International Journal of Mechanics and Materials in Design最新文献

Classical thermoelastic-diffusion theories are inadequate at micro- and nanoscales because they assume instantaneous local response of heat and mass fluxes, predict infinite propagation speeds, and completely neglect long-range microstructural interactions. This paper introduces the first thermodynamically consistent theoretical framework that simultaneously overcomes all three limitations: it extends the Lord–Shulman generalized theory by incorporating nonlocal heat conduction of Guyer–Krumhansl type with its own thermal length scale, a newly proposed nonlocal mass-diffusion law governed by an independent diffusive length scale, and separate phase-lag relaxation times for thermal and chemical-potential gradients. The model is analytically solved for an infinite isotropic solid containing a traction-free spherical cavity subjected to a pulsed thermal shock and an exponentially decaying chemical potential at the inner surface. Numerical results for copper reveal three striking physical effects that are entirely absent in all previous local and single-nonlocality models: temperature and concentration disturbances penetrate far deeper into the material while their spatial gradients become remarkably smoother; peak displacements and thermoelastic stresses are reduced by more than half; and the coupled thermo-elasto-diffusive waves experience significantly stronger attenuation throughout the medium. These distinctive size-dependent phenomena originate from long-range interactions among energy carriers and diffusing species. The proposed framework therefore enables accurate performance prediction and deliberate microstructural tailoring in modern nanoscale devices, offering substantially improved reliability for MEMS thermal actuators, faster hydrogen charging in metallic microspheres, safer laser-triggered drug-release nanocapsules, and reduced thermoelastic losses in high-frequency nanoresonators.

Micro machining technology has rapidly developed with the widespread application of miniature components. Chip morphology and burr size are critical indicators for assessing the surface topography in micro machining. However, the evaluation criteria established for macroscopic cutting conditions are no longer applicable in this context. To investigate the effects of cutting parameters on chip morphology and burr size under micro-machining conditions, a typical dual-phase titanium alloy is selected as the workpiece for the micro milling study. First, a physical micro milling experimental platform is established. Next, based on a single-factor experimental approach, the influence of cutting parameters on chip morphology and burr size is analyzed. Finally, top burrs height prediction model of the down and up milling is developed using the SSA-LSSVM algorithm. The results indicate that the cutting depth has a minimal effect on chip morphology. However, as the feed per tooth increases, fine crack-like features become more prominent along the edges of the chips. The cutting depth primarily affects the top burr size in down milling, while the feed per tooth has the least. The prediction accuracy of the SSA-LSSVM models for both the down and up milling reaches 90%, with the maximum prediction errors being 14.2 and 15.1%, respectively. This prediction model can effectively guide the complex nonlinear mapping relationship between cutting parameters and burr size. The research results provide theoretical and experimental basis for the analysis of chip morphology and burr size prediction in micro-milling of dual-phase alloys.

The engine power is transmitted to the tail rotor via the tail drive shaft system without redundancy. Characterized by complex structure, long shafts, and intricate vibration behaviors, excessive vibration-induced failure may lead to uncontrolled drivetrain dynamics, severely compromising flight safety. This study incorporates internal excitations of spiral bevel gears in intermediate and tail reducers. A 162-degree-of-freedom (DOF) dynamic model is established using hybrid finite element and lumped-mass modeling techniques, discretizing the system into shaft segment unit, gear unit, and bearing-casing unit. The nonlinear dynamics are solved through combined Newmark-β and conjugate gradient methods, yielding nodal shaft trajectories and vibration accelerations. Experimental validation on reducer test benches demonstrates a maximum 14.01% deviation between simulations and measurements, confirming model validity.

Graded cellular structures have attracted increasing attention for lightweight and multifunctional applications. However, most existing gradation definitions are qualitative, limiting systematic exploration of their potential in multifunctional design. This study proposes a function-based parametric strategy to tailor the mechanical and thermal performance of two-dimensional (2D) graded cellular structures. By parameterizing key geometric features of regularly patterned structures with mathematical functions, both the dimensionless elastic modulus (E*) and the dimensionless thermal conductivity (K*) can be effectively tuned at a fixed overall infill porosity (P). Comparative analyses highlight the critical roles of porosity and the gradation function form. At P = 40%, quadratic gradations expand the tunable performance range by up to 50% relative to linear gradations. Furthermore, quadratic-graded structures achieve up to 2.1-fold wider tunability in E* and 3.7-fold in K* compared with randomly patterned counterparts, which exhibit narrower, near-normal performance distributions. To address trade-offs in multifunctional design, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to optimize the gradation coefficients. The resulting Pareto fronts show an approximately linear trade-off between E* and K* under the same gradation strategy, revealing promising sub-regions for high-stiffness, low-thermal-conductivity designs. Overall, this work offers a computationally light, physically interpretable approach for the multifunctional design of graded cellular structures, with strong potential for applications in thermal protection, energy absorption, and architected metamaterials.

Magneto-electro-elastic (MEE) materials with integrated sensory and actuation functions have promising application potentials in the spacecraft and automotive engineering. The deformation of MEE structures in temperature varying environments leads to a thermo-magneto-electro-elastic coupled problem. However, most studies considered temperature changes as a thermal load. This unidirectional coupling misses thermal changes due to structural deformations. This study establishes a thermo-magneto-electro-elastic fully coupled finite element (FE) model for MEE plates based on the first-order shear deformation (FOSD) theory. The proposed eight-node Serendipity plate/shell elements for MEE structures incorporate five displacement DOFs per node, and one electric, one magnetic and one temperature DOF per element. The present FE model is first analyzed for mesh convergence. Subsequently, the static and dynamic responses of MEE plates under mechanical, electric, and magnetic loads are investigated. The numerical results, including displacements and temperature fields, are compared with COMSOL simulations. The comparative results indicate that the model has good accuracy in predicting the impact of structural deformations on the temperature field.

The propagation of Love-type waves in composite structures has significant implications for wave-based sensing, energy harvesting, and structural health monitoring. This study investigates the effect of an electric membrane and a classical spring on Love-type wave propagation at the common interface of a piezoelectric fiber-reinforced composite (PFRC) layer comprising a PZT-5A-epoxy combination and a piezoelectric substrate. Utilizing a mathematical model incorporating interface conditions, the wave dispersion characteristics are examined under different bonding scenarios, such as perfect, spring-type, membrane-type, and combined spring-membrane type interfaces. Numerical analysis is conducted to elucidate the influence of material properties, bonding parameters, and interface stiffness on phase velocity. The results show that the presence of a thin electric membrane and a classical spring significantly alters Love-type wave behavior, providing opportunities for optimizing wave control in smart materials and non-destructive evaluation systems. These findings contribute to the advancement of wave manipulation techniques in engineered composite structures and the design of surface acoustic wave (SAW) devices like Love wave sensor, which have gained traction in advanced defence systems due to their robustness, sensitivity, and passive operation.

This study aimed to enhance the tribological and corrosion-resistance properties of copper-tin (Cu–Sn) alloy substrates by developing multilayer diamond-like carbon (DLC) coatings with different modulation periods. Gradient transition layers (Cr and Cr-WC composite) were first deposited, followed by WC-DLC/DLC coatings with four modulation periods (1, 2, 3, and 4) on the Cu–Sn substrates. The microstructure, tribological behavior, and corrosion resistance of the coatings were systematically investigated. Results indicate that the modulation period significantly affects both tribological and corrosion properties. The coating with two modulation periods demonstrated the best performance, exhibiting high bonding strength and a low friction coefficient of 0.044. This tribological improvement is attributed to an optimized internal structure, which, despite a slightly lower sp³ content (38.8%), effectively resists wear and spalling. Additionally, its corrosion current density is only 9.16 × 10^–8 A/cm², two orders of magnitude lower than the other coatings, indicating superior corrosion resistance. These results suggest that DLC coatings with appropriately designed modulation periods develop a dense microstructure with minimal defects, which is a key factor in enhancing corrosion resistance.

This study presents a multi-channel design and optimization framework for active vibration control of ring shell structures using flexoelectric actuators. The novelty of this work is three-fold: (i) a coupled electromechanical dynamic model that captures both membrane and bending responses of a freely floating ring under localized flexoelectric actuation; (ii) a practical actuation mechanism based on AFM-probe–generated nonuniform electric fields to produce highly localized converse-flexoelectric driving forces; and (iii) a multi-objective Sequential Quadratic Programming (SQP) procedure that simultaneously optimizes actuator positions and drive voltages to minimize a physically motivated roundness function measuring deviation from circularity. Numerical case studies for a ring (radius 0.05 m, thickness 0.001 m; flexoelectric patch thickness 50 μm; AFM tip radius 50 nm; actuation voltages up to 10 V) demonstrate that the SQP routine robustly identifies actuator configurations that cancel overall vibration across multiple excited modes, yielding near-zero residual deformation where single-channel schemes fail. We further show that the optimal actuator distributions obey cyclotomic-polynomial symmetry and that control benefit saturates as the actuator count increases (computational cost also rises), indicating an effective practical range for actuator number. The approach offers a systematic route for precision deformation control in ring-shaped micro- and nano-devices and informs design choices for multi-actuator flexoelectric systems.

In this study, the free vibration behavior of a viscoelastic nanobeam resting in a nonlocal viscoelastic medium is analytically investigated using the Navier solution method. A modified Jeffreys-type viscoelastic model, consisting of one elastic and two viscous elements, is employed to more accurately represent the time-dependent and hereditary mechanical behavior of the beam material. The equations of motion are formulated by combining stress-driven model and, nonlocal elasticity theory for viscoelastic foundation. These are coupled with the modified Jeffreys model to derive a generalized differential equation that captures both stress-driven effects and nonlocal viscoelastic interactions within a unified analytical framework. Unlike conventional studies limited to classical viscoelastic formulations, this work introduces an enhanced viscoelastic model to describe viscoelastic nanobeam dynamics under the influence of a nonlocal viscoelastic foundation, providing a more realistic depiction of nanoscale structural behavior. The analytical closed-form solutions obtained allow a detailed investigation of how scale effects, viscous damping, and foundation parameters influence the dynamic response characteristics of viscoelastic nanobeams. This theoretical contribution highlights that the dynamic behavior of nanobeams is strongly governed by the coupled effects of nonlocal elasticity and advanced viscoelasticity, offering new insights into nanoscale material modeling and providing a valuable analytical benchmark for future nanomechanical system designs.

This study presents a comprehensive investigation into the dynamic stability analysis of laminated composite plates using meshless methods, particularly the Radial Point Interpolation Method (RPIM). Laminated composite plates are widely utilized in civil and aerospace engineering due to their exceptional properties, including high strength-to-weight ratios, lightweight nature, and tailorable anisotropic behavior. However, analyzing their dynamic stability poses significant challenges due to geometric nonlinearities and critical responses under time-varying loading conditions. In this research, RPIM is integrated with higher-order shear deformation theories, specifically the Third-Order Shear Deformation Theory (TSDT) and Classical Plate Theory (CPT), to model complex plate behaviors under diverse dynamic loadings, such as periodic, moving, and combined loads. The influence of critical parameters, including fiber orientation, number of layers, thickness-to-width ratio, boundary conditions, and elastic modulus ratio, on the primary dynamic instability region is thoroughly examined. The results demonstrate that the combination of RPIM and TSDT yields highly accurate predictions of natural frequencies and critical buckling loads, particularly for thick plates where shear deformation effects are pronounced. The primary innovation lies in a robust computational framework leveraging meshless methods for greater geometric flexibility and computational efficiency; benchmark tests show RPIM achieves ~ 20–30% faster computation than FEM for comparable accuracy. Increasing the length-to-thickness ratio and elastic modulus ratio shifts the dynamic instability region to higher excitation frequencies, enhancing structural stability. This work advances the understanding of nonlinear dynamic stability phenomena in laminated composites and offers a robust computational framework for future studies in structural mechanics.