be more accurate in terms of lift and drag, it was a result of the cancellation of positive and negative errors. Whereas IDDES overpredicted lift and drag and requires an order of magnitude more computational resources, it was able to capture the trend of surface pressure seen in the wind tunnel measurements.

Comparative Accuracies of Models for Drag Prediction During Geomagnetically Disturbed Periods: A First Principles Model Versus Empirical Models

AbstractWe examine the accuracy of density prediction by the first principles model Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) developed by the National Center for Atmospheric Research and compare it to the accuracy of three empirical models: Jacchia 71, the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Extended 2000 (NRLMSIS), Jacchia 1971, and Jacchia‐Bowman 2008. Comparisons are made for three large storms: the October 2003 storm, the March 2013 storm, and the March 2015 storm. To evaluate the accuracy of these models we use tracking data for nine space objects in low Earth orbit. Additionally, we evaluate the accuracy of the TIEGCM and NRLMSIS with data from high precision accelerometers on the Challenging Minisatellite Payload (CHAMP) and Gravity field and Circulation Explorer (GOCE) satellites. The goal is to assess the use of a first principles model as a potential tool for forecasting satellite drag during large magnetic storms. For the storms considered, we found the TIEGCM, JB2008, and NRLMSIS models to be substantially more accurate than the Jacchia 71 model. The accuracies of the TIEGCM and JB2008 models were similar, but overall, the TIEGCM was more accurate. We found smaller differences for TIEGCM versus CHAMP than for NRLMIS for the Halloween Storm, and smaller differences than results published for JB2008 and the assimilative model HASDM. The empirical models are at present more practical for operational purposes, but the TIEGCM, developed as a research model, with a greater focus on operational use offers the potential for improved utility during stressing conditions.

INVESTIGATING THE COMPARISON OF SHIP RESISTANCE COMPONENTS BETWEEN U AND V-SHAPED HULLS

The selection of a hull design with minimal drag is an important effort to reduce emission levels on ships. Two different hull shapes, U and V hulls, have unique properties that affect their drag production, which has been studied extensively in the past. This study aims to re-examine the differences between the two hull types by conducting a simple analysis of drag prediction results using empirical and numerical slender body methods. Both hull models in this study have the same size and volume. The results indicate that the U hull has a higher frictional resistance ( ) than the V hull due to its wider wetted surface area ( ). Additionally, the viscous pressure resistance ( ) and form factor coefficient ( ) of the U hull are also higher than those of the V hull. However, for Froude numbers (Fr) above 0.245, the U hull has lower wave resistance ( ) than the V hull, whereas for Fr below 0.245, the U hull has higher . Overall, the U hull produces a higher total resistance ( ) than the V hull at low speeds, but a lower at high speeds. Therefore, the choice of hull shape for minimizing a ship's resistance is influenced by the desired speed of service. If Fr is low, below 0.24, a V-shaped hull is more suitable. However, if Fr is higher than 0.24, a U-shaped hull is more appropriate.

A Machine Learning and Feature Engineering Approach for the Prediction of the Uncontrolled Re-Entry of Space Objects

The continuously growing number of objects orbiting around the Earth is expected to be accompanied by an increasing frequency of objects re-entering the Earth’s atmosphere. Many of these re-entries will be uncontrolled, making their prediction challenging and subject to several uncertainties. Traditionally, re-entry predictions are based on the propagation of the object’s dynamics using state-of-the-art modelling techniques for the forces acting on the object. However, modelling errors, particularly related to the prediction of atmospheric drag, may result in poor prediction accuracies. In this context, we explored the possibility of performing a paradigm shift, from a physics-based approach to a data-driven approach. To this aim, we present the development of a deep learning model for the re-entry prediction of uncontrolled objects in Low Earth Orbit (LEO). The model is based on a modified version of the Sequence-to-Sequence architecture and is trained on the average altitude profile as derived from a set of Two-Line Element (TLE) data of over 400 bodies. The novelty of the work consists in introducing in the deep learning model, alongside the average altitude, and three new input features: a drag-like coefficient (B*), the average solar index, and the area-to-mass ratio of the object. The developed model was tested on a set of objects studied in the Inter-Agency Space Debris Coordination Committee (IADC) campaigns. The results show that the best performances are obtained on bodies characterised by the same drag-like coefficient and eccentricity distribution as the training set.

To study the Aerodynamic Effects of Spoiler of a Car (Sedan – Segment) using Computational Fluid Dynamics

Aerodynamic is an important aspect in consideration with regard to automotive design. Efficient diagnosis of aerodynamic forces’ effect on a car body becomes necessary when automobiles run at very high speed. In recent days, almost all automobile products coming into the market are designed considering the effect of aerodynamic forces.
 The objective of this analysis is to simulate the flow of air over a car body and to estimate the effect of aerodynamic forces like drag and lift. The prediction of drag becomes necessary for vehicle running at higher speeds, may lead to higher fuel consumption, dropping the efficiency. The induced “LIFT” will disconnect wheels and road, which may lead to accidents. The current analysis we are performing, will analyze the effect of these forces on car, with and without spoiler, to understand the spoiler’s presence helping in reducing the drag and its contribution to increase the efficiency of the car. Hypermesh is used for pre-processing and ANSYS Fluent is used as a solver and post processor.

Defining an equivalent homogeneous roughness length for turbulent boundary layers developing over patchy or heterogeneous surfaces

A new approach based on the power mean is suggested for defining an equivalent homogeneous roughness length kehr which takes into account patchiness or heterogeneous distribution of roughness on ship hulls and can be readily incorporated into existing full-scale drag prediction methods. In the limit where patch sizes are much greater than the boundary layer thickness, it is readily shown that the relationship between drag coefficient and roughness length is non-linear, highlighting an obvious source of error with current approaches that attempt to define an equivalent homogeneous roughness through an area-weighed arithmetic mean. The degree of error is dependent on the roughness distribution, but is estimated to exceed 16% for highly skewed beta heterogeneous distributions. For fully-rough models, the power-mean approach returns errors of <1% for the distributions tested here. The efficacy of the power-mean approach is also evaluated in the transitional regime and with different transitional roughness models (Nikuradse and Colebrook) and retains accuracy for most realistic operating scenarios.

Effect of interfacial area modeling method on interfacial drag predictions for two-fluid model calculations in large diameter pipes

The nuclear industry requires accurate modeling efforts to ensure safety standards are consistently achieved. To that end, the sensitivity of void fraction and interfacial area concentration predictions to changes in the interfacial area concentration modeling methods was evaluated. Several interfacial area concentration correlations and interfacial area transport equation coalescence and breakup models have been compared to the data of Schlegel et al. and Shen et al. using a computational tool developed in MATLAB. Bubble coalescence and breakup empirical constants were optimized for the group void fractions and interfacial area concentrations using the computational tool and the surface response method. The results indicate that the transport equation approach has a higher accuracy for both the void fraction and interfacial area concentration predictions than the correlation approach. The Smith et al. model is shown to have the highest void fraction predictive accuracy. The optimized model is shown to successfully increase accuracy of the interfacial area concentration prediction. This is also the highest accuracy observed for interfacial area concentration predictions.

Effects of Speed and Posture on Aerodynamic Characteristics of Running and Required Power

Types of running vary from jogging in parks to fast running in competitions. Humans strive for faster, stronger, and more sustainable running performances spanning short to long distances. In the near future, wearable devices will enable humans to run at high speeds and overcome human limits. Therefore, aerodynamic prediction is essential for the system design of a wearable device. This study focused on the aerodynamic drag and flow field according to the assumed human posture at takeoff and touchdown for various running speeds. Numerical simulations were conducted with the Reynolds-averaged Navier–Stokes equation, and a mathematical model, in conjunction with the use of simple geometric models, was developed to predict the aerodynamic drag. In addition, the power and energy were analyzed based on the generated aerodynamic drag. This study demonstrated the theoretical prediction of aerodynamic drag, and estimated the power and energy required to overcome it. The results from this study can be useful in the fields of sports, soft robotics, and biomechanics. Furthermore, the effects of wearable devices attached to the body on the aerodynamic drag can be analyzed by applying the presented methods, and this analysis is beneficial for the optimal design of wearable suits.

Field Measurement and Prediction of Drag in a Planted Rhizophora Mangrove Forest

AbstractDrag effects of mangrove forests with complex root systems modulate flow and substance transport and promote sedimentation, all of which are linked to mangroves' ecosystem services (e.g., coastal protection, trapping of suspended organic carbon) and resilience (e.g., vertical accretion relative to sea‐level rise). Previous flume studies proposed a predictive model of drag by Rhizophora mangrove forests based on the quadratic drag law using two parameters‐drag coefficient (CD) and vegetation projected area density (a). However, its general applicability to mangrove forests in the field has not been tested. To fill this knowledge gap, this study quantified drag in a 17‐year‐old planted Rhizophora mangrove forest using comprehensive measurements of hydrodynamics and vegetation morphology. The site showed a much higher value for a than the conditions assumed in previous flume studies, mainly due to root branching and high tree density. We found that despite the much higher vegetation complexity, the derived CD was 1.0 ± 0.2 for tide‐driven currents, consistent with previous flume studies. By using the mean value of derived CD (1.0), we confirmed that the quadratic drag model expresses well the field‐measured drag. We also showed that the value of parameter a can be predicted by only two vegetation parameters (stem diameter and tree density) using an empirical Rhizophora root model, and confirmed the successful prediction of drag from these vegetation parameters and the derived CD. This provides insights into effectively implementing the drag model in hydrodynamic models for better representation of flow, transport, and geomorphic dynamics in mangrove forests.

Accurate Stall Prediction for Thick Airfoil by Delayed Detached-Eddy Simulations

The continuous increase in wind turbine blade length raises a serious question about how to effectively reduce the blade mass. As one of the solutions, recently, some wind turbine manufacturers are moving towards longer blades with thicker airfoils. As most of the numerical simulation experiences are based on thin airfoils, the present paper focused on airfoils with thickness to chord ratios of 30% and specifically focused on the influence of spanwise length on the numerical results. Airfoils with a spanwise length of 0.1 to 5 chords were simulated utilizing the Delayed Detached-Eddy Simulations (DDES) approach. One of the important objectives was to identify the necessary grid resolution and configuration while still maintaining accuracy under a deep stall situation. It was found that the spanwise length of the computational domain had a crucial influence on the prediction of lift and drag. At a stall angle of attack, the aerodynamic force could not be accurately predicted when the airfoil span was reduced to 0.3 chords, even with a high grid density. The periodicity of the spanwise flow was clearly visible when the airfoil span was extended to 5 chords.

Drag decomposition of a subsonic wing via a far-field, exergy-based method

This paper focuses on the aerodynamic analysis and drag decomposition of an unpowered, low aspect ratio wing, using a far-field, exergy-based method. As opposed to traditional drag accounting methods, exergy balance provides insights into the amount of energy that can be potentially recovered off the body’s wake, which further translates into potential efficiency gains of the integrated engine-wing system. In this study, a far-field exergy balance method was used to determine the total drag of a three-dimensional wing. The far-field drag prediction was verified against near-field calculations. In addition, drag decomposition using exergetic terms was conducted to identify drag components that contain possibly recoverable energy. Such analysis can be subsequently used to educate the integration of a propulsion system to exploit the potentially recoverable wake energy and deliver an integrated engine-wing system with enhanced installed efficiency. The present methodology is a major step ahead in the application of far-field methods on three-dimensional wake domains and can potentially become a major enabler for optimal propulsion integration for future, novel aircraft-engine configurations.

Flight Simulation and Drag Prediction for a Pitching-Accelerating Hypersonic Reentry Vehicle

A nonwinged reentry vehicle, such as the upper stage of a ballistic missile, endures harsh aerodynamic loads during the phase of reentry. This phase is characterized by sophisticated flight phenomena including hypersonic speed, continuous variation of surrounding atmospheric conditions, and pitching transient vehicle motion. During the flight in this descent phase, drag is considered the dominant aerodynamic force where accurate prediction is crucial as far as reliable trajectory prediction and mission planning are concerned. This study aims to investigate drag on a generic bi-cone nonwinged reentry vehicle resembling an upper stage of a ballistic missile during descent. This is done by using both trajectory prediction and numerical simulation of vehicle–air interaction. To obtain the vehicle dynamics and instantaneous flight conditions through descending phase, a three-degree-of-freedom pitch flight trajectory model is utilized starting from point of separation. It was concluded that the vehicle experiences small-amplitude pitching motion while descending from about 90 to 30 km and accelerating in a hypersonic regime (Mach 5.7–7). Drag is then calculated via time-dependent numerical simulations. The results show the flowfield pattern evolution in addition to the temporal variation of drag on the vehicle during the flight phase in concern.

Effect of two-group void fraction covariance correlations on interfacial drag predictions for two-fluid model calculations in large diameter pipes

Effect of two-group void fraction covariance correlations on interfacial drag predictions for two-fluid model calculations in large diameter pipes

Novel numerical results for heat transfer along a stretching cylinder immersed in a shear-thinning fluid

Boundary layer formation over a moving or stationary surface has a wide range of applications in aerodynamics, heat transfer enhancement, and prediction of drag or resistance on a surface. Furthermore, viscosity changes with deformation cannot be ignored in almost all industrially vital fluids. Present work describes boundary layer development around a cylinder stretching axially in a shear-thinning fluid obeying Carreau model. Accompanying heat transfer problem is analyzed in the existence of frictional heating and Joule heating terms in the thermal energy equation. Previous studies concerning Carreau fluid flow driven by a stretching cylinder are discussed with a view to point out some errors concerning mathematical modeling. For computational results, a widely employed MATLAB package bvp4c is utilized, which is based on a collocation scheme. New numerical results of the resulting six parameter problem are worked out, which are utilized to assess the contribution of surface curvature on the flow fields in the presence of a shear-thinning effect. The results show that the fluid velocity is considerably enhanced for larger values of flow index behavior . In the presence of a magnetic field, momentum diffusion is significantly reduced while temperature profile is expanded.

A wave damping model for flexible marsh plants with leaves considering linear to weakly nonlinear wave conditions

Marsh plants protect the coasts and coastal communities by dissipating wave energy. The dissipation of wave energy depends on the geometric (leaf and stem dimensions) and mechanical (material rigidity) properties of the plants. First, flexible plants bend in response to hydrodynamic drag (called reconfiguration), which diminishes wave decay relative to a rigid plant of the same morphology. Second, mutual sheltering between plant leaves and stem can reduce the drag, and thus wave damping. This study connects the prediction of drag on an individual plant and the measurement of wave decay over a meadow of plants to build a physically-based wave-damping model that includes leaves, the impact of reconfiguration, and the impact of sheltering between plant elements. Model plants were constructed to be both geometrically and dynamically similar to Spartina alterniflora . The wave damping model assumed linear wave conditions, but was validated using a wide range of weakly nonlinear wave conditions within model plants, over a patch of live Spartina anglica in the laboratory, and over a meadow of Spartina alterniflora in the field. After validation, the model was used to explore the variation in wave decay over a range of wave parameters and plant geometric and bio-mechanic parameters, including stem length, stem diameter, number of leaves per plant, leaf length, leaf width, the rigidity of the stem and the leaf. • A physics-based prediction for wave dissipation by flexible marsh plants with leaves was developed and validated with laboratory experiments. • The dependence of wave dissipation on water depth, wave amplitude, and wave period was explored in detail with model predictions. • The impact of leaf and stem geometry and mechanical properties on wave dissipation were revealed by systematic model predictions.

Partial Pressure Field for Airfoil Wave Drag

Far-field drag prediction methods have proven to be effective at capturing drag sources in both computational fluid dynamics and wind-tunnel testing analyses. Near-field decomposition, on the other hand, has been neglected due to the failure to divide pressure drag directly into its contributions to both form and wave drag. The work presented in this paper is an extension of previous research conducted into partial pressure fields that allow such a near-field drag decomposition. In particular, the current paper proposes a new partial pressure field that captures wave drag sources in two-dimensional compressible viscous flow. Pressure decompositions are performed on the conventional NACA0012 and RAE2822 airfoils, and the results are compared to those obtained by classical far-field decomposition, with reference data from previous studies providing a means of verification. Finally, the slotted natural laminar-flow airfoil, the S207, is analyzed to test the applicability of the decomposition method on multielement airfoils that are considered for next-generation aircraft design. It is demonstrated that an adjusted compressible pressure field captures wave drag as a reliable near-field method that correlates closely with the traditional far-field methods, particularly for typical transonic cases.

Calibration of the Critical Amplification Factor for Reynolds-Averaged Navier–Stokes-Based Transition Modeling

The present study uses an adjoint-based gradient optimization framework to perform calibration of the critical amplification factor for transition models based on the linear stability theory. More specifically, the two-equation amplification factor transport model is used, and the critical amplification factor, which directly controls the onset of the transition via the source term of the intermittency equation, is calibrated for a set of canonical flat plate test cases in both bypass and natural transitional regimes. It is shown that, by utilizing a sigmoid fitting of the turbulence index profile, the transition onset location can be accurately predicted in a differentiable and smooth fashion, which is essential to the adjoint-based sensitivity analysis of the Reynolds-averaged Navier–Stokes solver. Subsequently, the results of these calibration studies are used for obtaining a new relation via a high-order polynomial regression model relating the critical amplification factor to the freestream turbulence intensity. Finally, the prediction capability of the calibrated relation is tested for natural transitional flows past NLF(1)-0416 and S809 airfoils. The numerical results show significant improvements in predicting the transition onset location as well as lift and drag predictions.

Ground Track Control Using Differential Drag for Small Earth Observation Satellite Constellations

This paper presents a framework for the acquisition and the maintenance of ground track configurations of small Earth observation satellite constellations. Specifically, the relative ground track spacings at the equator are controlled using differential drag to achieve the desired Earth coverage pattern without a propulsion system. The proposed framework is based on a divide-and-conquer approach to solving the optimal differential drag constellation management problem and comprises five processes for solving the related subproblems. The proposed framework can be used to manage end-to-end applications, from establishing the initial acquisition plan for the target ground track configuration, to the closed-loop command generation for the ground track acquisition and maintenance. Using the proposed framework, optimal acquisition plans with the minimum time and minimum altitude losses can be identified in a systematic way. The usefulness of the proposed method is demonstrated based on simulations incorporating the uncertainties in drag prediction.