Surface Pressure Distribution Research Articles

Neural fields for rapid aircraft aerodynamics simulations

This paper presents a methodology to learn surrogate models of steady state fluid dynamics simulations on meshed domains, based on Implicit Neural Representations (INRs). The proposed models can be applied directly to unstructured domains for different flow conditions, handle non-parametric 3D geometric variations, and generalize to unseen shapes at test time. The coordinate-based formulation naturally leads to robustness with respect to discretization, allowing an excellent trade-off between computational cost (memory footprint and training time) and accuracy. The method is demonstrated on two industrially relevant applications: a RANS dataset of the two-dimensional compressible flow over a transonic airfoil and a dataset of the surface pressure distribution over 3D wings, including shape, inflow condition, and control surface deflection variations. On the considered test cases, our approach achieves a more than three times lower test error and significantly improves generalization error on unseen geometries compared to state-of-the-art Graph Neural Network architectures. Remarkably, the method can drastically accelerate high fidelity numerical solver, achieving a five order of magnitude speedup on the RANS transonic airfoil dataset.

A Theoretical and Experimental Investigation of the Effects of Inverted Wings Modifications on the Stability and Aerodynamic Performance of a Sedan Car at Cornering

ABSTRACTThis research examines the impact of cornering on the aerodynamic forces and stability of a Nissan Versa (Almera) passenger sedan car by introducing novel modifications. These modifications included single inverted wings with end plates as a front spoiler, double‐element inverted wings with end plates as a rear spoiler, and incorporating the ground as a diffuser under the car trunk. The goal is to enhance the performance and stability of conventional passenger cars. To ensure the accuracy of the numerical data, the study utilized multiple methodologies to model the turbulence model, ultimately selecting the most suitable option. This involved comparing numerical data with wind tunnel experimental data using force balance and pressure distribution. Once validated, the computational fluid dynamics (CFD) was employed to analyze the vehicle's aerodynamic performance relative to the straight‐line condition under cornering conditions. The car simulation in a cornering condition was conducted at a representative Reynolds number based on the vehicle length of about 1.3 × 107. The study discovered that asymmetry was a recurring theme regarding surface pressure distribution, with greater prominence under cornering conditions. All modified models exhibited a more favorable lift‐to‐drag ratio than the baseline, indicating improved aerodynamic efficiency. The underbody double‐element diffuser proved most effective for enhancing fuel efficiency and stability. Mesh refinement with a polyhedral algorithm consisting of 11.27 million elements and a computational domain with a frontal area of 91.8 m2 and a curved length of 31 m (˜7 times car length) was crucial for achieving accurate and repeatable results. The study employed multiple turbulence models within the CFD framework. The realizable k‐ε model was chosen due to its balance between accuracy and computational cost for all Nissan Versa models. These findings are limited to the selected parameters and wind tunnel conditions, and further investigations might be needed for extreme driving scenarios.

Surface pressure reconstruction from LPT data with boundary conforming grids

Abstract The coupling between fluid-structure interactions is governed by the pressure distribution over the interaction surface between the fluid and solid domains. The capabilities of non-intrusive optical techniques, such as particle image velocimetry and Lagrangian particle tracking (LPT), have been proven to provide accurate velocity and acceleration information within the flow field while simultaneously tracking the corresponding structural deformations. However, scattered data from LPT measurements are typically mapped onto Cartesian grids, independently of the shape of the solid objects in the measurement domain. The use of Cartesian grids poses challenges for the determination of the surface pressure because the velocity gradients close to the object’s surface are not captured accurately. Therefore, an alternative surface pressure reconstruction scheme utilizing LPT data based on the arbitrary Lagrangian–Eulerian approach is proposed to mitigate the error propagation associated with the use of uniform grids. The introduced method provides an exact surface conformation utilizing boundary fitted coordinate systems and radial basis function based mesh deformations, which eliminates the need to use extrapolations to obtain surface pressure distributions. The introduced approach is assessed by means of a synthetic hill surface probing a three-dimensional analytical flow field; its practical applicability is demonstrated through an experimental characterization of turbulent boundary layer interactions with a steadily and unsteadily deforming elastic membrane.

Wall-Modeled Large-Eddy Simulation Method for Unstructured-Grid Navier–Stokes Solvers

This paper reports on the implementation and assessment of a wall-modeled large-eddy simulation (WMLES) methodology in an unstructured-grid, node-centered flow solver, FUN3D, that is developed and supported at the NASA Langley Research Center. Finite-volume (FV) and finite-element (FE) discretization schemes considered in the study provide formal second-order spatial accuracy. Large-eddy simulations (LES) resolve large-scale turbulent-flow features, and small-scale effects are modeled using the Vreman subgrid-scale model. At solid-wall boundaries, a shear-stress model is employed to provide a proper boundary-flux closure. The nonlinear equations are integrated in time using either an optimized backward difference formula or an implicit multistage Runge–Kutta temporal scheme. The implicit equations at each time step are solved by strong nonlinear iteration schemes. WMLES demonstrations are shown for two high-lift configurations, namely, the McDonnell Douglas 30P30N multi-element airfoil and a NASA High-Lift Common Research Model. Results show that the WMLES approaches implemented in the FV and FE discretization methods produce consistent solutions and are capable of capturing key aerodynamic characteristics and flow structures for high-lift configurations at a wide range of angles of attack, including maximum-lift conditions. In the 30P30N example, correct trends in the variations of integrated aerodynamic forces and moments, surface pressure distributions, and boundary-layer profiles are captured as the Reynolds number is increased.

Experimental investigation on the aerodynamics and flow patterns of a 5:1 rectangular cylinder with spoilers

The current study experimentally investigates a passive control method for the flow field by placing spoilers symmetrically on the leading edge of a 5:1 rectangular cylinder. The Reynolds number (Re) is based on the inflow velocity and the height of the model. The length of the spoiler is equal to the span length of the model, and the width and angle are defined as w and α. At Re = 1.07 2.50×104, the surface pressure distribution of the model is obtained to initially investigate the effects of α and w on the aerodynamic characteristics. Based on the aerodynamic results, some cases are selected to reveal the control mechanism using the particle image velocimetry (PIV) technique. The proper orthogonal decomposition (POD) is adopted to analyze the POD modes and instantaneous flow. The results show that the spoiler with a certain α can suppress the aerodynamic forces of the model. Spoilers with a relative angle of 247.5° significantly reduce CL′ by 75 % and slightly reduce CD¯ by 5.5 %. Also, its TKE and RSS values are reduced by 56 % and 57 %, respectively. The PIV visualization shows that the spoiler affects the flow separation at the leading edge. Then, the rolling and interactions of shear layers are suppressed, making them tend to be parallel. Besides, spoilers with a relative angle of 67.5° almost eliminate the flow separation.

Research on UAV Downwash Airflow and Wind-Induced Response Characteristics of Rapeseed Seedling Stage Based on Computational Fluid Dynamics Simulation

Multi-rotor unmanned aerial vehicles (UAVs) are increasingly prevalent due to technological advancements. During rapeseed’s seedling stage, UAV-generated airflow, known as wind-induced response, affects leaf movement, tied to airflow speed and distribution. Understanding wind-induced response aids early rapeseed lodging prediction. Determining airflow distribution at various UAV heights is crucial for wind-induced response study, yet lacks theoretical guidance. In this study, Computational Fluid Dynamics (CFD) was employed to analyze airflow distribution at different UAV heights. Fluid–solid coupling simulation assessed 3D rapeseed model motion and surface pressure distribution in UAV downwash airflow. Validation occurred via wind speed experiments. Optimal uniform airflow distribution was observed at 2 m UAV height, with a wind speed variation coefficient of 0.258. The simulation showed greater vertical than horizontal leaf displacement, with elastic modulus inversely affecting displacement and leaf area directly. Discrepancies within 10.5% in the 0.5–0.8 m height range above the rapeseed canopy validated simulation accuracy. This study guides UAV height selection, leaf point determination, and wind-induced response parameter identification for rapeseed seedling stage wind-induced response research.

Pollutant cross-transmission in courtyard buildings: Wind tunnel experiments and computational fluid dynamics (CFD) evaluation

Courtyards, a historical architectural feature surrounded by buildings, are common in urban housing and residential complexes. These spaces, often open-air and with rooms facing them, are crucial for daylight and natural ventilation. While courtyards are essential for introducing fresh airflow into adjacent indoor areas, the effectiveness of natural ventilation may be compromised due to potentially poor air circulation from limited openings. This raises a significant concern: could the design of courtyards inadvertently facilitate pollutant cross-transmission? Despite a wealth of research focused on airflow within courtyards, the indoor spaces in proximity to these courtyards have often been neglected in previous works, particularly concerning the exchange of pollutants between the indoor and courtyard environment. This research investigates the dynamics of indoor-outdoor pollutant cross-transmission in courtyard buildings, assessing factors like external wind flow patterns and internal pollutant sources. Wind tunnel experiments were conducted to measure internal pressure and CO2 concentration and to validate a computational model of the courtyard with 12 rooms. The validated Computational Fluid Dynamics (CFD) models were used to simulate the dispersion of pollutants from internal rooms under different wind conditions. The results showed that the k-epsilon Realizable model accurately simulated internal surface pressure distribution and pollutant dispersion in the courtyard building. It was observed that when pollutants were released from the downwind east-facing ground floor room, CO2 concentrations in adjacent side rooms on the same floor were significantly higher, increasing from the baseline of 400 ppm and reaching up to 3211 ppm in the north-facing room at a wind speed of 4.51 m/s and wind direction of 0°. Conversely, when pollutants originated from north- and south-facing side rooms, pollutants were minimally dispersed to adjacent rooms. Furthermore, at a wind direction of 45°, pollutants from wind-exposed rooms predominantly dispersed to downwind rooms, with peak concentrations exceeding 2400 ppm in downwind rooms. These findings demonstrate that pollutant dispersion is highly dependent on wind direction and the location of the pollutant source. The study concludes that while courtyards enhance indoor environmental quality through natural ventilation, their design must be carefully considered to prevent unintended pollutant cross-transmission, particularly under varying wind conditions and pollutant source locations.

Systematical study on the aerodynamic control mechanisms of a 1:2 rectangular cylinder with Kirigami scales

Biomimetic flow control is being widely applied. In the present study, a biomimetic flow control method, i.e., Kirigami scales, was applied on a 1:2 rectangular cylinder. The effects of scales' shapes and pasting surfaces on the aerodynamics and circumferential flow patterns of a 1:2 rectangular cylinder were studied. Three scale shapes were investigated with different pasting methods, i.e., elliptical, circular, and triangular scales. The Reynolds number (Re) was set at 1.3–3.1 × 104. The surface pressure distributions and the integrated aerodynamic forces were further analyzed at Re = 1.3 × 104. Results show that pasting the elliptical scales on all surfaces performs best, reaching a 2.4% drag reduction and a 76.4% lift reduction. Moreover, the elliptical and triangular scales on the windward and leeward surfaces can significantly reduce the Re effect. To reveal the control mechanism, the particle image velocimetry technique was employed to obtain the circumferential and wake flow fields. The time-averaged and phase-averaged results indicate that the Kirigami scales can push the interactions of shear layers and the shedding vortices further downstream. The Proper orthogonal decomposition analysis and time-averaged turbulent kinetic energy (TKE) results indicate that the wake vortex shedding is significantly suppressed. The spanwise wake flow field was also investigated. Results show that the spanwise TKE values are significantly reduced. This study further deepened the application of Kirigami scales on the common blunt bodies.

Transferable machine learning model for the aerodynamic prediction of swept wings

With their development, machine learning models can be used instead of computational fluid dynamics simulations to predict flow fields in aerodynamic optimization. However, it is difficult to construct a prediction model for swept wings with various planform geometries because too many samples are required to cover the parameter space. In the present paper, a new model framework is proposed to predict wing surface pressure and friction distributions with fewer samples. The distributed geometry parameters along spanwise are used as model inputs instead of the global planform parameters, and processors are designed to help the model better learn the local effect of geometric variation. The model is trained and tested on simple swept wings with single segment and linear twist distribution, where it outperforms the global input model by 57.6% in terms of lift coefficient prediction errors on small dataset sizes. The distributed input also enables the model to be transferred from single wings to more engineering-practical yet complex kink wings. After fine-tuning with a few samples, model accuracy for kink wings can be similar to that of simple wings, which proves the model for wings with complex planform geometries can be efficiently built with the proposed method.

Prediction model of aircraft hinge moment: Compressed sensing based on proper orthogonal decomposition

By hinge moment, we mean the aerodynamic torque exerted on the rudder shaft by the airflow passing through the aircraft control surface, with obtaining high-precision results often relying on wind tunnel tests. Due to the complex aerodynamic balance insulation and installation errors that must be considered in cryogenic wind tunnels, the main method for calculating hinge moments is to directly integrate surface pressure distribution information. However, it is usually difficult to arrange enough pressure taps, resulting in the accuracy failing to meet expectations. Combining the sparse wind tunnel test data and low-precision computational fluid dynamics results, this paper introduces the compressed sensing based on proper orthogonal decomposition (CS-POD) method and presents the sub-Ma model and the full-Ma model for predicting hinge moments. The number of sensors and sensor positions are determined based on the sparsity of the numerical simulations and basis functions. Then, the CS algorithm solves the basis coefficients. Finally, the hinge moments are obtained by integrating the reconstruction pressure distribution which is calculated by linearly combining the basis functions and basis coefficients. The result shows that the full-Ma model exhibits higher prediction accuracy with approximately five sensors under subsonic and transonic cases, reducing the relative error of the sub-Ma model by 2–10 times, even at high angles of attack. The mean reconstruction accuracy for the hinge moments is 97.6%, and for the normal forces, it is 94.3%. Therefore, adding relevant terms when the number of samples is small can effectively improve modeling accuracy.

On the sound field of an oscillating elliptical disk in free space with an open and closed back.

An oscillating elliptical disk in free space has a uniform surface velocity distribution and is therefore a rigid sound radiator. The radiated sound also represents that scattered from a stationary disk in the presence of a normal plane wave. Using the Fourier (Hankel) Green's function in cylindrical coordinates, together with the monopole Kirchhoff-Helmholtz boundary integral, rigorous analytical formulas are derived for calculating the surface pressure distribution, radiation impedance, on-axis pressure, and, directivity pattern of an elliptical open-back disk in free space, and these are plotted over a range of normalized frequencies. The directivity is compared with that of a rigid circular disk in free space, and asymptotic low-frequency approximations are derived for the radiation impedance and on-axis pressure. Using the Gutin concept, the radiated sound is combined with that from a rigid elliptical disk in an infinite baffle to obtain the radiation impedance, on-axis pressure, and, directivity pattern of a closed-back elliptical disk in free space. The latter has a uniform velocity distribution on the front surface and zero velocity over the entire back surface.

Comparison of Pressure-based and Skin Friction-based Methods for the Determination of Flow Separation of a Circular Cylinder with Roundness Imperfection

Introduction: A delayed detached eddy simulation in Open FOAM was performed to study flow separation of a circular cylinder with roundness imperfection up to 4% of its diameter at Reynolds numbers of 100, 3900, and 104 in normal flow. Methods: The flow was considered to be Newtonian and incompressible. The separation position was determined independently based on surface pressure distribution and skin friction. Results: Results show that the patterns of these distributions depend on both Reynolds number and roundness imperfection level, and flow separation in an imperfectly round cylinder may be induced by either an adverse pressure gradient or a Gentle Bend (GB) introduced by the roughness. For the separation point determined by the pressure-based method, its accuracy can be affected by the characteristic of pressure distribution near the separation point at low Reynolds numbers, and, thus, its physical validity needs to be verified by flow visualization at high Reynolds numbers. Conclusion: The skin friction-based method can accurately predict separation point for both perfectly and imperfectly round cylinders without additional information. When the roundness imperfection ratio reaches 2% and the Reynolds number reaches 3900, both approaches indicate that the flow separation point converges to the location of GB on the cylinder surface and the two sets of predicted separation points agree well.

Study on the free surface evolution and slamming pressure of curved-wedge water entry using a Riemann-smoothed particle hydrodynamics method

The present study aims to provide a deep understanding of curved wedge water entry. It involves a numerical simulation investigation into the kinematic and dynamic properties of water entry for two curved wedges with deadrise angles of 25° and 35°. The meshless Riemann-smoothed particle hydrodynamics (SPH) model embedded with an acoustic damper is developed to simulate these violent water entries. The validation of the Riemann-SPH accuracy is confirmed through comparison with experimental data, and subsequently, we make a systematical simulation study on curved wedge water entry, including a comparative study of free surface evolution and pressure distribution at different curvatures and drop heights. Furthermore, the kinematics analysis of velocity and displacement of curved wedges and time domain characteristics of slamming pressure loads on both sides of the wedge are investigated. It is revealed that the pressure distribution is symmetrical, with high-pressure regions forming near the bottom of the wedge and gradually propagating outward. The free surface profiles are symmetrical, with deeper depressions formed by sharper wedges. The entry depth and velocity are correlated with the initial theoretical entry velocity, and the rate of speed decline varies with the curvature of the wedge. The slamming pressure loads exhibit distinct time-domain patterns, with lower pressure loads by sharper wedges.

Characterization of the Endwall Flow in a Low-Pressure Turbine Cascade Perturbed by Periodically Incoming Wakes, Part 2: Unsteady Blade Surface Measurements Using Pressure-Sensitive Paint

Unsteady pressure-sensitive paint (i-PSP) measurements were performed at a sampling rate of 30 kHz to investigate the near-endwall blade suction surface flow inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions. The investigation focuses on the interaction of periodically incoming bar wakes at 500 Hz with the secondary flow and the blade suction surface. The results build on extensive PIV measurements presented in the first part of this two-part publication, which captured the ’negative-jet-effect’ of the wakes throughout the blade passage. The surface pressure distributions are combined with CFD to analyze the flow topology, such as the passage vortex separation line. By analyzing data from phase-locked PIV and PSP measurements, a wake-induced moving pressure gradient negative in space and positive in time is found, which is intensified in the secondary flow region by 33% with respect to midspan. Furthermore, two methods of frequency-filtering based on FFT and SPOD are compared and utilized to associate a pressure fluctuation peak around 678 Hz with separation bubble oscillation.

Influence of Sweep Angle on the Surface Pressure of Delta Wing Along Pivot Positions at Hypersonic Mach Numbers

Influence of Sweep Angle on the Surface Pressure of Delta Wing Along Pivot Positions at Hypersonic Mach Numbers

Effect of static compression on near-field tsunami waves: Three-dimensional solution

An analytical solution of three-dimensional surface wave profiles due to arbitrary spatio-temporal disturbance of a circular ocean bottom in a compressible ocean is obtained by incorporating the influence of the static ocean background compression under the assumptions of linearized water wave theory. Time-domain simulations of the surface profile in three dimensions and the pressure distribution within the water column for a circular uniform rise and tilt are shown. The corresponding animation movies depict the temporal evolution of the surface profile and pressure field inside the water column eloquently, which was not shown in earlier literature. The impact of static compression is also discussed through the simulations. A novel analytical expression of the potential function for a generic tilted motion (rmcos(mθ),m∈Z) of the circular ocean floor is derived. An efficient numerical code is developed to find surface elevation and pressure distribution, implementing the inverse Fourier integral as matrix multiplication. Validation is performed for the specific case of a rising flat ocean floor, showing the oscillations due to acoustic-gravity modes. Initially, a simplified problem of a flat rising ocean bottom is solved using the eigenfunction matching method, which involves finding a particular solution for the nonhomogeneous ocean bottom condition and the solution for its homogeneous counterpart. Solutions are obtained using a newly developed inner product between the depth-dependent functions. Later, a Green function technique is used to incorporate the impact of the arbitrary spatio-temporal motion of the circular portion of the ocean bed. The solution obtained from the eigenfunction matching method is utilized to obtain the analytical form of Green’s function and, eventually, an expression of surface elevation and pressure distribution inside the ocean water column.

Aerodynamic characteristic analysis of blast wave lateral sweeping aircraft based on CFD transient numerical simulation method

Blast wave overpressure and dynamic pressure significantly change the surface pressure distribution of the aircraft and resulting in transient aerodynamic forces when the blast wave sweeps the aircraft laterally. These transient aerodynamic forces will pose a serious threat to flight safety. In this paper, the aerodynamic parameters of aircraft components under lateral sweep of blast waves are studied by the Computational Fluid Dynamics (CFD) numerical simulation method, and the waveform characteristics of the dominant aerodynamic parameters of the aircraft key components are analyzed according to the CFD simulation results. The research method can provide reference and guidance for the study of aircraft flight safety under blast wave sweeping.

A Highly Sensitive and Stretchable Core-Shell Fiber Sensor for Gesture Recognition and Surface Pressure Distribution Monitoring.

This work reports a highly-strain flexible fiber sensor with a core-shell structure utilizes a unique swelling diffusion technique to infiltrate carbon nanotubes (CNTs) into the surface layer of Ecoflex fibers. Compared with traditional blended Ecoflex/CNTs fibers, this manufacturing process ensures that the sensor maintains the mechanical properties (923% strain) of the Ecoflex fiber while also improving sensitivity (gauge factor is up to 3716). By adjusting the penetration time during fabrication, the sensor can be customized for different uses. As an application demonstration, the fiber sensor is integrated into the glove to develop a wearable gesture language recognition system with high sensitivity and precision. Additionally, the authors successfully monitor the pressure distribution on the curved surface of a soccer ball by winding the fiber sensor along the ball's surface.

A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings

Traditional methods of evaluating the performance of journal bearings, for example thermal-elastic-hydrodynamic- lubrication theory, are limited to simplified conditions that often fail to accurately model real-world components. Numerical models that include additional phenomena such as cavitation and fully coupled effects like deformation, temperature, pressure and viscosity can be more accurate but require a large amount of computational overhead, making analysis slower and more costly. To address this limitation, a novel machine learning-driven approach is developed to predict the 2D distribution of surface deformation, film thickness, temperature, and pressure across the bearing surface as a function of design variables such as load and speed. The training dataset, generated using a fully coupled Reynolds’ Equation solver implemented in OpenFOAM, contains a significantly extended range of conditions than in previous studies with approximately 39000000 points encompassing 4925 different test cases. Modelled bearing speeds range from 2000 to 10000rpm, while load values are varied between 1 and 30kN. Predicting surface deformation, film thickness, temperature and pressure across the bearing surface results in a mean absolute percentage error below 0.4% or better. The work also demonstrates that the trained models have a strong ability to generalise the prediction beyond the original training data range with only a 1% error at up to 200% of the highest trained speed. This work also demonstrates that machine learning-based processes are a practical alternative to physics-based numerical modelling, especially in cases where rapid performance evaluation is desired as real-time calculation is possible with significantly reduced computational cost. This has the potential to enable development of rapid design optimisation tools and real-time performance monitoring at high resolution and with low latency. Using consumer hardware, it is found that the neural network-based approach is faster than the existing numerical modelling technique by a factor of over 10000, enabling real-time predictions of lubrication systems.

Potential impact of Aeroclipper observations targeting tropical cyclone in the Western Pacific

AbstractThe Aeroclipper is a new balloon device that can be attracted and captured by tropical cyclones (TC) and perform continuous in situ measurements at the air–sea interfaces. To estimate the potential effect of Aeroclipper observations on the analysis of TCs, virtual Aeroclipper observations targeting TC Haima (October 2016) were synthesized using an idealized surface pressure distribution and best track data and were assimilated using an ensemble data assimilation system. Results show that the assimilation of Aeroclipper measurements may provide a more accurate representation of the TC pressure, wind, and temperature in analyses. This also leads to improved precipitation around the Philippines. The ensemble spread shows that the Aeroclipper measurement assimilation has an impact on the analyses that extends into the tropics from the early stages of TC development. These impact signals propagate westward with easterly waves and eastward with large‐scale convective disturbances. Although the underlying mechanisms need to be further examined and tested using real Aeroclipper measurements, the present study shows that these balloons could provide valuable observations to improve the precision of analyses in presence of a TC. This is a first step toward a study of the impact of the Aeroclipper measurement on TC forecast.