Aerospace Science and Technology最新文献

This study proposes a passive bionic noise reduction strategy using serrated trailing edge (TE) designs to be applied to the aero-train's ground-effect wing. The aim is to mitigate TE noise by suppressing the tail vortex under high-speed and near-wall conditions. Three different serrated TE designs were numerically investigated via large eddy simulation, combined with Möhring acoustic analogy theory under Ma = 0.3 to reveal their noise reduction effects. The noise reduction mechanism was analyzed from the perspective of the flow characteristics in the TE boundary layer. The results indicate that all serrated TE designs achieve noise reduction, with the TE2 exhibiting superior performance. This outcome is linked to the ability of serrated TE designs to moderate boundary layer airflow separation and backpressure gradients, facilitating smoother transitions and lessening wake vortex intensity, thereby reducing turbulence-induced noise. Designs featuring wider serration gaps and sharper edges further enhance noise attenuation.

This work highlights the necessity of taking into account surface roughness when conducting experimental tests, and when using numerical simulations to precisely calculate the turbulent lift and drag of wind-tunnel models or real aircraft in transonic conditions. The present article is a continuation of “Turbulent drag induced by low surface roughness at transonic speeds: Experimental/numerical comparisons,” Physics of Fluids, Vol. 32, 045108 (2020) by Hue and Molton. The outcomes of this former study, which was focused on flat plate samples, are here applied to a three-dimensional aircraft configuration: the Common Research Model used as a reference in the recent international Drag Prediction Workshops. Experimental campaigns have been performed in the largest ONERA wind tunnels S1MA and S2MA involving models with average surface roughness heights Ra close to 0.5 micrometers, wingspans up to 3.5 meters, Mach and Reynolds numbers up to 0.95 and 5 million respectively. Reynolds-averaged Navier–Stokes computations based on the wind-tunnel tests have then been carried out, using the equivalent sand-grain roughness height approach as well as a Musker-type correlation to determine relevant k_s values. The results of both the experimental and numerical campaigns have demonstrated that the aerodynamic coefficients of the aircraft can be significantly affected by the surface roughness, even with roughness Reynolds numbers k_s⁺ potentially below the usual threshold values sometimes considered in engineering applications (i.e. in the order of 3.5 to 5). In particular, the surface roughness effects on lift and drag have been studied using far-field analyses to evaluate the responses of friction, viscous pressure, wave and lift-induced drag components. Finally, the numerical studies have been extended to the full-scale geometry in flight conditions in order to assess the roughness effects and potential gains in realistic aircraft operating conditions.

The throughflow analysis is indispensable for designers in the early stage of gas turbine engine development. However, only a little attention is paid to the combustion chamber in previous relevant researches. The dilution hole in the slinger combustion chamber hasn't been studied with an intact geometry considered. In this paper, a throughflow methodology of the slinger combustion chamber based on the circumferential average method (CAM) is established. The parallel grid method is proposed to simulate the flow both in the dilution hole and between two neighboring dilution holes. For the same region of the meridional plane relevant to the dilution hole, two separate sets of grids are involved to simulate both flow structures and the flow combination occurs at the indicative position of the dilution hole outlet. The velocity acceleration process in these two positions can be grasped more exactly. The spanwise distribution tendency of the Mach number and the density flow at the flame tube outlet is similar to the Fluent results. They are higher in the middle and lower at both ends, which is consistent with the correct physical knowledge. The residual of this combustor simulation can arrive at nearly 10⁻⁴ and it costs only 20 min to get convergent. The convergent feature of the mass flow is improved drastically compared with results from the Nigmatullin method in CIAM. The relative fluctuation range of the inlet mass flow is decreased from 1.5 % to 0.008 % and the outlet mass flow is reduced from 4.2 % to 0.005 %.

The acceleration schedule is crucial for generating acceleration control references for the gas turbine engine (GTE) and ensuring optimal acceleration performance. However, under harsh operating conditions, GTEs may encounter difficult-to-diagnose pressure sensor faults, which lead to inaccurate control references and decreased acceleration performance. This paper proposes a data-driven robust acceleration schedule (RAS) design method to tackle this issue, including fault data augmentation and adaptive sample class weighting (ASCW). Fault data augmentation generates multiple pressure fault sample classes from a normal acceleration schedule dataset. Due to the redundant pressure sensor configuration, the RAS can reconstruct these classes and generate accurate control references when a single pressure sensor fails. The ASCW employs a multilayer perceptron network to reconstruct the normal and fault sample classes accurately. Proportional integral regulation adjusts their weights during training to ensure balanced reconstruction precision. Simulation cases were conducted to verify the effectiveness of the RAS under actual GTE conditions, including engine-model mismatches, performance deterioration, flight envelope, and measurement uncertainty. The results demonstrate that the RAS ensures superior acceleration performance of GTEs across the full flight envelope in both normal and single pressure sensor fault scenarios. Additionally, the ASCW achieves reconstruction precision of 0.068 %, 0.080 %, 0.080 %, 0.082 %, and 0.077 % for normal and fault sample classes, respectively, prioritizing the precision of the normal sample class and balancing the precision of fault sample classes.

The current work examines the thermal postbuckling, aero-elastic flutter and thermally induced postbuckled flutter about a static equilibrium state of tri-directional functionally graded (TFGM) rectangular and tapered plates in yawed supersonic flow. Based on the von Kármán nonlinear strains, the general higher-order shear deformation theory (GHSDT) and the first-order piston theory, the governing equations of motion for TFGM plates in yawed supersonic flow are established via the Hamilton's principle. The isogemetric analysis (IGA), the load continue strategy associated with the Newton Raphson iterative technique are exploited synthetically to capture the postbuckling paths, and then the postbuckled flutter behaviors are acquired with the static equilibrium state being obtained. Comparative and convergence studies are provided to improve reliabilities of the present material model, formulae and code implementations. Subsequently, detailed parametric investigations are carried out to evaluate the influences of material volume fractions, boundary conditions and airflow angles on the thermal postbuckling, aero-elastic flutter and postbuckled flutter behaviors of TFGM plates. The results show that it is the in-plane volume fractions, rather than the thickness volume fraction, that exert a greater influence on the thermal postbuckling and flutter behaviors of TFGM plates. Furthermore, TFGM plates exhibit more diverse postbuckling paths and more complex deformations due to the inhomogeneity of the in-plane material properties compared with z-directional FGM plates.

Accurate identification and estimation of external forces on launch vehicles, aircraft, and other in-service engineering structures plays a vital role in structural design and health monitoring. Considering structural modeling errors, this paper develops a novel force identification method based on modal expansion and relevant vector regression (RVR). Initially, the incomplete and noisy experimental modal data are used to modify the stiffness and mass matrices of the finite element (FE) model, reducing the impact of modeling errors on force identification accuracy. Subsequently, to account for noise disturbances and potential information about unknown initial conditions in the measured acceleration responses, the external forces and the unknown initial conditions are respectively expanded using trigonometric functions and the mode shapes based on the function fitting technique. On this basis, the force identification equation is established for the updated model. The RVR algorithm is integrated into modal expansion and force identification. Firstly, the mode shapes of the FE model are utilized to expand the incomplete and noisy experimental mode shapes to their full degree of freedom, significantly enhancing the accuracy of the model updating. Secondly, by combining the measured acceleration responses, the base coefficients can be solved sparsely, effectively identifying the dynamic forces even when unknown initial conditions are present.

This study investigates the effects of injector spacing and momentum flux ratio on combustion instability in a model chamber with single and two injectors, both experimentally and numerically. For the experiments, injectors similar to those used in actual rocket engines were installed in a laboratory-constructed model chamber. Numerical simulations were conducted using ANSYS Fluent, employing a detailed combustion model to complement the experimental data. Flow conditions were categorized as fuel-lean and fuel-rich based on the fuel mass flow rate. The injector spacing varied from 15 to 45 mm, and the momentum flux ratio was adjusted from 6.4 to 139.8 by manipulating the fuel and oxidizer flow rates. Both experimental and numerical results consistently revealed distinct trends in combustion instability for lean and rich conditions, influenced by injector spacing and momentum flux ratio. Combustion stabilization was consistently more effective under fuel-rich conditions. Increasing the momentum flux ratio intensified combustion instability regardless of the fuel condition. For fuel-lean conditions, a rapid transition in combustion stability was observed, with the specific transition point varying depending on the injector spacing. Considering the trade-off between instability and injector number density, a spacing of 30 mm between injectors is recommended. Additionally, for both single and two injectors with various spacings under both lean and rich conditions, combustion stability was generally better when the momentum flux ratio was less than 48.8. These findings provide valuable insights into the control and management of combustion instability, aiding in the design of rocket engine combustors.

The actual rotor motion and seal dynamics are nonlinear and uncertain. The uncertain effects include the seal flow and the rotor system parameters. While the influence of system parameters makes it more difficult to accurately predict the seal dynamics. A rotor nonlinear whirling model was established to achieve the synchronous solution of rotor motion and seal simulation. The coupling effect between rotor system parameters and seal aerodynamic performance was adopted. The actual seal dynamics for SCO₂ turbine were obtained and evaluated by the numerical finite difference method. In the rotor nonlinear whirling model, the rotor has the uncertain continuous free motion. The influence of the system main parameters, such as elastic recovery stiffness and unbalanced mass force, on seal dynamics is revealed. And the dynamic coefficients beyond the artificial specific disturbance frequency are shown. The results show that the rotor nonlinear whirling can better predict the seal dynamics. The rotation speed, elastic recovery stiffness and unbalanced mass eccentricity have different significant effects on seal dynamics.

Unmanned aerial vehicle (UAV) inlets commonly have a compact S-shaped inlet structure for the sake of stealth. Most of the current studies on subsonic inlets have focused on S-shaped configurations with relatively gentle transitions of the flow channel. In this study, the aerodynamic performance and swirl flow characteristics of a UAV inlet, which has double 90° bends in the duct and is integrated with an aircraft fuselage and a volute, are studied both experimentally and numerically. The influences of angle of attack, sideslip angle, AIP (Aerodynamic Interface Plane) Mach number, and freestream airspeed are analyzed. A measure of adding two deflectors in front of the first bend and a baffle at the bottom of the volute is proposed to improve the total pressure distortion and swirl distortion characteristics of the inlet. Finally, a practice of shape optimization is performed to further improve the aerodynamic performance and swirl flow characteristics on the basis of the baseline configuration. The results indicate that the maximum and minimum total pressure recovery coefficients of the baseline inlet configuration are 0.982 and 0.969, respectively, as well as the maximum total pressure distortion index of –0.0814 and the maximum swirl distortion index of 32.1 % under normal operating conditions. Through a total of 8 iterations of optimization, the total pressure recovery coefficient is eventually improved by 0.21 % of that of the baseline configuration, as well as the total pressure distortion index, swirl distortion index and maximum swirl angle reduced by 43.6 %, 4.6 % and 11.1 %, respectively.

Possibility-based design optimization (PBDO) can provide theoretical basis for the structural optimal design of fuzzy uncertainty model in engineering, so as to obtain the optimal design variables. The genetic algorithm (GA) based on adaptive Kriging method for PBDO requires high precision in the whole design space, while the region far from the limit state surface (LSS) of the constraint function has little effect on PBDO, thus greatly affects the computational efficiency. In order to improve the efficiency of PBDO, an improved adaptive Kriging method combined with active possibility constraint (I-AK-AC) is proposed in this paper. In I-AK-AC, the enhanced expected improvement learning function is first put forward to promote the convergence efficiency of Kriging model by reducing the accuracy of the region far from the LSS of the constraint function. Whereafter, the active possibility constraint is identified, and only the boundaries of active possibility constraint need to be approximated precisely by Kriging model. By these ways, the convergence speed of Kriging model is further ameliorated without affecting the computational accuracy, and the efficiency of PBDO is significantly improved. Three test examples and an engineering application of aeroengine turbine disk illustrate the validity and accuracy of the proposed I-AK-AC.