Acta Mechanica Sinica最新文献

The cavitation tunnel with controlled background pressure is a pivotal experimental setup for studying the mechanisms of cavitating flows and hydrodynamic loads on cavitating bodies. Existing recirculating cavitation tunnels predominantly feature horizontal test sections for modeling cavity flows in horizontal incoming flow and vertical gravitational acceleration and fail to meet the requirements for long-duration experiments on ventilated cavity flows. This paper introduces the unique gravity-driven vertical water tunnel (GVWT), facilitating hydrodynamic experiments on axisymmetric slender bodies with ventilated cavities in the streamwise gravitational acceleration. It elaborates high-throughput data processing method for synchronously measured high-speed camera images of cavity forms and pressure distribution from sensor arrays on model surfaces in unsteady long-duration ventilation conditions. For the ventilated cavity flow against an axisymmetric slender body with 60° cone headform at zero angle of attack, the developed partial cavity can be divided into four regimes: The sheet cavity, the combined sheet and cloud cavity, the entire cloud cavity, and the shedding cloud cavity. The mean cavity length and thickness are well-defined by the high-speed images. For the unsteady ventilated cavity due to the re-entrant jet, the Strouhal number based on cavity length and pulsation frequency of the cloud cavity equals 0.276. The mean pressure distribution in the ventilated cavity reveals a difference between the pressure within the sheet cavity and the maximum pressure in the cavity closure, which is influenced by the streamwise gravitational effect. The experimental results demonstrate that GVWT provides a novel experimental approach for understanding the physics of ventilated cavity evolution and bubbly flows under the effect of the streamwise gravitational acceleration.

This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters, aiming to reduce the computational costs and improve accuracy in determining bounds of system response. The screening method is firstly used to reduce the scale of active uncertain parameters. The sequential high-order polynomials surrogate models are then used to approximate the dynamic system’s response at each time step. To reduce the sampling cost of constructing surrogate model, the interaction effect among uncertain parameters is gradually added to the surrogate model by sequentially incorporating samples from a candidate set, which is composed of vertices and inner grid points. Finally, the points that may produce the bounds of the system response at each time step are searched using the surrogate models. The optimization algorithm is used to locate extreme points, which contribute to determining the inner points producing system response bounds. Additionally, all vertices are also checked using the surrogate models. A vehicle nonlinear dynamic model with 72 uncertain parameters is presented to demonstrate the accuracy and efficiency of the proposed uncertain computational method.

A comprehensive dynamic model for thermal buckling, elastic vibration and transient response analysis of rotating nano-composite porous metal-matrix microbeams reinforced with graphene nanoplatelets (GNPs) under a uniform thermal gradient is proposed. Various pore distribution patterns are considered together with different GNPs dispersion rules according to the specific functions. The extended rule of mixture and Halpin-Tsai micromechanics model are employed to evaluate the effective material properties of the nanocomposites. Based on the modified couple stress theory and the improved third-order shear deformation theory, the dynamic equations of the rotating microbeam are established by the Lagrange’s equation. The Chebyshev-based Galerkin method is adopted to discretize these equations, which are then solved by the complex modal analysis and Runge-Kutta-Merson method. Convergence study and comparisons with previous literature are conducted for validation of the present method. A parametric study performed analyzes the effects of angular velocity, thickness-to-length scale parameter ratio, porosity coefficient, weight fraction and geometry of GNPs together with distribution patterns of GNPs and pore on the critical buckling temperature rise, fundamental frequency and time-dependent response of the rotating nanocomposite microbeams. The results reveal significant effects of these parameters on the relevant mechanical behaviors, some of which are even contrary to expectations. Therefore, it is necessary to further study this kind of rotating nanocomposite structures for the optimal design.

Self-propulsion of a deformable ellipse immersed in an unbounded inviscid fluid is discussed in order to explore the effect of the deformation and controlled rotation of the body coupled with the shift of its internal mass on the self-motion. The ellipse is capable of symmetric deformation along the two orthogonal axes and endowed with some self-regulation ability via the shift and rotation of its internal mass. From the model, the appropriate velocity potential induced by the motion of the ellipse with the deformation in an otherwise undisturbed fluid is derived, and then the equations of motion are obtained by means of integrals of the unsteady fluid pressure. The equations are utilized to explore self-translational behaviors of the ellipse through the cyclic shift of its internal mass and deformation coupled with its own controllable rotation. Analysis and numerical results show that the ellipse can break the kinematic time-reversal symmetry by properly adjusting its own rotation to coordinate with the deformation and the cyclic shift of the inner mass to meet a forward criterion, and push itself to move persistently forward without a regression at zero system momentum, exhibiting some basic serpentine movements according as the ellipse performs complete revolutions or oscillates between two extreme yaw angles during its self-motion.

The demand for lightweight and multifunctional surface structure in high-end equipment is steadily growing. The harmonization between flexibility and electromagnetic tunability has become a significant subject for stealth morphing aircraft. This paper presents a microwave absorbing structure based on the kirigami configuration, aiming at improving the conformality with the negative Poisson’s ratio characteristic and expanding the radar stealth range with tunability. A precise electromagnetic reflectivity model of the impedance surface was established by the inversion method, and an integrated optimization algorithm was employed to optimize the structural parameters based on numerical analysis. Specimens composed of thermoplastic polyurethane elastic colloids and resistive materials were prepared to assess the in-plane mechanical tensile and electromagnetic absorption performances through experimental methods. The results indicate that the original absorption band spans 6.2–11.1 GHz, shifts to 8–18 GHz with stretching at a panel rotation angle of 16°, and remains nearly constant for further stretching. The specimens adhere to complex curved surfaces well in experiments and maintain the electromagnetic absorption performance compared with flat surfaces. This research offers a valuable reference for designing electromagnetic stealth structures that are highly stretchable and adjustable.

The dynamics of beams subjected to moving loads are of practical importance since the responses caused by these loads can be greater than those under equivalent static loads in some cases. In this work, a novel inertial nonlinear energy sink (NES) is applied for the first time to achieve vibration suppression in beams under moving loads. Based on the Timoshenko beam theory, the nonlinear motion equations of a beam with an inertial NES are derived using the energy method and Lagrange equations. The Newmark-β method combined with the Heaviside step function is adopted to calculate the responses of the beam under moving loads of constant amplitude and harmonic excitation. The accuracy of the modelling derivation and solution methodology are validated through comparisons with results from other studies. The results demonstrate that the velocity and excitation frequency of the moving load significantly affect the response of the beam as well as the performance of the inertial NES. To enhance its effectiveness under various moving load conditions, parametric optimization is numerically performed. The optimized inertial NES can achieve good performance by efficiently reducing the maximum deflection of the beam. The findings of this study contribute to advancing the understanding and application of NESs in mitigating structural vibrations caused by moving loads.

A lightweight composite resonator, consisting of a soft material acoustic black hole (SABH) and multiple vibration absorbers, is embedded in a plate to achieve localization and absorption of low-frequency vibration energy. The combination of local and global admissible functions for displacement enhances the accuracy of the Ritz method in predicting vibration localization characteristics within the SABH domain. Utilizing soft materials for the SABH can reduce the mass and frequency of the composite resonator. Due to the lack of orthogonality between global vibration modes and localized modes, the low-frequency localized modes induced by the SABH are used to shape the initial global modes, thereby concentrating the global vibration of the plate in the SABH region. Consequently, the absorbers of the composite resonator only need to be a small fraction of the mass of the local SABH to achieve substantial vibration control of the host plate. This vibration localization strategy can significantly reduce the vibration amplitude of the host plate and enhance the effectiveness of lightweight absorbers in vibration reduction.

This study numerically investigates inclined magneto-hydrodynamic natural convection in a porous cavity filled with nanofluid containing gyrotactic microorganisms. The governing equations are nondimensionalized and solved using the finite volume method. The simulations examine the impact of key parameters such as heat source length and position, Peclet number, porosity, and heat generation/absorption on flow patterns, temperature distribution, concentration profiles, and microorganism rotation. Results indicate that extending the heat source length enhances convective currents and heat transfer efficiency, while optimizing the heat source position reduces entropy generation. Higher Peclet numbers amplify convective currents and microorganism distribution complexity. Variations in porosity and heat generation/absorption significantly influence flow dynamics. Additionally, the artificial neural network model reliably predicts the mean Nusselt and Sherwood numbers ((overline{Nu}) & (overline{Sh})), demonstrating its effectiveness for such analyses. The simulation results reveal that increasing the heat source length significantly enhances heat transfer, as evidenced by a 15% increase in the mean Nusselt number.

High-speed flows have consistently presented significant challenges to experimental research due to their complex and unsteady characteristics. This study investigates the use of the megahertz-frequency particle image velocimetry (MHz-PIV) technique to enhance time resolution under high-speed flow conditions. In our experiments, five high-speed cameras were utilized in rapid succession to capture images of the same measurement area, achieving ultra-high time resolution particle image data. Through advanced image processing techniques, we corrected optical distortions and identified common areas among the captured images. The implementation of a sliding average algorithm, along with spectral analysis of the compressible turbulent flow field based on velocity data, facilitated a comprehensive analysis. The results confirm the capability of MHz-PIV for high-frequency sampling, significantly reducing reliance on individual camera performance. This approach offers a refined measurement method with superior spatiotemporal resolution for high-speed flow experiments.

This paper establishes a method for identifying and locating dynamic loads in time-varying systems. The proposed method linearizes time-varying parameters within small time units and uses the Wilson-θ inverse analysis method to solve modal loads of each order at each time step. It then uses an exhaustive method to determine the load position. Finally, it calculates the time history of the load. Simulation examples demonstrate how the number of measuring points and step size affect load identification accuracy, verifying that this algorithm achieves good identification accuracy for loads under resonance conditions. Additionally, it explores how noise affects load position and recognition accuracy, while providing a solution. Simulation examples and experimental results demonstrate that the proposed method can identify both the time history and position of loads simultaneously with high identification accuracy.