Search Results (138)

During the process of flexible aerial refueling, the flexible structure of the hose drogue assembly is affected by internal and external interference, such as docking maneuvering, deformation of the hose, attitude changes, and body vibrations, causing the hose to swing and the whipping phenomenon, which greatly limits the success rate and safety of aerial refueling operations. Based on a 2.4 m transonic wind tunnel, high-speed wind tunnel test technology of a flexible aerial refueling hose–drogue system was established to carry out experimental research on the coupling characteristics of aerodynamics and multi-body dynamics. Based on the aid of Videogrammetry Model Deformation (VMD), high-speed photography, dynamic balance, and other wind tunnel test technologies, the dynamic characteristics of the hose–drogue system in a high-speed airflow and during the approach of the receiver are obtained. Adopting flexible multi-body dynamics, a dynamic system of the tanker, hose, drogue, and receiver is modeled. The cable/beam model is based on an arbitrary Lagrange–Euler method, and the absolute node coordinate method is used to describe the deformation, movement, and length variation in the hose during both winding and unwinding. The aerodynamic forces of the tanker, receiver, hose, and drogue are modeled, reflecting the coupling influence of movement of the tanker and receiver, the deformation of the hose and drogue, and the aerodynamic forces on each other. The tests show that during the approach of the receiver (distance from 1000 mm to 20 mm), the sinking amount of the drogue increases by 31 mm; due to the offset of the receiver probe, the drogue moves sideways from the symmetric plane of the receiver. Meanwhile, the oscillation magnitude of the drogue increases (from 33 to 48 and from 48 to 80 in spanwise and longitudinal directions, respectively). The simulation results show that the shear force induced by the oscillation of the hose and the propagation velocity of both the longitudinal and shear waves are affected by the hose stiffness and Mach number. The results presented in this work can be of great reference to further increase the safety of aerial refueling. Full article

The aerodynamic optimization of airfoil shapes remains a critical research area for enhancing aircraft performance under various flight conditions. In this study, the RAE 2822 airfoil was selected as a benchmark case to investigate and compare the effectiveness of surrogate-based methods under an Efficient Global Optimization (EGO) framework and an adjoint-based approach in both single-point and multi-point optimization settings. Prior to optimization, the computational fluid dynamics (CFD) model was validated against experimental data to ensure accuracy. For the surrogate-based methods, Kriging (KRG), Kriging with Partial Least Squares (KPLS), Gradient-Enhanced Kriging (GEK), and Gradient-Enhanced Kriging with Partial Least Squares (GEKPLS) were employed. In the single-point optimization, the GEK method achieved the highest drag reduction, outperforming other approaches, while in the multi-point case, GEKPLS provided the best overall improvement. Detailed comparisons were made against existing literature results, with the proposed methods showing competitive and superior performance, particularly in viscous, transonic conditions. The results underline the importance of incorporating gradient information into surrogate models for achieving high-fidelity aerodynamic optimizations. The study demonstrates that surrogate-based methods, especially those enriched with gradient information, can effectively match or exceed the performance of gradient-based adjoint methods within reasonable computational costs. Full article

In this study, an optimization framework for turbomachinery blades using a hybrid surrogate model assisted by proper orthogonal decomposition (POD) is introduced and then applied to the aero-structural multidisciplinary design optimization of a transonic fan rotor, NASA Rotor 67. The rotor blade is optimized through blade sweeping controlled by Gaussian radial basis functions. Calculations of aerodynamic and structural performance are achieved through computational fluid dynamics and computational structural mechanics. With a number of performance snapshots, singular value decomposition is employed to extract the basis modes, which are then used as the kernel functions in training the POD-based hybrid model. The inverse multi-quadratic radial basis function is adopted to construct the response surfaces for the coefficients of kernel functions. Aerodynamic design optimization is first investigated to preliminarily explore the impact of blade sweeping. In the aero-structural optimization, the aerodynamic performance, and von Mises stress are considered equally important and incorporated into one single objective function with different weight coefficients. The results are given and compared in detail, demonstrating that the average stress is dependent on the aerodynamic loading, and the configuration with forward sweeping on inner spans and backward sweeping on outer spans is the most effective for increasing the adiabatic efficiency while decreasing the average stress when the total pressure ratio is constrained. Through this study, the optimization framework is validated and a practical configuration for reducing the stress in a transonic fan rotor is provided. Full article

Kolmogorov–Arnold Networks (KANs) are a recent development in machine learning, offering strong functional representation capabilities, enhanced interpretability, and reduced parameter complexity. Leveraging these advantages, this paper proposes a KAN-based reduced-order model (ROM) for unsteady aerodynamics and aeroelasticity. To effectively capture temporal dependencies inherent in nonlinear unsteady flow phenomena, an architecture termed Kolmogorov–Arnold Gated Recurrent Network (KAGRN) is introduced. By incorporating a recurrent structure and a gating mechanism, the proposed model effectively captures time-delay effects and enables the selective control and preservation of long-term temporal dependencies. This architecture provides high predictive accuracy, good generalization capability, and fast prediction speed. The performance of the model is evaluated using simulations of the NACA (National Advisory Committee for Aeronautics) 64A010 airfoil undergoing harmonic motion and limit cycle oscillations in transonic flow conditions. Results demonstrate that the proposed model can not only accurately and efficiently predict unsteady aerodynamic coefficients, but also effectively capture nonlinear aeroelastic responses. Full article

Airfoil aerodynamic design represents an essential domain in aircraft development, where the pursuit of advanced and intelligent optimization strategies is important for achieving significant advancements. In this paper, we demonstrate the effectiveness and versatility of reinforcement learning (RL)-based optimization methods in enhancing aerodynamic performance for both transonic and supersonic airfoils. We introduced a novel methodology using RL to optimize airfoil designs, leveraging ADflow as the aerodynamic solver and constructing an RL environment where Class-Shape Transformation (CST) parameters describe the airfoil geometry, transforming it into a finite state variable. Key flow field features, especially shock waves, were incorporated to guide the optimization process, enabling the RL model to iteratively improve designs based on real-time feedback from simulations. Applied to transonic airfoils, this method yielded remarkable results, including a 70.20% increase in the lift-to-drag ratio for one airfoil, with consistent improvements across various initial geometries and flight conditions. Extending to the NASA SC(2)-0404 supersonic airfoil, the optimized design achieved significant geometric changes that resulted in a 6.25% increase in the lift-to-drag ratio, with improvements ranging from 4.90% to 25.46% across different lift coefficients. These findings highlight the robustness and adaptability of RL techniques in addressing the unique challenges of both transonic and supersonic aerodynamics while maintaining structural integrity. Full article

In the present paper, a reduced-order modeling (ROM) approach based on a hybrid neural network is presented in order to calculate wing buffet pressure distributions due to structural eigenmode-based deformations. The accurate prediction of unsteady surface pressure distributions is crucial for assessing aeroelastic stability and preventing structural failure, but full-order simulations are computationally expensive; the proposed ROM provides a fast and efficient alternative with a sufficient level of accuracy. The hybrid ROM is defined by a series connection of a convolutional autoencoder (CNN-AE) and a long short-term memory (LSTM) neural network. As a test case, the NASA Common Research Model (CRM) configuration for the transonic buffet condition is applied. Forced-motion computational fluid dynamics (CFD) simulations are conducted in order to obtain the aerodynamic responses induced by the eigenmode-based deformations. For the unsteady simulations, the triangular adaptive upwind (TAU) solver of the German Aerospace Center (DLR), is used. Based on a selected structural model, symmetric and asymmetric eigenmode-based deformations of the wing structure are implemented and considered for performance evaluation. Comparing the pressure loads modeled by the hybrid ROM and the reference full-order numerical solution, an overall good prediction performance is indicated with mean squared error (MSE) values mostly below $3\%$, reaching local maxima of about $12\%$, due to strong pressure gradients associated with pronounced shock oscillations. Full article

Multi-stage axial compressors play a crucial role in aerospace propulsion systems, as their exit flow field characteristics directly impact engine performance and stability. This study conducted numerical simulations on the first 3.5 stages of the NASA 74A transonic multi-stage axial compressor to analyze the exit flow field characteristics under different typical operating conditions. The research primarily investigated airflow deflection angle, radial velocity distribution, and their variation patterns. Additionally, the effects of inlet airflow angle and pressure variations on the exit flow field under non-uniform inlet conditions were examined in detail. The results indicate that at 68% rotational speed, the exit flow field of the NASA 74A compressor deteriorates significantly, with noticeable changes in distribution patterns. For the other four operating conditions, as the rotational speed decreases, both velocity and airflow angle exhibit a positive correlation with rotational speed. Compared to the design condition, peak velocity decreases by 2%, 3.7%, and 7%, while airflow deflection angle changes remain within 3°. Under non-uniform inlet conditions, when the inlet airflow angle decreases from 90° to 70°, variations in peak and average exit velocities remain within 2%, and the changes in peak and average airflow deflection angles are within 1%. However, when the inlet airflow angle decreases from 90° to 70°, the curve of the airflow deflection angle exhibits a leftward shift, with a deviation of 2.6%. Meanwhile, changes in inlet pressure under non-uniform conditions have a relatively minor impact on the overall flow field but significantly affect local distributions. When the inlet pressure increases from 1 atm to 1.05 atm, peak velocity increases by 0.98%, and average velocity rises by 3%. The maximum velocity difference reaches 6%, while the average airflow deflection angle differs by 0.7%, with a maximum deviation of 1.9°. Overall, the compressor exit flow field undergoes significant variations under different operating conditions, with increased flow instability at lower rotational speeds leading to flow separation, low-energy fluid accumulation, and non-uniform pressure distribution. In contrast, non-uniform inlet conditions have a relatively minor effect on the overall flow field but induce noticeable local changes, providing theoretical insights for compressor design optimization and performance evaluation. Full article

Aerodynamic shape design optimization faces challenges due to the computational demands and the vast design space, limiting its practicality and scalability. While progress has been made in subsonic and transonic regimes, the real-time optimization for supersonic conditions remains unexplored. To bridge this gap, this work exploits knowledge learned from subsonic and transonic real-world data and introduces a rapid optimization framework tailored for the supersonic regime. A novel end-to-end multitask Convolutional Neural Network is proposed to predict the aerodynamic coefficients of an airfoil shape, extracting global and local features directly from the geometry. The surrogate model is thoroughly examined and validated, including an analysis of model explainability. The surrogate model achieves on par results with the state-of-the-art, with relative errors in aerodynamic coefficient predictions below 1.7%. Furthermore, a surrogate-based optimization strategy integrates the surrogate model with a Generative Adversarial Network to generate realistic airfoil shapes, thereby reducing the design space to a low-dimensional representation. This approach provides a robust solution that accelerates the optimization routine by over 3000 times when compared to simulation-based methods while achieving a deviation of less than 1.9% from their optimum performance. Overall, this work strikes a balance between efficiency and effectiveness without compromising reliability. Full article

Dynamic stability derivatives are critical parameters in the design of trajectories and attitude control systems for flight vehicles, as they directly affect the divergence behavior of vibrations in an aircraft’s open-loop system when subjected to disturbances. This study focuses on the estimation of dynamic stability derivatives using a computational fluid dynamics (CFD)-based force oscillation method. A transient Reynolds-averaged Navier–Stokes solver is utilized to compute the time history of aerodynamic moments for an aircraft model oscillating about its center of gravity. The NASA Common Research Model serves as the reference geometry for this investigation, which explores the impact of pitching, rolling, and yawing oscillations on aerodynamic performance. Periodic oscillatory motions are imposed while using a dynamic mesh technique for CFD analysis. Preliminary steady-state simulations are conducted to validate the computational approach, ensuring the reliability and accuracy of the applied CFD model for transonic flow. The primary goal of this research is to confirm the efficacy of CFD in accurately predicting stability derivative values, underscoring its advantages over traditional wind tunnel experiments at high angles of attack. The study highlights the accuracy of CFD predictions and provides detailed insights into how different oscillations affect aerodynamic performance. This approach showcases the potential for significant cost and time savings in the estimation of dynamic stability derivatives. Full article

The steady-state aerodynamics and the aeroelastic response have been analyzed in an oscillating linear transonic cascade at the KTH Royal Institute of Technology. The investigated operating points ($\mathrm{\Pi }=1.29$ and $1.25$) represent an open-source virtual compressor (VINK) operating at a part speed line. At these conditions, a shock-induced separation mechanism is present on the suction side. In the cascade, the central blade vibrates in its first natural modeshape with a 0.69 reduced frequency, and the reference measurement span is 85%. The numerical results are computed from the commercial software Ansys CFX with an SST turbulence model, including a reattachment modification (RM). Steady-state results consist of a Laser-2-Focus anemometer (L2F), pressure taps, and flow visualization. Steady-state numerical results indicate good agreement with experimental data, including the reattachment line length, at both operating points, while discrepancies are observed at low-momentum regions within the passage. Experimental unsteady pressure coefficients at the oscillating blade display a fast amplitude decrease downstream, while numerical results overpredict the amplitude response. Numerical results indicate that, at the measurement plane, for both operating points, the harmonic amplitude is dominated by the shock location. At midspan, there is an interaction between the shock and the separation onset, where large pressure gradients are located. Experimental and numerical responses at blades adjacent to the oscillating blade are in good agreement at both operating points. Full article

The significant computational cost incurred due to the iterative nature of Computational Fluid Dynamics (CFD) in traditional aerodynamic shape design frameworks poses a major challenge, especially in the context of modern integrated design requirements and increasingly complex design conditions. To address the demands of modern design, we developed an efficient aerodynamic shape design framework based on our previous work involving the locally linear embedding plus constrained optimization genetic algorithm (LLE+COGA) high-fidelity reduced-order model (ROM). An active manifold (AM) auto-en/decoder was employed to address the dimensionality curse arising from an excessively large design space. The fast mesh deformation method was utilized for high-precision, rapid mesh deformation, significantly reducing the computational cost associated with transferring geometric deformations to CFD fine mesh. This work addressed the transonic optimization problem of the undeflected Common Research Model (uCRM) three-dimensional wing (with an aspect ratio of 9), involving 241 design variables. The results demonstrate that the optimized design achieved a significant reduction in the drag coefficient by 38.9% and 54.5% compared to the baseline in Case 1 and Case 2, respectively. Additionally, the total optimization time was shortened by 62.6% and 57.7% in the two cases. Moreover, the optimization outcomes aligned well with those obtained from the FOM-based framework, further validating the effectiveness and practical applicability of the proposed approach. Full article

The missions of modern aircraft require multiple abilities, such as highly efficient taking-off and landing, fast arrival, and long-endurance hovering. It is difficult to achieve all technical objectives using traditional aircraft design technology. The active flow control technology using the concept of a co-flow jet (CFJ) is a flow control method without a mass source that does not require air from the engine. It has strong flow control ability in low-speed flow, can greatly improve the stall angle of the aircraft, and can obtain large lift enhancement. At transonic conditions, it can lead to a larger lift–drag ratio with a small expense. CFJ technology has great application potential for aircraft due to its flexible control strategy and remarkable control effect. In this paper, the concept of a combination of CFJ and variable camber technology is proposed which realizes the change of airfoil camber to meet different task requirements with the movable droop head. By using the built-in ducted fan, air is blown and sucked in the jet channel so as to realize CFJ flow control. In a state of high-speed flight, complete geometric restoration is achieved by closing the channel and retracting the droop head. In this paper, the design and aerodynamic analysis of a CFJ device with variable camber based on a supercritical airfoil with small camber and a small leading-edge radius are carried out using the computational fluid dynamics (CFD) method. Comparative studies are conducted for different schemes on the taking off and landing performances, and discussions are had on core technical parameters such as power consumption. The results indicate that by utilizing the CFJ technology with more than 10 degrees of droop device, the maximum lift coefficient of a supercritical airfoil with a small camber and leading-edge radius, which is suitable for transonic flight, can be increased to a value larger than 4.0. Full article

Aviation accounts for a significant share of global CO₂ emissions, necessitating efficient propulsion technologies to achieve net-zero emissions by 2050. Geared turbofan architectures offer a promising solution by enabling higher bypass ratios and improved fuel efficiency. However, geared turbofans introduce significant aerodynamic and structural challenges, particularly in the low-pressure turbine. Current understanding of high-speed low-pressure turbine behavior under engine-representative conditions is limited, especially regarding unsteady wake interactions, secondary flows, and compressibility effects. To address these gaps, this work presents a novel test case of high-speed low-pressure turbines, the SPLEEN C1. The test case and experimental methodology are depicted. The study includes the commissioning and characterization of a transonic low-density linear cascade capable of testing quasi-3D flows. The rig’s operational stability, periodicity, and inlet flow characterization are assessed in terms of loss and turbulence quantities to ensure an accurate representation of engine conditions. These findings provide a validated experimental platform for studying complex flow interactions in high-speed low-pressure turbines, supporting future turbine design and efficiency advancements. Full article

This study proposes a design procedure for the multi-objective aeroelastic optimization of a tow-steered composite wing structure that operates at transonic speed. The aerodynamic influence coefficient matrix is generated using the doublet lattice method, with the steady-state component further refined through high-fidelity computational fluid dynamics (CFD) analysis to enhance accuracy in transonic conditions. Finite element analysis (FEA) is used to perform structural analysis. A multi-objective transonic aeroelastic optimization problem is formulated for the tow-steered composite wing structure, where the objective functions are designed for mass and critical speed, and the design constraints include structural and aeroelastic limits. A comparative analysis of eight state-of-the-art algorithms is conducted to evaluate their performance in solving this problem. Among them, the Multi-Objective Multi-Verse Optimization (MOMVO) algorithm stands out, demonstrating superior performance and achieving the best results in the aeroelastic optimization task. Full article

This study examines the aerodynamic performance of a joined-wing (JW) aircraft design based on the NASA Common Research Model (CRM), aiming to assess its potential for efficient commercial transport or cargo aircraft at transonic speed (Mach 0.85). The CRM wing, optimised for transonic flight, was transformed into a JW design featuring a high-aspect-ratio main wing. An initial parametric study using the vortex lattice minimum drag panel method identified viable designs. The selected JW configuration, comprising front and rear wings joined by a vertical fin, was analysed using ANSYS Fluent to understand flow interactions and aerodynamic performance. At an angle of attack (AoA) of −1°, the JW design achieved a peak lift-to-drag ratio (L/D) of 17.45, close to the CRM’s peak L/D of 19.64 at 2°, demonstrating competitive efficiency. The JW’s L/D exceeded the CRM’s between AoA −3° and 0.8°, but the CRM performed better above 0.8°, with differences decreasing at a higher AoA. Based on induced drag alone, the JW outperformed the CRM across AoA −3° to 8°, but flow complications restricted its L/D advantage to a small, low AoA range. A strong shock on the vertical fin’s inboard side due to high incoming flow speed delayed shock formation on the main wing near the joint. Optimising the vertical fin shape slightly improved L/D, suggesting potential for further enhancements or that other design factors significantly affect JW performance. This study provides insights into JW aerodynamics at transonic speeds, revealing its potential benefits and challenges compared to the CRM design. Full article