Journal of Aerospace Engineering

This study proposes a multiscale numerical modeling procedure to evaluate the elastic properties of two-dimensional (2D) eight-harness satin woven carbon/carbon (C/C) composites. The multiscale modeling technique consists of analysis at the microlevel and mesolevel. In microscale analysis, a 3D representative volume element (RVE) of C/C composite with carbon fiber, pyrolytic carbon, and pores is considered. The microstructure of the C/C composite is analyzed using scanning electron microscope (SEM) images. Statistical characterization of pore distribution inside the C/C composite is performed, and different probability density functions are generated for pores’ number, area, and aspect ratio inside the C/C composite. Carbon fibers and pores are inserted in the 3D RVE using the RSA algorithm. The size and shape of the pores inserted in 3D RVE are based on the probability density functions generated. Effective elastic properties of C/C composite at the microscale are computed by finite element analysis (FE) based homogenization and taken as input for the next level of homogenization. The RVE at mesoscale is modeled using the information from SEM images, and FE-based homogenization is performed to compute the effective elastic properties of 8HS woven C/C composite. The effective elastic properties obtained from the numerical study are validated with the results of the uniaxial tensile test performed on 2D C/C composite. The effect of fiber volume fraction, yarn volume fraction, and porosity on elastic properties of 2D 8HS woven C/C composite are also assessed and presented in this study.

Abstract

In order to meet the demanding drag reduction requirements of high-speed aircraft, the drag reduction mechanism of array microslit-opposed jets in the passivation leading edge is studied using a numerical method based on the shear stress transfer (SST) $\mathrm{k}\text{-}\omega$ two-path turbulence model. The computations are performed with the commercial CFD solver FLUENT 13.0 code. The interference characteristics of the array jets are analyzed, the influence laws of the microslit array mode and the angle of attack on drag reduction performance are explored, and a prediction method of passivation leading edge drag characteristics based on radial basis function (RBF) neural network is constructed. The research conditions are as follows: the incoming Mach number is 2.0, the angle of attack ranges from 0° to 30°, and the number of microslits is 0 to 5. The results show that when there is interference between microslit jets, the interaction between adjacent reverse reflux regions will change the shape of the reflux regions. When there is a microslit jet in the center line, the position of the detached shock wave is more affected by the angle of attack. The drag characteristics of the leading edge are determined by the location of the detached shock wave and the characteristics of the reflux regions. The mode of microslits determines the drag reduction efficiency and sensitivity to the angle of attack. There may be contradictions in the design of array microslit-opposed jet schemes regarding the overall drag reduction efficiency, local load, and drag reduction stability. The drag prediction model based on the RBF neural network has an accuracy of 5%, which can provide support for the design of array microslit-opposed jets.

Practical Applications

The array microslit-opposed jets provide a new technical approach for reducing drag on the passivation leading edge. The paper studies its flow characteristics and laws and provides relevant conclusions. It can serve as a theoretical reference during design. The number of microslits is not the more the better. When designing microslit patterns, many factors need to be considered.

Abstract

Rolling element bearings are widely used in aero engines, high-speed trains, precision machine tools, and other technical fields due to their high rotational accuracy and strong carrying capacity. With the development of rotating machinery in the direction of high speed, the working conditions of rolling element bearings are becoming more and more harsh, resulting in thermal problems that will seriously affect the mechanical properties of the bearing and the stability of the rotor system. In this paper, the four-degrees-of-freedom quasi-static model of cylindrical roller bearings was established based on the elastohydrodynamic lubrication theory combined with slicing technology. The local thermal approach and the thermal resistance network method were adopted to calculate the frictional heat generation and the transient temperature field of bearings. So the thermal-mechanical coupling model was obtained considering the correction of the thermal effect. On this basis, the influences of temperature on the vibration of the bearing-rotor system were researched. Finally, the temperature and stiffness of the bearings under various operating conditions were discussed. The coupling theory of thermal characteristics and mechanical properties of such bearing-rotor systems was improved.

Practical Applications

Cylindrical roller bearings generally play a supporting role in rotating machinery and are widely used on high-speed occasions. For example, aero engines work under high-speed conditions, and high speeds in mechanical systems often bring serious thermal problems. As one of the core components, the spindle bearing must be able to overcome such a complex working environment. In this paper, cylindrical roller bearings and bearing-rotor systems are mathematically modeled for this feature in order to study their thermal and dynamic characteristics. The conclusions of this paper can provide relevant references for the design theory of this type of bearings applied in the fields of aero engines, high-speed precision machine tools, high-speed trains, etc., as well as theoretical guidance for the evaluation of their actual service performance.

Abstract

In this paper, a new model predictive control termed as intelligent model predictive control (IMPC) combined with an improved new competitive swarm optimizer (CSO) is designed. The analytical predictive model is not necessarily established a priori in the proposed IMPC algorithm, and the control plant can be used directly as the predictive model to reduce the complexity of the algorithm. In addition, two new techniques, dynamic initialization and back steps methods, are proposed and utilized to improve the traditional CSO to realize constraints management during the optimization process. An application to aeroengine transient-state control is studied to verify the effectiveness of the presented IMPC algorithm. It is shown that, benefitting from the IMPC algorithm, the control task is well completed and all the constraints are satisfied.

Practical Applications

This paper proposes a new optimization algorithm to solve some complex optimization problems with constraints. The designed new optimization algorithm is simple and easy to implement and it is more suitable for applications with black-box models or complex optimization objective functions compared with some existing optimization algorithms. This paper may provide some help to researchers who are interested in model predictive control or metaheuristic algorithms and to people whose work contains some complex optimization problems. This paper also provides a design method of aeroengine transient-state control plans. The simulation results showed that compared with some existing control methods or optimization algorithms, the aeroengine could accelerate to the desired steady-state point with shorter transient time and all constraints are satisfied when utilizing the proposed new optimization algorithm.

Abstract

Carbon nanotubes (CNTs) are added to the matrix according to proper distribution configurations by many researchers to improve the stiffness of laminated composites. However, the distribution configurations of CNTs may induce dramatic changes in displacements and stresses, which significantly affect structural safety. Moreover, such issues have received little attention at present because existing theoretical models encounter difficulties in accurately predicting dramatic changes in stresses of these structures. To accurately analyze the thermal expansion behaviors of laminated panels reinforced by CNTs, an equivalent single-layer higher-order model is proposed in which in-plane displacements are constructed by superimposing the second local displacements onto a smooth cubic varying field. Transverse normal deformation should be considered for the thermal expansion behavior of the laminated plate; therefore, a smooth cubic distribution along the thickness is adopted in the transverse displacement field. The layer-dependent displacement parameters can be expressed using global displacement variables by applying compatible conditions of displacements and stresses. Based on the proposed model, analytical solutions for laminated composites are obtained using Navier’s technique. The capability of the proposed model is verified by comparing the results of the proposed model with the exact solutions and the three-dimensional finite element model. The effect of the distribution configuration and volume fraction of CNTs on the thermomechanical behavior of the composite panels is studied based on the present model. Numerical results show that the distribution configuration and volume fraction of the CNTs significantly influence the distributions and magnitudes of stresses.

Practical Applications

In order to improve the stiffness of aircraft wings, stiffeners are typically used to enforce the skin of the wing. However, the aerodynamic shape of the wing cannot be changed, so that the stiffeners cannot be placed on external surface of the skin. As a result, the panel’s bending stiffness relative to the midplane is not asymmetric, which affected its loading capability. To overcome such problems, previous studies have demonstrated that adding CNTs can improve the stiffness of panels, and it has been found that composite panels reinforced with X-X-distributing CNTs possess the best capability in preventing buckling deformation. However, the effect of the distribution profiles of CNTs on the thermomechanical behavior has been less studied in the existing literature. Therefore, this study proposes a higher-order model to accurately predict the thermomechanical behavior of CNT-reinforced composite panels and investigate the effect of CNT distribution profiles and volume fractions on the thermomechanical responses of composite panels. The present work can provide suggestions for the design of a reinforcing scheme for CNT-reinforced composite panels, so that the stiffness of wings can be enhanced.

This paper proposes a trajectory-optimization problem for spacecraft close proximity to a noncooperative target, aiming at the generation of a six-degree-of-freedom (DOF) trajectory with the fuel-optimal objective value and considering multiple constraints on the control magnitude, line-of-sight, and glide-slope. The line-of-sight and glide-slope constraints are coupled between translational and rotational motions. The dual quaternion is an effective method for establishing the translationally and rotationally coupled model, because it can represent the translation and rotation in an integrated manner. Therefore, in this study, the trajectory-optimization problem of spacecraft close proximity coupled with position and attitude is established using dual quaternions. Next, the close-proximity trajectory-optimization problem is converted into a nonlinear programming problem, which can be solved efficiently using well-developed algorithms such as convex optimization. However, the zero-order hold used in the discrete method of convex optimization is an equidistant dispersion, which cannot guarantee the satisfaction of constraints between discrete points. Therefore the pseudospectral convex method is proposed using nonequidistant collocation points to mitigate the problem of constraint violation between discrete points and improve the accuracy and computational efficiency of the algorithm. The proposed algorithm can be applied to tasks such as rendezvous and docking with noncooperative targets and close proximity. Finally, the effectiveness of the proposed method was validated via numerical simulation, and the results were compared with those of the existing approach, GPOPS. The results indicate that the proposed algorithm is superior to GPOPS in computational efficiency and objective values.

Vibration causes compressor rotor blade failure that affects aeroengine safety. Therefore, a plane cascade model of rotor blades was developed to capture the vibration phenomenon. The blade vibration, vortex shedding, and aerodynamic noise were measured. The results indicate that flow and noise induce a natural vibration mode, resulting in torsional vibration fatigue damage. The frequency of trailing edge vortex shedding is consistent with the frequency of tip clearance leakage vortex pulsation and is close to the second-order modal frequency of the blade, which induces torsional vibrations. The triple frequency of the background noise peak frequency in the wind tunnel is consistent with the first standing wave acoustic resonance modal frequency of the cascade experimental section duct and is close to the third-order natural modal frequency of the blade, which induces bending and torsional vibrations. This research provides guidance for the study of rotor blade multifield coupling-induced vibration.

In order to study the combustion instability of solid rocket motors, the vibration-acoustic vibration-burning rate oscillation-thrust oscillation coupling system of solid rocket motors is analyzed. In this paper, a numerical model covering the pressure oscillation, combustion, pseudo-one-dimensional fluid field, and overall thrust is built. We investigate the thrust oscillation caused by projectile structure vibration and the response characteristics of thrust oscillation. By conducting a sine sweep test, we obtain the response function of thrust in relation to pressure oscillation. A physical experiment shows that the calculated frequency response function is consistent with the experimental results.

Aiming at raising the efficiency of multidisciplinary optimization of UAV rotor aerodynamics and aeroacoustics, this paper established a low-order method of rotor aerodynamics and noise prediction based on lifting line theory (LLT) and FWH acoustic analogy theory. The maximum errors between the low-order method and the high-fidelity CFD results are 1.53% and 3.3 dB for the thrust and overall sound pressure level (OASPL) respectively, demonstrating the ability of design optimization by the low-order LLT method. Combined with the proper orthogonal decomposition (POD) dimension reduction technique to reduce the variable space, a multidisciplinary optimization of rotor aerodynamics and noise was implemented. The rotor thrust and OASPL were taken as the optimization objectives, and the chord length, thickness, and blade twist angle at different spanwise positions were taken as the design variables. The results show that the proposed optimization strategy effectively reduces the design space, the convergence process is greatly accelerated by coupling the low-order LLT-FWH prediction method, and the whole optimization process is only about 0.094% of the computational resource of the method based on unsteady CFD and conventional optimization method. Compared with the original rotor, the thrust at the design condition is increased by 1.66%, and the OASPL is maximally reduced by 3.10 dB. After optimization, the aerodynamic load fluctuation in the middle of the rotor blade (40%–80% spanwise) is significantly reduced, and the high vorticity area in the wake is reduced from the middle to the blade tip (45%–100% spanwise).

Abstract

The trajectory optimization of multiple quadcopters for Mars exploration has been a challenging task due to a difficult nonconvex space formed by multiple quadcopters in the flight, the complex dynamics model, and complicated obstacle environments. We propose a distributed optimization algorithm (DiPenOpt) using direct collocation methods to solve the optimization in the nonconvex space. The DiPenOpt algorithm contains a penalty function method to transfer the nonconvex space into a convex one and an iterative optimization strategy employing initial value selection methods to enhance the algorithm’s convergence rate. We design a position-tracking controller to ensure that the quadcopters can effectively follow trajectories generated by the DiPenOpt, regardless of initial position deviations and uncertainties. We compare the results of the DiPenOpt with other algorithms and find that DiPenOpt has a faster solution speed and shows superior robustness for trajectory optimization of multiple quadcopters in large and complex environments. The simulation results show that the position-tracking controller can ensure error convergence and stabilize the flight path when the quadcopter has an initial error.

Practical Applications

When exploring Mars with multiple quadcopters, ensuring they move efficiently and safely is critical. Think of it like trying to coordinate several quadcopters in a maze-like environment, where every quadcopter needs its own clear path. Our research introduces a new way (DiPenOpt) to help these quadcopters find their best paths, even in complicated surroundings. Our method makes challenging path-finding problems simpler, and we have added tools to make sure quadcopters stick to their paths, even if they start off a little off-course or have uncertain disturbances. Compared to other methods, DiPenOpt is faster and better suited for situations where there are many quadcopters and obstacles. In simple terms, if we were to send a team of quadcopters to explore Mars, our method would make it easier for them to navigate and provide more reliable results, which is crucial for successful space missions.

The phenomenon of multiple tones is a typical feature of high-lift configuration noise, and the underlying nonlinear and nonstationary features need to be revealed through time-frequency analysis. This paper introduces the Hilbert–Huang transform method to detect the inherent amplitude modulation and frequency modulation phenomena of multiple tones from 30P30N three-element high-lift configuration with both slat and flap completely stowed. The acoustic modes are extracted from the multiple tones firstly and then the variation features of amplitude and instantaneous frequency are analyzed. The results show that the acoustic energy concentrates on the primary mode with much larger amplitude. Moreover, both the amplitude and instantaneous frequency are periodically varied in time and the predicted modulation frequencies are equal to the frequency intervals between nearby tones, confirming that the inherent temporal features of multiple tones are amplitude modulation and frequency modulation.

Piezoelectric materials can develop mechanical strain upon applying electric voltage and vice-versa. A piezoelectric bimorph, widely used in various sensors and actuator applications, essentially behaves like a beam and consists of a nonpiezoelectric material substrate layer glued between two piezoelectric layers. The application of an electric field alone can induce the bending of such a beam. Studies on the modeling of the piezoelectric bimorph are mostly restricted to the small deflection regime. In the present work, a simple numerical method is proposed to obtain the large deflection response of any piezoelectric bimorph. To begin with, the governing equation of a cantilever bimorph under electric field and end load is obtained. The nonlinear governing equation is then linearized with respect to the current time step. Subsequently, the linearized equation is solved using the RK4 method. From the numerical results, it is found that the response of the key design parameter, namely free displacement is considerably different from that predicted from small deflection analysis. Also, as the entities involved are suitably nondimensionalized, the results are directly relatable to all classes of piezoelectric materials. The nondimensionalization has also paved the way for better insight into the physical problem by rendering a simple mathematical representation.

A new structure with negative stiffness and negative Poisson’s ratio was designed to exhibit these characteristics during compression, energy absorption, and energy storage. The structure also shows improved impact resistance under extreme conditions due to transverse contraction during impact compression. These characteristics make the structure very suitable for use in spacecraft landing systems. A finite-element model using the improved Auricchio constitutive model was established, and compression tests were conducted on the new structure. The test results are in agreement with the simulation, validating the finite-element model. Comparing the new structure with traditional structures with negative Poisson’s ratio, the new structure demonstrated significantly better energy absorption and experienced minimal deformation during the compression-pull process. In addition, the finite-element model was used to analyze the influence of cell structural parameters. Further analysis showed that cell width and wall thickness of a curved beam are critical parameters influencing the structure’s overall energy-absorption performance, which should be emphasized in the design of landing energy-absorption devices with the new structure.

In the approach of metric-based geometric parameterization, the concept of database filtration and proper orthogonal decomposition manipulation quantitatively enhances the generation of new geometric parameters so that the problem-oriented information is reflected in aerodynamic design. Compared with the conventional approach that applies only geometric filtration, this paper incorporates performance filtration so that the problem-oriented information is no longer limited to geometric constraints, thereby enabling the guidance of optimization direction in a more informed manner. This paper focuses on the pressure distribution of samples and their relationship with geometric variations. A variational autoencoder is employed to extract the dominant features of the aerodynamic potentials that an initial geometry can attain in optimization. The authors believe that the aerodynamic potential is reflected in how the pressure distribution differs from that of the initial geometry. Then, samples have to meet the performance filtration criterion based on pressure distribution proposed by designers according to their aerodynamic understanding of the optimization problem. Finally, the remaining collection of qualified samples generates new geometric parameters via proper orthogonal decomposition. The conventional and new approaches were validated in a two-dimensional airfoil case of drag coefficient optimization; the lift-to-drag ratio improved by 17.07% using the traditional method, and by 38.20% using the new approach. The pressure distribution shows that the performance filtration approach produces more supercritical properties than the geometric filtration approach. This implies that the performance filtration approach can capture more intricate details related to the aerodynamic performance of the airfoil.