Archive of Applied Mechanics最新文献

To analyze the computational mechanisms of longitudinal motion at stiffening girder ends of suspension bridges under vehicle loads, a new simplified calculation method is proposed. The longitudinal motion is modeled as a single-degree-of-freedom (SDOF) forced vibration system. The spring stiffness coefficient of the SDOF system is derived based on mechanical equilibrium and geometric compatibility conditions, and the unbalanced horizontal cable force at main cable suspension points is identified as the driving force of the longitudinal motion. A harmonic function is established to correlate the unbalanced horizontal cable force with vehicle load positions. An explicit equation for the extreme values of unbalanced horizontal cable force is derived using deflection theory. By defining the harmonic load as the excitation force, the bridge longitudinal stiffness coefficient as the SDOF system spring stiffness coefficient, and the stiffening girder mass as the SDOF system mass, an explicit equation is derived to characterize longitudinal motion at stiffening girder ends under vehicle loads. Finally, the effects of vehicle speed and damping ratio on the dynamic amplification factor are investigated. Comparisons with the finite element model (FEM) validate that the dynamic effects of vehicle loads on the longitudinal displacement at stiffening girder ends are reasonably close to static effects, with calculation errors controlled within 5% for displacement and 4‰ for unbalanced horizontal cable force. Both vehicle speed and damping ratio affect the dynamic amplification factor.

Microencapsulated self-healing resin mineral composites (MSRMCs) are widely recognized for their excellent dynamic performance and intrinsic crack-repair ability. However, existing mechanical models fail to accurately capture the complex interactions between the constituent phases, particularly the role of the interfacial transition zone (ITZ). To address this limitation, this study develops a three-dimensional finite element model of a core–wall–ITZ–matrix composite by integrating the Mori–Tanaka method with the generalized self-consistent model. The model is validated against published experimental data and subsequently employed to systematically investigate the influence of ITZ and microcapsule parameters on the elastic properties of MSRMC. The results indicate that: (1) increasing the ITZ thickness alters composite properties by up to 15.72%, while higher ITZ modulus raises the elastic modulus by a maximum of 14.23%; (2) the microcapsule distribution significantly affects the elastic response, with a modulus difference of 0.2547 GPa between clustered and uniform arrangements; (3) larger capsule size, stiffer walls, and greater wall thickness enhance the overall stiffness, with property increments reaching 18.62%. These results provide a theoretical foundation and a preliminary reference for the design and performance optimization of MSRMC, though their direct applicability to advanced engineering applications awaits further experimental validation.

In this paper, the investigations of free vibrations are presented for the analysis of isotropic homogeneous thermoelastic hollow cylinder in the context of spatiotemporal theory of nonlocal elasticity with double porosity. The governing equations are transformed into ordinary differential equations from partial differential equations using time harmonic vibration technique. Analytical results have been verified through computations and simulations for frequency shift and thermoelastic damping at various values of normalized thickness and non-locality parameter, which are derived from the analytical expressions and illustrated graphically with respect to mode number. The obtained analytical results were implemented in MATLAB software to present the numerical functional iteration method for free vibration analysis. The tabulated natural frequencies have been shown in tables which yields that the variation of vibrations go on increasing with increase in mode number. The findings of this study have potential applications in nanotechnology, smart materials, energy storage systems, biomedical implants and aerospace components.

Hollow spheres have been widely utilized in marine engineering and other fields. The mechanical behavior of the spherical shell under external pressure is influenced by corrosion. This study investigates the elastoplastic collapse of corroded spherical shells under external pressure by combining theoretical analysis and the machine learning. The existing elastic buckling theoretical formulas for perfect hollow spheres are summarized. Starting from classical buckling formulas for intact spherical shells, an elastoplastic collapse expression is developed for shells with local thickness reduction, and its applicability is examined over a broad range of geometric and material parameters. The influence of corrosion size, residual thickness, shell geometry, and yield strength on collapse pressure is systematically quantified, discussing the transition from yield-dominated response to instability-controlled failure. To address random corrosion that are difficult to characterize analytically, a convolutional neural network (CNN) is trained using finite element datasets constructed from spatial thickness distributions and corresponding collapse-pressure reduction factors. The trained CNN enables efficient prediction of collapse pressure. The results show that the developed elastoplastic formula provides a rational description of locally thinned spherical shells, and that the trained CNN offers an effective reduced-order tool for rapidly evaluating randomly corroded shells. The study contributes to the mechanics-based assessment of corrosion-weakened spherical shells and provides a unified route from theoretical modeling to fast structural integrity evaluation.

Elliptical cracks widely exist in practical engineering structures. The nonlocal theory postulates that the stress at a given point depends on the strain at that point itself, as well as the strain fields over the entire computational domain, thereby providing more accurate predictions when materials are scaled down to micro- and nanometers. The novelty of this work lies in the first investigation of nonlocal thermal fracture behavior and thermal shock resistance of nanoplates containing embedded elliptical cracks, for which closed-form analytical expressions of the nonlocal thermal stress field are derived via a semi-analytical approach. Based on the resulting thermal stress fields, the thermal stress intensity factor is calculated, and its variations with crack geometry (particularly the c/a ratio), thermal shock duration, and crack length are systematically analyzed. Furthermore, two failure criteria (the strength criterion and the fracture toughness criterion) are jointly adopted to assess the overall thermal shock resistance, enabling a comprehensive evaluation that complements each criterion’s limitations. Finally, the thermal shock resistance predicted by the nonlocal and local models is compared, revealing the significant scale effect on fracture behavior at the nanoscale.

Accurate prediction of notch stress field and stress intensity factor (N-SIF) is very important for understanding and optimizing the fatigue performance of notched composite structures. However, the traditional analytical method faces limitations in dealing with the complex nonlinear relationship of anisotropic composites, which leads to great prediction errors in some cases. An approach based on interpretable neural network is proposed and improved to predict the notch stress field and N-SIF value of notched composites. The proposed method combines the SHAP (SHapley Additive exPlanations) method to improve the interpretability and feature importance analysis. The neural network is trained according to the stress field data generated by finite element analysis, and is studied and verified through various notch geometries and material characteristics. The results show that the prediction error of the proposed approach on the verification set is less than 3%, which is more accurate than the traditional method. In addition, SHAP analysis shows that the geometric ratio and eigenvalue are the key factors affecting the prediction of N-SIF. This framework not only improves the accuracy of N-SIF prediction, but also provides an effective and interpretable tool for structural design and optimization of notched composites.

To reduce the stress concentration of composite structures with cutouts, this paper presents a principal stress lines-driven (PSLs-driven) design method for variable stiffness (VS) composite structures with cutouts. To address local directional discontinuities in the principal stress direction field (PSDF), particularly in high-stress gradient regions under complex non-uniform loading, an adaptive local smoothing criterion considering principal stress magnitudes is developed to improve directional continuity while preserving load transfer characteristics. Following PSL generation obtained from the Euler method, a geometric interpolation-based fiber placement strategy is introduced to translate continuous PSLs into element-wise fiber orientations, achieving close synergy between structural stiffness and the principal stress field (PSF). Numerical results show that the proposed VS laminates reduce stress concentration at the cutout boundary by at least 10.2% compared with constant stiffness (CS) laminates, and also outperform streamline‑driven fiber laminates. For a composite cylindrical shell with a single cutout under non‑uniform loading, the method reduces circumferential deformation by 13.7% and cutout boundary stress concentration by 34.3%. The research results indicate that the PSLs-driven design method for VS composite structures with cutouts proves to be highly applicable and effective, offering a viable approach for developing high-performance composite structures with cutouts.

In the present study, a physics-informed simulation-based digital twin framework for an automotive suspension system exposed to transient and stochastic road excitations is formulated for health monitoring and prognostics. A physics-based quarter-car dynamic model is considered for the development of governing equation of motion and integrated with the state estimation and online damping parameter tracking to synchronize the virtual model with the simulated degrading physical system. Further, the proposed framework is assessed through obtaining the response data under controlled road excitations, where the prescribed road displacement and velocity serve as excitation inputs during the state estimation process. A normalized suspension health index (SHI) is obtained continuously from the estimated damping coefficient to quantify its degradation in real time. Initially, remaining useful life (RUL) of the suspension system is evaluated using the conventional slope-based degradation approach. The numerical instability of the slope-based approach is evident from the presence of artificial spikes and projection of unreliable life. However, this limitation is overcome through developing a cumulative damage-based prognostic of suspension system such that the life degradation is expressed in terms of integral of degradation of intensity of the damping coefficient, obtained through SHI. The comparative analysis under half-cosine bump and stochastic road inputs demonstrates that the proposed damage-based RUL approach provides stable, interpretable, and monotonic prognostic estimates. Further, the robustness of the proposed framework against the various uncertainties in vehicle loading is investigated through performing a mass sensitivity analysis. The various uncertainties such as the variation in the sprung mass depending on passenger occupancy, payload, and operating conditions are considered for the investigation. Further, the results demonstrate that the proposed digital twin framework enhances the robustness and reliability of suspension life prediction through integrating the time-varying damping coefficient, SHI, and cumulative damage modelling. It can be concluded that the proposed simulation-based digital twin framework yields a scalable foundation for the physics-informed health monitoring, prognostic studies and offers a extensible basis for future real-world implementation.

This paper investigates the sliding adhesive contact mechanics of one-dimensional (1D) hexagonal piezoelectric quasicrystals (PEQCs) coating. Under the assumption of perfect bonding between the coating and the rigid substrate, the frequency response functions for the relevant physical quantities are derived analytically via the double Fourier integral transforms by combining the fundamental solutions of 1D hexagonal PEQCs half-space with the adhesive contact boundary conditions. The adhesion-driven conjugate gradient method (AD-CGM) and the discrete convolution-fast Fourier transform (DC-FFT) technique are employed to numerically calculate the stress and displacement fields. Numerical results reveal the significant effects of the friction coefficient, total charge, adhesion parameters, and coating thickness on the adhesive contact behavior. The findings establish a theoretical foundation for the reliability design and performance optimization of novel PEQCs functional coating in micro-electromechanical systems (MEMS) and nanodevices, particularly with regard to interfacial stress regulation and anti-adhesion surface engineering.

This study involves the nonlinear buckling of deep-buried functionally graded porous (FGP) pipelines with irregular (egg-shaped) cross-sections mixed with graphene platelets (GPLs). After heating, the pipeline deflects radially inward since it is constrained tightly and rigidly by the medium (soils/rocks). A refined sine formula is utilized to express this deformation. The response equations are derived by combining the thin-walled shell scheme and energy theory. The response equations are solved to acquire the minimum and critical temperature variations, respectively. Moreover, strict validation is completed to prove the analytical scheme. One may observe that the curves between the analytical scheme and other studies are closely fitted. Finally, this study evaluates the effects of several key indices on the stability of the FGP-GPLs egg-shaped submarine pipeline, involving the porosity coefficient, geometric profile, weight fraction, etc.