Acta Mechanica Sinica最新文献

Dielectric elastomer (DE) is an electroactive polymer with the characteristics of high energy output, great flexibility, light-weight, mechanical compliance, and low cost, which are particularly suitable for DE energy generators. Energy harvesting efficiency is a key index to evaluate the performance of the energy generator, which depends on the structural configuration and the mechanical and dielectric properties of the DE material. This paper proposes a fractional viscoelastic polarization (FVP) model by combining the fractional viscoelasticity model and the polarization-based lumped parameter model. A dynamical model of a cone dielectric energy generator (CDEG) considering stretch-dependent electrostriction and nonlinear viscoelasticity is established. Additionally, a deep neural network (DNN) model is developed to explore the relationships between various parameters and the output energy of CDEGs to efficiently and accurately predict the energy output of CDEGs. Based on the DNN model, optimal parameter designs for CDEGs are obtained by using non-dominated sorting genetic algorithm II (NSGA-II). The experiments verified that the FVP model predicts accurately the output energy of CDEG and the established optimal design framework can accurately provide the optimal design parameters of CDEG, which offers deep insights for the design and fabrication of a high-efficiency dielectric energy generator.

The time spectral approach, a spectral method based on the Fourier series with an appropriate convergence speed, can be utilized for a time-varying problem like the flow around a pitching airfoil. This approach has the drawback of having a constant number of time intervals over the entire computational domain, which unnecessarily uses up more computer memory and central processing unit (CPU) time. By distributing time intervals in the computational domain optimally (proportional to the flow gradient), the adaptive time spectral approach can overcome the shortcoming of the time spectral method. In the current study, the adaptive time spectral method is added to an inviscid fluid flow solver. Also, in the airfoil with pitching motion, a grid known as an overset grid has been used, including two grids with an overlapping region. The results for the three cases (Cases 1, 2, and 5) of the NACA0012 pitching airfoil with different angles of attack studied by AGARD Institute, with Mach numbers 0.6, 0.6, and 0.755, respectively, showed that while having an acceptable solution accuracy, the amount of computer memory and CPU time is significantly reduced compared to the standard time spectral method.

We present a numerical framework for simulating viscous compressible flows in the presence of solid particles with large size ratios. The volume-filtered Navier-Stokes equations are discretized using a class of high-order low-dissipative finite difference operators with energy-preserving properties. No-slip, adiabatic boundary conditions are enforced at the surface of large particles (with diameters significantly larger than the local grid spacing) using a ghost-point immersed boundary method. Two-way coupling between the gas phase and small particles (with diameters proportional to the grid spacing) is accounted for through volumetric source terms for interphase momentum and energy exchange. A simple and efficient approach for collision detection between small and large particles is proposed. The framework is applied to simulations of planar shocks interacting with bidisperse distributions of particles with size ratios of approximately thirty. Particle dispersion and size segregation are reported and a simple analytical model for size segregation is proposed.

The mechanical properties of biological soft tissues play a critical role in the study of biomechanics and the development of protective measures against human injury. Various testing techniques at different scales have been employed to characterize the mechanical behavior of soft tissues, which is essential for developing accurate tissue simulants and numerical models. This review comprehensively explores the mechanical properties of soft tissues, examining experimental methods, mechanical models, numerical simulations, and the progress in materials that mimic the mechanical performance of soft tissues. Finally, it reviews the damage and protection of human tissues under kinetic impacts, anticipating the future construction of soft tissue surrogate targets. The aim is to provide a systematic theoretical foundation and the latest advancements in the field, addressing the design, preparation, and quantitative modeling of biomimetic materials, thereby promoting the in-depth development of soft tissue mechanics and its applications.

This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation (DNS) of particle-laden flows. The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow. The Eulerian framework numerically resolves turbulent carrier flow using a parallelized, finite-volume DNS solver on a staggered Cartesian grid. Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking (LPT) algorithm. The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases. The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results. We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics. The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver. In addition, we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.

The seepage behavior of bone fluid is the main pathway of osteocyte metabolism, and the pore pressure, fluid velocity, and fluid shear stress generated by it are the main fluid flow stimuli perceived by mechanically sensitive osteocytes. However, the impact of intramedullary pressure (IMP) on the fluid behavior of interstitial fluid in bone remains unclear. The purpose of this study was to evaluate the effect of IMP on the fluid flow behavior in the Haversian canals and lacuno-canalicular network (LCN). This study established a multiscale finite element model of bone tissue based on the theory of poroelasticity, considering the interconnection of different pore scales such as bone marrow cavity, Haversian canals, and LCN. The effects of IMP frequency and amplitude on Haversian canal pore pressure (p_Hc) and flow velocity (v_Hc), as well as on LCN pore pressure (p_lc), flow velocity (v_lc), and fluid shear stress (τ), were analyzed. In this model, we assumed that IMP is a pulsating liquid pressure that is synchronized with arterial blood pressure and respiration, located within the bone marrow cavity and acting on the inner wall of bone tissue. We considered the stepwise conduction of pore pressure at different pore scales. As the initial pressure condition of the overall model, IMP was calculated to obtain p_Hc and v_Hc, while p_Hc was calculated as the initial pressure condition of the next scale model to obtain p_lc, v_lc, and τ. The results indicated that IMP had a significant impact on the fluid flow of bone. The p_Hc and p_lc significantly increased with the increase in IMP amplitude, and the frequency of IMP had a significant impact on the peak p_Hc over time. The multilevel pore model established in this study provides a more accurate analysis of the fluid flow behavior within bones, which is of great significance for a deeper understanding of bone internal force conduction and is crucial for a better understanding of bone adaptation based on IMP.

In engineering, a reasonable and efficient method to simplify the large-scale calculation of dynamic response of stiffened plates is highly desired. This paper proposes a novel equivalent-isotropic-plate model (EIPM) to convert a symmetrically stiffened plate to an isotropic flat plate within elasticity. EIPM provides concise and explicit formulas to calculate the equivalent plate thickness, which can save a lot of computational resources compared with direct simulation or solving complex differential equations. Under uniformly distributed impulse loading, EIPM performs excellently in predicting the maximum deflection response with an error of no more than 10%. The stiffened and the equivalent plates have similar vibration modes, but the former has a vibration frequency slightly higher than the latter by about 17% at maximum. After verification, EIPM is suitable for various complex stiffening forms with independence of materials and loads, and even qualified for large deformation problems. Due to its accuracy, efficiency, and applicability, the EIPM has potential applications in structural optimization and fast prediction of dynamic response.

This paper proposes a time-delayed quad-stable stochastic resonance (SR) model driven by Gaussian white correlated noises and a weak periodic signal. For the small time delay, the mean first-passage times and spectral amplification (SA) are derived. The curve of SA exhibits a typical resonant peak at an optimal noise intensity and SR happens. Moreover, as the time delay increases, the peak value of SA is enhanced for a fixed feedback gain. It is found that selecting appropriate cross-correlation between noises and feedback gain for fixed time delay can induce the appearance of SR. In particular, an ideal quad-stable potential structure is determined to optimize the SR effect. Subsequently, an adaptive improved quad-stable SR model based on quantum particle swarm optimization is proposed to determine the optimal structure parameters to maximize improved signal-to-noise ratio. Meanwhile, the proposed model is applied to diagnose weak bearing faults in inner race, outer race, and rolling elements. The results indicate that the time-delayed quad-stable SR model significantly enhances the fault diagnosis performance and resolves the issues related to side frequency interference compared to the underdamped bi-stable SR model and the underdamped quad-stable SR model. In the fault diagnosis of bearing rolling elements, the proposed SR model can accurately identify fault frequency values. While the underdamped bi-stable and quad-stable SR models are invalid for this case.

To guide clinical treatment and optimize blood pump design, a mathematical model was developed to evaluate thrombosis and stroke risks induced by blood pumps. Incorporating platelet receptor synthesis/shedding and von Willebrand factor (vWF) unfolding/degradation under shear stress, the model assessed hemorrhagic stroke risk based on shear stress-impaired platelet-vWF binding and thrombosis risk through shear stress-enhanced platelet-vWF interactions leading to hypercoagulability and blood stagnation. The model was validated using three blood pumps—HeartWare, HeartMate II, and HeartMate 3—showing consistency with clinical evidence. Thrombosis risk ranked as HeartMate II > HeartWare > HeartMate 3, primarily due to blood stagnation and shear stress-induced hypercoagulability. Hemorrhagic and ischemic stroke risks followed the ranking HeartWare > HeartMate II > HeartMate 3, with ischemic stroke regions overlapping shear stress and thrombosis-prone regions. Reducing narrow clearances and stagnation regions and avoiding regions of overlapping high shear stress and prolonged residence time can enhance hemocompatibility. The model accurately identified high-risk regions for thrombosis and stroke, providing insights for optimizing blood pump design and clinical strategies.

To investigate the characteristics of vented explosions in stoichiometric hydrogen/methane/air mixtures in the presence of obstacles, experiments were conducted within a cylindrical duct, taking into account the effects of hydrogen concentration, blockage ratio (BR), and the number of obstacles. The results indicate that internal and external peak overpressures generally increase with a higher hydrogen fraction. A higher propensity for transitioning from deflagration to detonation is observed under conditions of elevated hydrogen concentration and higher BRs. The rupture shock overpressure increases with the hydrogen fraction, peaking with five obstacles, and then decreases as the BR further increases. This pattern is also observed in the overpressure of external explosions and the maximum temperature of external flames. Given the impact of blast overpressure on human safety and structural integrity, the minimum safe distance required for equipment is notably greater than that for personnel. These results contribute to the safe and efficient use of hydrogen/methane blended gases.