Archive of Applied Mechanics最新文献

Ti6Al4V alloy is widely used in aerospace, marine, and chemical industries due to its excellent specific strength and good biocompatibility. Understanding the damage and fracture mechanism of Ti6Al4V is crucial for the practical applications. In this work, the deformation and failure behaviors of Ti6Al4V were studied by digital image correlation method. Post-fracture surface analysis was performed to investigate the influence of stress triaxiality on failure behavior. A machine learning-based identification strategy was proposed to determine the strain hardening and Johnson–Cook damage model parameters. The datasets were obtained by finite element simulations for training the artificial neural network (ANN) models, which were utilized to establish the relation between the mechanical response and model parameters. The effect of ANN structure hyperparameters on prediction performance was discussed and whale optimization algorithm (WOA) could improve the prediction accuracy of neural network model. The results indicated that the WOA algorithm optimized three-layer BP neural network with 16 hidden neurons and activation functions of tansig + tansig can be used to effectively identify the plastic and damage model parameters of Ti6Al4V alloy.

This study models and analyzes the thermomechanical vibration behavior of biocompatible sandwich plates under compressive forces, thermal fields, and magnetic fields, employing high-order plate theory. The sandwich plate is composed of a solid and foam structured ZK60 magnesium alloy reinforced with graphene in the core layer, with surface layers consisting of functionally graded ZK60 ceramic material in the inner sections and zirconia ceramic material in the outer sections. The results indicate that the metal foam structure in the core layer and the distribution of metal ceramic materials in the surface layers significantly influence the thermomechanical vibration behavior of the sandwich plate. The application of an external magnetic field was found to enhance the thermal buckling resistance of the sandwich plate. The study results indicate that the wave propagation characteristics of the sandwich plate can be significantly influenced by different foam structures in the core and top layers, as well as by variations in material distribution qualities. The study’s findings are expected to substantially enhance the existing body of research and are applicable to emerging applications in fields such as sonar radars, aircraft, and marine vehicle stealth technologies.

The dual-phase-lag (DPL) model and Lord–Shulman (LS) theories, incorporating a single relaxation time, are utilized to analyze the impact of hydrostatic initial stress on a medium. A novel model will be introduced, utilizing two-temperature factors, to improve the photothermal theory. This study analyzes the effects of changing thermal and electrical conductivity. We examined the phenomenon of thermal loading on the exposed surface of an indefinitely extending semiconducting material in one dimension. This medium was also affected by plasma waves and the mechanical force generated during a photothermal process. The exact values of the variables in question are obtained using the Laplace transform (LT) approach. Furthermore, the two values of temperature coefficients were obtained by analytical methods. The field quantities are exhibited as numerical results in the physical domain and visually represented to illustrate the influence of distinct characteristics, such as electrical conductivity. The findings are compared with and without two-temperature components, as well as for two distinct values of the hydrostatic starting stress. A comparison is made between the computed variables obtained from generalized thermoelasticity using the DPL model and the LS theory. This comparison is performed in the absence and presence of the electrical conductivity parameter.

During the fatigue process, the variability in the residual strength of the composite gradually increased. This paper examined the transformation law of Weibull parameters for residual strength as a function of cycle count using experimental data and a literature review. The findings indicated that the attenuation of the shape parameters was tied to the degradation behavior of residual strength. Data from three distinct composite systems further indicate an approximately linear relationship between the shape parameter and residual strength, although additional validation is required under other loading and material conditions. A revised Weibull distribution model was introduced, enhancing the decay law of the shape parameters. The model better described the shape parameter, enabling accurate prediction of the variability in residual strength. With known Weibull parameters for material strength and fatigue performance, along with the law governing the weakening of residual strength, the probability distribution of strength after any number of cycles could be estimated.

Numerical simulation of complex geometries can be an expensive and time-consuming undertaking, in particular due to the lengthy preparation of geometry for meshing and the meshing process itself. To tackle this problem, immersed boundary and fictitious domain methods rely on embedding the physical domain into a Cartesian grid of finite elements and resolving the geometry only by adaptive numerical integration schemes. However, the accuracy, robustness, and efficiency of immersed or cut cell approaches depends crucially on the integration technique applied on trimmed cells. This issue becomes more apparent in nonlinear problems, where intermediate solution steps are necessary to achieve convergence. In this work, we adopt an innovative algorithm for boundary conformal quadrature that relies on a high-order B-spline re-parameterization of trimmed elements to address small and large deformation elasticity problems. We accomplish this using spline-based immersed isogeometric analysis, which eliminates the need for body conformal finite element mesh. The integration points are obtained by applying classical Gauss quadrature to conformal re-parameterizations of the cut elements, whereas the discretization itself is not refined. This ensures a precise integration with minimum quadrature points and degrees of freedom. The proposed immersed isogeometric analysis with boundary conformal quadrature is evaluated on benchmark problems for 2D linear and nonlinear elasticity. The results show convergence with optimal rates in h-and k-refinement, thus demonstrating the efficiency and the precision of the method. As demonstrated, in conjunction with the simple to implement penalization and deformation map resetting approaches in the fictitious domain, it performs robustly also for finite deformations. Furthermore, it is exemplified that the method can be easily applied for multiscale homogenization of microstructured materials in the large deformation regime.

This study investigates the wave propagation characteristics of functionally graded ZrO₂ and Nickel sandwich surface plate with Nickel foam core under various influencing factors, including power-law index, temperature rise, porosity, nonlocal parameter, size parameter, and graphene platelet reinforcement (GPLR) as well as different core distributions. Flexural, longitudinal, and shear wave modes were analyzed using Hamiltonian principle in order to establish small-scale (axial-shear-bending) governing equations utilizing refined shear deformation theory (RSDT) of plate in combination with nonlocal strain gradient theory (NSGT) and validated against published results. The wave responses of the nanoplate, considered with free boundary conditions, are analytically obtained by solving the governing equations. The effects of surface material gradation, thermal expansion, and elastic moduli on phase velocity, wave frequency, and group velocity were systematically explored. Results indicate that a zero-power index surface (ceramic) yields the highest wave properties due to superior stiffness while rising temperature and increasing foam porosity reduce wave velocities and frequencies due to softening effects. Nonlocal parameter increments lower phase and group velocities, whereas size parameter enhancements improve wave properties. Additionally, GPL reinforcement significantly enhances wave propagation behavior, demonstrating its potential for optimizing nanoplate performance. The study offers crucial insights for designing FG nanoplates for advanced thermal and mechanical applications, highlighting the tunability of wave propagation through material and structural modifications.

This paper presents a novel photo-thermoelastic wave model that integrates porosity effects, plasma interactions, and band-gap engineering within a semiconductor metamaterial framework under different boundary and excitation conditions. Due to its engineered porosity and periodic structure, a porous metamaterial is a structured composite material with unique mechanical, thermal, or wave propagation properties. The primary motivation behind this research is to explore how porosity-induced microvoids, thermal relaxation effects, and electron-plasma interactions influence the propagation of thermoelastic waves in porous semiconductor metamaterials. Introducing plasma wave interactions in the metamaterial framework, accounting for electron diffusion, recombination, and their influence on mechanical and thermal fields. Applying a normal mode technique to derive and solve governing differential equations in two dimensions that describe elastic, thermal, and plasma waves in a porous semiconductor metamaterial. The results indicate that by tuning porosity levels, carrier diffusion parameters, and thermal relaxation times, wave propagation in semiconductor metamaterials can be engineered for optimized energy transfer and signal processing applications.

Glass is an extensively used material in numerous branches such as automotive and aerospace industries as well as residential construction. The conventional production methods of glass are either subtractive or molding-based. However, for geometrically complex structures, additive manufacturing techniques are inevitable. Additive manufacturing of glass is a relatively new field especially when it comes to mathematical modeling and numerical simulation. A continuum-based mathematical model based on extended Hamilton’s principle is developed in this paper for phase transformation during the manufacturing process. The application of the model can be in the simulation of laser powder bed fusion (L-PBF) method. Since the focus is on modeling the phase change, mechanical deformation is excluded from the energy formulation. Three distinct phases, namely crystalline powder, liquid (molten), and amorphous solid, is considered, and the transformation of these phases is thermally driven. Whether a molten material turns into either crystalline or amorphous solid depends on the cooling rate. The proposed model is naturally capable of switching between these two paths in an energetic framework. To find an optimal setting for the manufacturing process in glass industry, numerical tools are remarkable alternatives to trial-and-error procedures which are time-consuming and expensive. The mathematical model is implemented using AceGen in the framework of finite element method leading to an in-house user element that can be invoked by many FE solver.

This paper investigates the transient fracture behaviors of an eccentric crack in a n-type piezoelectric semiconductor (PSC) strip subjected to anti-plane shear mechanical and in-plane electrical impacts. By employing Laplace and Fourier transform, the mixed boundary value problem is reduced to a standard Cauchy singular integral equation of the first kind, which is subsequently solved numerically to obtain the dynamic field intensity factors and energy release rate near the crack tip. Numerical results demonstrate that material conductivity promotes crack propagation under mechanical loading but suppresses it under electrical loading. Furthermore, thinner PSC layers and cracks positioned closer to the boundaries significantly increase structural risks. These findings may provide valuable theoretical insights for optimizing the performance and ensuring the long-term reliability of PSC devices.