With the continuous advancement of composite manufacturing technology and the requirements of civil aviation for economy, the application of lightweight and high-strength composite structures in the aerospace field has gradually expanded from thin-walled secondary load-bearing structures to large-thickness, variable-section main load-bearing structures. The wide application of these complex composite structural parts has raised higher requirements for their manufacturing reliability verification. However, due to the anisotropy of the composite materials and the complexity of the shape of the aviation structure, defects such as delamination, pores, fiber waviness, and resin-rich layers are prone to occur during the manufacturing process of the main load-bearing composite structure. These microstructural anomalies significantly degrade the macro-mechanical performance of the composite components. Ultrasonic testing has become an important technology of defect detection in aerospace composite structures due to its high penetration, high sensitivity and good applicability. In this paper, we first introduce the types and characteristics of manufacturing defects in aerospace composite structures, focusing on the analysis of the causes of defects such as pores, delamination, fiber waviness and resin-rich layers and their effects on the mechanical properties of the structure. Then, the research progress of ultrasonic testing in the detection of single-type manufacturing defects and mixed-type defects in thin laminate and thick composite structures in recent years is reviewed. Subsequently, the application of artificial intelligence technology in the defect diagnosis of composite structure is discussed. Finally, the challenges faced by the current ultrasonic testing of aviation composite structures are analyzed, and the future development trend is prospected.

Fatigue life prediction is crucial for the safety of metallic materials and structures. Machine learning (ML) models have demonstrated strong predictive capabilities in this field, but their "black-box" nature limits their reliability, trustworthiness, and application in engineering practice. Explainable Artificial Intelligence (XAI) provides key techniques to open the ML "black box". This paper aims to systematically review the current applications of XAI in the field of metal fatigue life prediction. Addressing the issue that current research applies various interpretation methods without systematic categorization, this paper proposes classifying existing methods into two main categories: "post-hoc explanations" and "interpretable by-design". This paper outlines the key techniques of these two categories and their specific application examples in fatigue life prediction, discusses the limitations of model interpretation methods and current technical challenges, and prospects for opportunities and challenges in subsequent research.

Inspired by the nervous system of biological movement, Central Pattern Generator (CPG) control theory is applied to achieve various gait patterns in legged robots, which is of great significance in bio-inspired motion control. For the gait movement control of hexapod robots, the classical Van der Pol (VDP) oscillator model is first improved by adding a time proportion function to adjust the rising and falling phases of the periodic rhythm signal, enabling the regulation of the swing and support phases of the robot's legs. Next, the improved VDP oscillator is used as a functional unit, and the coupling delay between units is employed to regulate gait patterns, constructing a novel time-delay coupled CPG controller with a unidirectional loop. Furthermore, a hexapod robot model is designed in SolidWorks, and co-simulation experiments using ADAMS and MATLAB are conducted to achieve three common gait patterns: tripod, tetrapod, and wave gaits. Finally, gait tests are performed on a physical prototype to verify the feasibility and effectiveness of the proposed time-delay coupled CPG control system.

Chiral Liquid Crystal Elastomers (CLCE), with their ability to selectively reflect specific wavelengths of light and exhibit excellent large-deformation capabilities, have gradually become a promising flexible reflective display material. Studies show that the optical coloration properties of CLCE are closely related to local strain, displaying a significant force-optical coupling effect. As a soft material, CLCE possesses viscoelastic characteristics, resulting in a time-dependent mechanical response during deformation. However, systematic research on the optical and viscoelastic coupling properties of CLCE under uniaxial and biaxial deformation conditions remains limited. In this study, using a multi-axial opto-mechanical testing platform, we systematically investigate the time-dependent characteristics of the reflection spectrum of CLCE under uniaxial and equibiaxial deformation conditions. By analyzing the spectral properties under stress relaxation and different loading rates, we propose an improved phenomenological model for CLCE based on the stretched exponential viscoelastic constitutive relationship. This model provides theoretical support and experimental insights for further optimizing the application of CLCE in smart optical devices.

During the charge and discharge processes of solid-state lithium metal batteries, the stress generated at the interface between the rough surfaces of the lithium electrode and solid-state electrolyte plays a crucial role in the formation of lithium dendrites. In this paper, a mechanical model is established by considering the electrode and electrolyte as elastic bodies. Specifically, the stress at the interface of a two-dimensional sinusoidal rough interface is investigated for isotropic linear elastic materials. Using a two-dimensional Fourier transform, the relationship between stress and displacement at the interface in the transform domain is obtained. By applying the inverse transform and incorporating boundary conditions and interface continuity conditions, an analytical solution for the interfacial stress in two dimensional conditions is derived. When the wavenumber of surface roughness in one direction of the interface is zero, the two-dimensional interfacial stress solution degrades to the one-dimensional case. Subsequently, the analytical solution is used to analyze the influences of the material parameters of the electrolyte and electrode on the magnitude of the interfacial stress.

In view of the high carbon emissions and limited land storage capacity in the eastern coastal areas of China, CO2 offshore geological storage holds significant application potential. Although the risk of CO2 leakage during offshore geological storage is extremely low, accurate assessment of CO2 diffusion in seawater under rapid leak scenarios is critical to ensure the safety of storage. Based on typical marine environment data, this study employs the Volume of Fluid (VOF) model to simulate the dynamic characteristics of CO₂ bubbles and utilizes the Euler model to simulate the diffusion characteristics of CO2 clusters in seawater, thereby completing a comprehensive simulation analysis of fluid dynamics. On this basis, a machine learning-based assessment method for subsea CO2 leakage is developed. The neural network model framework is constructed, and an inverse-problem solving model is established accordingly to analyze the morphological evolution and distribution range of CO2 leakage under different marine environmental conditions. Additionally, key parameters such as crack width and leakage velocity resulting from the leakage scenario are analyzed, enabling accurate calculation of the leakage amount. The prediction accuracy of this model can reach 95 %, demonstrating its effectiveness and applicability in addressing CO₂ leakage. This study not only offers an innovative method for rapid leakage assessment of CO2 offshore geological storage but also provides an important scientific basis and technical support for risk assessment and safety management in related fields in the future.

Low-frequency vibrations and noise levels are important indicators for evaluating automobile comfort. To address the issue of low-frequency vibrations and their control in automotive panel structures, we proposed a plate-type two-dimensional phononic crystal design based on the local resonance mechanism. The bandgap range of the phononic crystal was determined through the finite element method, and the mechanism of bandgap formation was analyzed. Subsequently, the transmission characteristics curve of the phononic crystal plate was calculated, and comparisons were also carried out for the vibration displacement. The results indicate that a complete bandgap appears in the plate within the frequency range from 62.48 Hz to 74.16 Hz. Within this frequency range, coupling effects between the base plate and the cylindrical resonators occur, leading to the formation of the bandgap. Elastic waves in the phononic crystal plate are successfully confined within the bandgap range. By adjusting the material and geometric parameters of the structure, the bandgap frequency range can be tuned to meet the requirements of more practical low-frequency applications. The structural design and analysis method proposed in this paper have broad application prospects in engineering fields such as low-frequency vibration reduction and noise control in automobiles.

Deoxyribonucleic acid (DNA), as the fundamental genetic material of life, possesses diverse mechanical characteristics endowed from its unique chemical and physical properties. These properties play a pivotal role in regulating gene expression, viral infection mechanisms, disease diagnostics, and intelligent nanodevices. A profound understanding of the mechanical properties and behaviors of DNA-like material—spanning from the molecular scale to the macroscopic device level—provides a foundation for unveiling the physical mechanisms underlying biological activities, advancing biomedical detection technologies, and enabling the precise design of dynamic nanodevices. This paper systematically reviewed recent research progress on the mechanical properties of DNA-like material and their applications in biomedicine and nanotechnology. First, some significant experimental advances across different-scale DNA systems were introduced, emphasizing how experiments revealed the influence of microstructure and environmental conditions on the mechanical properties and responses of DNA-like material. Second, the developments of theoretical models for the mechanical behavior of DNA-like material were explored, elucidating the mechanisms underlying relevant experimental findings. Finally, the paper identified the challenges in the current DNA-like material mechanics research and its practical implementation, and looked forward to the prospect of achieving breakthroughs through research paradigms such as "digital and intelligent mechanics".

Laminated beams are widely used in engineering structures due to their enhanced strength and stiffness. However, delamination, a barely visible form of damage, can occur during manufacturing or service. Accurate localization of delamination in laminated beams is essential for maintaining structural integrity. While the existing linear interface vibration model has been proposed to represent the absence of linear interface forces in the debonding region of open delamination, it fails to capture the opening-closing contact behavior of "breathing" debonding under nonlinear vibro-acoustic excitation. To address this problem, this study proposes a new nonlinear interface vibro-acoustic model, in which the nonlinear interface forces appear exclusively in the "breathing" debonding region, acting as multi-tone harmonic excitation sources to produce sideband harmonics. Moreover, this study emphasizes the use of nonlinear interface forces for the localization of delamination due to this inherent merit of localization. The nonlinear interface forces are reconstructed from nonlinear operating deflection shapes of a laminated beam. Nonlinear damage indices are established relying on nonlinear interfaces associated with multiple neighbouring sideband harmonics. The capability of the approach for localizing "breathing" debonding in laminated beams is experimentally validated through non-contact measurements using a scanning laser vibrometer. The results demonstrate that the approach is capable of predicting the occurrence of delaminations in laminated beams and accurately identifying their locations and sizes.

Damage identification is one of the most important aspects of structural health monitoring. In order to further improve the efficiency and accuracy of damage identification, a two-stage structural damage identification method based on the improved modal strain energy index and DBO-BP (Dung Beetle Optimization-Back Propagation) neural network is proposed. Firstly, the improved normalized damage index of modal strain energy is used for the damage localization analysis of the structure. Then, taking the average change rate of the structure unit modal strain energy as the input parameter, the stiffness reduction coefficient of the damaged unit as the output parameter, and utilizing the DBO algorithm which is an improved version of the optimal latin hypercubic method, the weights and thresholds of the BP neural network are optimized to perform the structural damage quantitative analysis. The concrete slab structure and flat rigid frame structure are used as exemplary models for damage identification verification. The results show that the proposed method is accurate in damage location identification, with high calculation efficiency for the degree of damage and small identification error as low as 0.4 %, exhibiting excellent damage identification performance.

Column buckling is a critical topic in university-level Materials Mechanics courses and is widely regarded as a challenging subject to teach. In classical Materials Mechanics theory, the critical load is determined by analyzing the non-zero solution condition of the approximate equilibrium differential equation in the critical buckling state. Although this method is straightforward, it remains highly abstract and is difficult to apply to complex engineering stability problems. To enhance students' understanding of column buckling and its analytical methods, this study revisits the classical approach through the principles of virtual work and minimum potential energy. Additionally, based on the principle of minimum potential energy, the thermal buckling behavior of carbon nanotubes under a longitudinal linear temperature gradient is examined. This work aims to provide new perspectives for the teaching and research of column buckling, helping students gain a deeper comprehension of relevant concepts and methods in handling buckling problems.

To meet new detection requirements and achieve high sensitivity, microbeam-based biosensor technique faces challenges in the development of signal interpretation models. Through 3D finite element simulations of the detected quasi-static signals of microbeam under surface adsorption, we revealed an asymmetric distribution characteristic of the microbeam cross-section's warping. However, the existing theoretical models considering shear deformation cannot accurately describe this asymmetric warping. To address this issue, first, we simplified the complete adsorption of molecules as a uniformly distributed surface stress acting on the microbeam's surface and obtained the distribution pattern of warping zero point through 3D finite element simulation. Then, we employed the semi-inverse method of plane elasticity theory to determine the shear stress distribution and shear force that correspond to the asymmetric warping characteristics on the deformed cross-section. This led to an improvement in Timoshenko beam theory and the establishment of a new model to predict the detected quasi-static signals of microbeam. Finally, we validated the analytical model by comparing with experimental results and finite element simulations. The results indicate that the predictions of our improved model agree well with the relevant microbeam experiments. Moreover, within the geometric size ranges employed in the existing adsorption-microbeam static experiments (length-to-thickness ratio of 200-500, length-to-width ratio of 3-7), its prediction error for the microbeam's free-end deflection is less than 3 %, which is smaller than that of other theoretical predictions. Additionally, the shear effect and axial force effect negatively impact the microbeam's deflection, with the shear effect having a significantly greater influence than the axial force effect. This model and its conclusions provide a new perspective for interpreting the static detection signals of microbeam biosensors and developing the relevant design.

By conducting tensile tests and numerical simulations on 304 stainless steel wire mesh/carbon fiber hybrid composite (SSWM/CFRP) laminates, the residual strength and failure modes of single hole specimens with different aperture sizes and double hole specimens with different circular hole arrangements were investigated. Digital Image Correlation (DIC) technology and Scanning Electron Microscopy (SEM) were used to observe the deformation and damage evolution characteristics of the specimens. The results indicate that the tensile stress-strain curve of SSWM/CFRP laminates with holes generally exhibits brittle failure characteristics. The residual strength of single hole specimens decreases with the increase of hole diameter, while the effective cross-sectional area of double hole specimens is affected by the arrangement of circular holes in the specimens. The DIC technology captures the maximum tensile and shear strains of a single hole specimen locally, which appear on the left and right sides of the circular hole along the diagonal direction. The constructed finite element model can effectively predict the residual strength and fracture path of the specimen, and reveal that the main failure modes of the specimen are ductile fracture of SSWM, fiber tensile damage of 0 ° fiber layer, matrix tensile damage of 90 ° fiber layer, and interlayer delamination damage.

The mechanical response of geotechnical granular materials exhibits multi-scale characteristics. The multi-scale simulations coupling the Finite Element Method (FEM) and Discrete Element Method (DEM) can effectively capture the multi-scale responses while maintaining high computational efficiency. A GPU-parallel FEM-DEM coupling code was developed based on the high-performance DEM software MatDEM, with computational parameters and results analyzed in conjunction with granular pore fractal characteristics. Firstly, multi-fractal theory was employed to investigate the spatial distribution characteristics of pores, identifying key fractal indices. Subsequently, the reliability of the FEM-DEM coupling code was verified through single element tests and biaxial compression tests. Finally, the meso-scopic responses of Representative Volume Elements (RVEs) at different locations were investigated based on biaxial compression tests. Results demonstrate that the pore spatial distribution within RVE exhibits multi-fractal characteristics. When the particle quantity exceeds 400, the self-similarity of pore spatial distribution ensures the stability of stress-strain responses output after homogenization of granular assemblies within RVE. The capacity dimension D0 and singularity index α0, which characterize the average information of pore distribution, show linear correlations with RVE volumetric strain. These indices can serve as internal variables reflecting the complexity of granular material spatial characteristics. This study provides an exploration for analyzing the macro-meso mechanical relationships in engineering-scale granular deposits.

To elucidate the complex bonding and fracture mechanisms at the interface between Ultra-High Performance Concrete (UHPC) and Normal Concrete (NC), this study systematically investigates how interfacial roughness and mesoscale structural characteristics influence interface mechanical performance. Four interface treatments (i.e., smooth surface, high-pressure water jetting, sandblasting, and chiseling) were comparatively analyzed through direct tension and shear tests, complemented by quantitative surface roughness characterization using laser scanning. Furthermore, X-ray Computed Tomography (X-CT) facilitated the three-dimensional reconstruction of UHPC-NC mesoscale structures, enabling advanced segmentation of pores, fibers, and other structural phases via deep learning algorithms. Multi-scale finite element modeling based on X-CT data simulated the damage evolution and crack propagation at the interface. Results indicate that chiseling significantly increased interfacial roughness, yielding substantial improvements in direct tensile and shear bond strengths by 123% and 126%, respectively, relative to the smooth surface. X-CT analysis revealed a distinct hydration transition zone at the interface, significantly influencing chemical bonding and exhibiting notably lower porosity compared to the NC matrix. Steel fibers from UHPC penetrated into the NC substrate, creating enhanced mechanical interlocking effects. Numerical simulations demonstrated that interface failure mechanisms are jointly governed by tensile failure within the NC substrate and crack propagation through the interfacial transition zone (ITZ), consistent with experimental observations of mixed-mode fractures. Overall, enhanced interfacial roughness improved bonding strength through both mechanical interlocking and chemical adhesion, while mesoscale structural defects critically influenced crack development pathways. The proposed multi-scale analytical approach provides comprehensive methodological support for optimizing the design and rehabilitation of concrete interfaces in engineering practice.

Interface consistency and error convergence are central issues in concurrent multiscale computational methods, particularly critical for atomistic-to-continuum coupling models. However, existing theoretical studies remain limited and are mostly confined to one-dimensional settings. This work focuses on the multiresolution molecular mechanics (MMM) approach and systematically investigates the impact of various energy sampling schemes on interface consistency and error convergence. Two-dimensional square and triangular lattice models containing both atomistic and coarse-grained regions are constructed under bilinear element interpolation. The results show that interface secondary sampling schemes can significantly improve consistency in the interfacial region, with the scheme incorporating all neighboring layers achieving the best performance. Error analysis reveals that discretization error dominates the total error, and increasing the number of secondary sampling points effectively reduces the sampling error, particularly under tensile loading conditions. Moreover, both lattice types exhibit consistent error convergence behavior, demonstrating high generality of the method to different structures. This study highlights the advantages of energy sampling strategies in improving interface treatment and convergence behavior in MMM, providing theoretical support for the development of high-accuracy multiscale computational mechanics methods.

In the precursor impregnation pyrolysis (PIP) process of ceramic matrix composites, the viscosity of the precursor liquid significantly affects the effectiveness and efficiency of its infiltration into the fiber preform. The solute mass fraction influences the viscosity itself in the impregnation solution. To provide a theoretical basis for optimizing the impregnation process, this study establishes an apparent viscosity model for precursor liquids with different solute contents. Firstly, an order parameter describing the solid and liquid phase content is introduced, establishing the interrelationship between shear stress, shear rate, and the order parameter of the precursor liquid. Then, based on Landau phase transition theory and the variational principle of the Lagrangian energy functional, a differential equation for the order parameter is constructed and solved, yielding an approximate analytical expression for apparent viscosity, mass fraction, and shear rate in a subdomain. Furthermore, a first-order approximation of the Bernstein polynomial is employed to extend the model to the entire computational domain, resulting in a viscosity model applicable to precursor liquids with different solute mass fractions. Finally, precursor liquids incorporating two types of additives, powders and binders, are examined. By calculating the effect of different mass fractions of additives on precursor viscosity, the validity of the model is verified, and the influence of solute mass fraction and shear rate on the apparent viscosity of the precursor liquid is analyzed based on the viscosity model.

This study systematically investigates the influence of the wall slip length (L_s) on the statistical properties and flow structures of turbulent channel flow. The Navier slip boundary condition is applied at the boundary of turbulent channel flow, and direct numerical simulation (DNS) is employed to numerically explore the evolution of turbulence for L_s ranging from 0 (no-slip) to 0.1. The results reveal that as L_s increases, the viscous damping effect at the wall is substantially reduced, resulting in an overall elevation of the mean velocity profile. Within the viscous sublayer, the mean velocity increment exhibits a linear relationship with L_s, satisfying the relation ∆〈U〉^+=Re_τ L_s. In the near-wall region, the turbulence fluctuation intensity demonstrates an enhanced dependence on , with the intensification of Q2 (ejection) events leading to an elevated Reynolds stress peak that shifts closer to the wall. Analysis of wall-attached low-speed streaks indicates that, for a dimensionless wall-normal structure scale l_y^+ < 50, both their number and volume increase significantly with rising L_s. Furthermore, it is found that the effects of the wall slip condition are confined to the near-wall region, while the outer inertia-dominated region continues to follow the scaling laws of no-slip wall turbulence.

Split-sleeve cold expansion technology is a critical process for improving the fatigue life of aerospace structural components. However, the influence of its parameter variations on fatigue performance remains insufficiently studied. This paper systematically investigates the sensitivity of initial hole diameter, thickness of split-sleeve, and diameter of the extrusion zone of the mandrel on the fatigue life of 7050-T7451 aluminum alloy through integrated fatigue testing, finite element simulation, and machine learning methods. Based on the S-N curve model of 7050-T7451 aluminum alloy and the critical distance line method, a fatigue life prediction model for cold-expanded holes was established. The model was then used to generate datasets for training an intelligent fatigue life prediction model. Leveraging 400 000 data points obtained from the intelligent model, Sobol global sensitivity analysis was conducted to quantify the independent and interactive contributions of these parameters to fatigue life.Results　indicate that the initial hole diameter has the most significant impact on fatigue life, dominating both independent effects and synergistic interactions, while the influence of Thickness of split-sleeve and mandrel diameter primarily manifests through interactive mechanisms. The study proposes prioritizing tolerance optimization for initial hole diameter while adopting collaborative design strategies for sleeve thickness and diameter of the extrusion zone of the mandrel. This methodology provides an efficient and economical approach for identifying critical process parameters and optimizing designs, demonstrating significant advantages over traditional physical experimentation and finite element analysis.

As a critical step in flexible electronics packaging, the ultra-thin chip peeling process plays a vital role in ensuring high-yield manufacturing. This study focused on mechanical behavior differences between two peeling methods: roller-stretching and needle-ejecting. A theoretical model of the "chip-adhesive-substrate" laminated structure was established and validated by finite element simulation. A dual-criteria safety criterion was proposed to quantify process safety based on the competing relationship between interfacial fracture energy of the adhesive layer and surface cracking stress of the chip layer, which overcame the limitations of traditional methods for quantitatively evaluating the safety of the peeling process. Results demonstrated that the needle-ejecting procedure outperforms roller-stretching in terms of the safety of ultra-thin chip peeling. The roller-stretching process only has high engineering application prospect for peeling large-sized and thick chips from soft and thick substrates. Furthermore, an innovative stretching-ejecting combination technology is proposed, introducing the concept of synergistic matching to achieve chip stress neutralization and fracture mode optimization. This research provides theoretical insights into non-destructive ultra-thin chip peeling technology, and delivers practical guidance for advancing high-yield flexible microelectronics packaging.

Shear fracture models play a crucial role in characterizing metal fracture, with shear tensile tests serving as the fundamental method for calibrating their parameters. However, existing shear tensile experiments often achieve limited maximum strain, making it difficult to maintain a stable shear state under large strain conditions. In this study, finite element analysis was conducted using LS-DYNA to simulate four distinct shear-tensile specimens, verifying the feasibility of their constitutive model and boundary conditions. Based on the guidelines from GB/T 34487-2017, a novel shear-tensile specimen is proposed. This new design ensures minimal stress triaxiality fluctuations (within ± 0.05) and achieves an effective plastic strain of up to 10% prior to fracture.

To investigate the effects of ambient pressure and standoff distance on the bonding quality of T2/Q235 explosive welding, a three-dimensional numerical simulation of the welding process was conducted using Ansys software. Two computational approaches-the Smooth Particle Hydrodynamics-Finite Element Method (SPH-FEM) coupled algorithm and the Arbitrary Lagrangian-Eulerian (ALE) method-were employed to analyze collision velocity and collision angle under varying ambient pressures (1 atm to 0.2 atm) and stand-off distances (3 mm, 6 mm, and 9 mm). Simulation results were systematically compared with experimental data and theoretical calculations. Key findings revealed that: (1) Under decreasing ambient pressure, maximum collision velocity occurred at 1 atm for the SPH-FEM method but shifted to 0.2 atm for the ALE method, aligning more closely with experimental observations; (2) Both algorithms consistently showed larger collision angles at the 6 mm stand-off distance compared to 3 mm and 9 mm configurations, with the ALE method yielding smaller angles closer to experimental lower bounds at 3 mm stand-off under atmospheric pressure; (3) At 0.2 atm ambient pressure and 6 mm stand-off, ALE simulations demonstrated superior agreement with theoretical predictions for both collision velocity and angle. The results conclusively demonstrate that the ALE algorithm achieves higher consistency with experimental measurements and theoretical models compared to the SPH-FEM approach, validating its effectiveness for simulating T2/Q235 explosive welding dynamics.

The free vibration problem of non-through cracked plates on fractional-order viscoelastic foundations is studied in this paper. First, a fractional-order viscoelastic foundation model is introduced to better describe the mechanical behavior of foundation. Next, the free vibration of cracked plate with through crack under the four-edge simply-supported boundary conditions is studied. Further, the through crack situation is generalized to the non-through crack situation. Based on the relation between the energy release rate and the stress instensity factor, the additional rotation angles induced by the crack is obtained, and the compliance coefficients of the crack equivilent rotation spring are derived for both the through and non-through crack situations. Finally, the complex natural frequency are obtained according to the boundary conditions. The numerical examples are provided and the influences of the fractional order coefficient, the viscosity coefficient, crack location and crack depth on the complex natural frequency and mode shape of the cracked plate were discussed.

Granite often contains initial cracks, therefore its strength characteristics are greatly affected by crack propagation. Most of the existing rock strength theories do not consider crack propagation, making them difficult to effectively reflect the strength and failure characteristics of the fractured granite. In this paper, uniaxial /triaxial compression tests and Brazilian splitting tests were conducted on the intact and fractured granite samples to study the strength and failure characteristics under tensile and compression conditions. The influences of confining pressure and crack inclination angle (the angle between the crack and the cross-section plane) on the strength stiffness and failure mode of granite were analyzed, and a method for calculating the strength of the initially cracked rocks was proposed. Based on the propensities of type II friction slip fracture in intact granite and type I-II composite fracture in fractured granite, the failure conditions of intact and fractured granite were established according to fracture mechanics theory. The experimental results show that the compressive strength and stiffness of granite specimens are significantly reduced by the introduction of initial crack. The compressive strength, elastic modulus, and secant modulus decrease with the crack inclination angle, while Poisson's ratio shows opposite trend. The initial cracks will significantly reduce the tensile strength of granite, which decreases with the decrease of crack inclination angle.

Graphene and its related two-dimensional materials have become a hot topic in the field of nanotribology. In recent years, many significant progresses have been made in theoretical, experimental, and computational simulation studies. Due to the extremely complex nature of nanoscale friction processes, the underlying mechanisms of friction are not yet fully understood. Therefore, it is necessary to delve into the mechanisms of friction and reveal the laws of friction on the atomic-scale. In this paper, the sliding friction behavior of a diamond probe on a suspended single-layer graphene surface is studied based on molecular dynamics simulation. The dependence of the friction on the normal load and the relationship between friction and actual contact area are considered. The results show that there is a nonlinear relationship between friction force and normal load (actual contact area), which is significantly different from the friction laws of bulk materials. Specifically, the friction force gradually increases with the load in the positive load range. However, the friction force is almost unaffected by changes in the load in the negative load range. The current research findings help to understand the nanoscale friction behavior of two-dimensional materials from an atomic perspective. This research can also provide new ideas and theoretical references for the design of nanodevices and the development of nanotribology.

Optimization of the natural frequencies of exponential functionally graded plates is a critical issue in the engineering field, playing a vital role in enhancing the dynamic performance of plate structures. In response to this challenge, this paper presents an innovative optimization approach that synergistically integrates the smoothed finite element method (SFEM) with surrogate models, aiming to address the problem with both high efficiency and precision. Based on the first order shear deformation theory, a SFEM is established for free vibration analyses of functionally graded plates. During the computation of the system stiffness matrix, gradient smoothing operations are applied to bending strains within smoothed domains, effectively improving computational accuracy. To overcome the shear locking phenomenon, different interpolation forms are adopted to treat bending strains and shear strains separately. For natural frequency optimization, a series of sample points are selected, and their corresponding natural frequencies are calculated using the SFEM. Subsequently, a surrogate model is established to map the relationship between the gradient index and the natural frequencies. The golden section method is employed to determine the optimal gradient index that achieves preset natural frequency targets. Numerical examples demonstrate that the surrogate model based on piecewise cubic Hermite interpolation exhibits high computational accuracy. Moreover, the surrogate model-based optimization significantly reduces the number of SFEM frequency calculations required, substantially enhancing optimization efficiency. This approach provides an efficient and practical method for optimizing natural frequencies of exponential functionally graded plates.

Due to the low strength of putty, it is impossible to directly measure its fracture toughness using the standard tensile fracture test. In order to accurately measure the tensile fracture toughness of low-strength materials such as putty, this study presents an improved compact tension test method and derives a tensile fracture toughness formula through numerical analysis. The formula is further refined by accounting for boundary effects, and its accuracy is validated through systematic testing with varying initial crack lengths. The results demonstrate that,the modified formula enables direct calculation of material fracture toughness. The stress intensity factor depends on relative boundary conditions rather than absolute boundary effects, with boundary effects becoming more pronounced with increasing initial crack length. The specimens exhibit pure Mode I fracture, with the modified formula yielding a stable fracture toughness of approximately 42 kN/m3/2. Experimental validation confirms the accuracy of both the improved test method and the modified formula, establishing their applicability for measuring fracture toughness in low-strength materials like putty and contributing to putty material development.

A study is conducted on the nonlinear dynamics of inclined flow pipes reinforced with graphene composite materials conveying fluid under two-phase flow conditions. Based on the von Karman nonlinear strain-displacement relationship and Hamilton's principle, the dynamic equations for inclined two-phase flow pipelines are established. The nonlinear dynamic model was solved using Galerkin method and fourth-order Runge-Kutta method to analyze the influence of the distribution pattern, weight fraction, and gas volume fraction of graphene platelets on the natural frequency and nonlinear dynamics of pipes conveying fluid. The experimental results show that the vibration amplitude of graphene reinforced pipes with V-shaped distribution is the smallest, followed by X-shaped distribution and A-shaped distribution. In addition, increasing the gas volume fraction can help alleviate fluid-induced vibration phenomena in pipelines. The above conclusion provides a theoretical basis for the application of graphene-reinforced inclined two-phase flow pipelines in practical engineering.

This study focuses on the integrated manufacturing process of sensors in unbonded flexible pipes for deep-sea mining engineering, investigating the sensor integration process with compensation reinforcement layers and their mechanical performance. A simulation model for the winding process of the compensation reinforcement layer in flexible pipes was established, systematically analyzing the influence patterns of winding tension and winding angles on sensor integration processes. Additionally, the effects of sensor quantity and winding angles on the tensile performance of integrated compensation reinforcement layers were explored. The results demonstrate that winding tension significantly affects sensor elongation rates, while winding angles predominantly influence stress distribution in the lining layer. The tensile performance of integrated compensation reinforcement layers shows minimal sensitivity to sensor quantity, and variations in winding angles within a specific range exhibit limited impact on anti-tensile properties. These findings reveal the correlation between sensor integration parameters and structural performance of flexible pipes, providing theoretical guidance for optimizing sensor integration processes in deep-sea flexible pipes.

To reveal the instability failure mechanism and energy evolution law of the rock mass with multiple cracks, a numerical model of red sandstone was established by using PFC2D. The mesoscopic parameters of the numerical model were calibrated based on the results of uniaxial compression tests and Brazilian splitting tests of intact red sandstone specimens. On this basis, the particle flow simulation tests of red sandstone with multiple cracks were carried out. The results show that with the increase of λ, the peak strength of the multiple-cracked red sandstone gradually decreases when the inclination angle remains unchanged; with the gradual increase of the inclination angle α, the peak strength of the multiple-cracked red sandstone gradually increases when the short-long axis ratio λ remains unchanged; the failure mode shows a diagonal tensile-shear failure, with tensile as the main and shear as the auxiliary, and the failure and instability mode of the specimens are all along the extension direction of the prefabricated cracks; the failure mode of the multiple-cracked red sandstone is jointly affected by the short-long axis ratio and the inclination angle; before the peak strength, the rock mainly shows the energy accumulation characteristics; at the peak strength, the total energy of the red sandstone is mainly elastic energy and supplemented by dissipated energy; at the instability failure, the total energy of the red sandstone is mainly dissipated energy and supplemented by elastic energy; the energy storage capacity and failure difficulty of the red sandstone change with the variation of the multiple-crack inclination angle α and the working conditions, which can be used as a reference for rock breaking operations; and a high-precision damage constitutive model of red sandstone based on different height-diameter ratios λ and different joint inclination angles α was established.

Bubbles are one of the important factors affecting the efficiency and quality of microreactors. Understanding the mechanisms of bubble transportation in the microchannel can provide guidelines for the designation. Meanwhile, bubble motion is one of the usual bubble transportation phenomena. In this paper, systematic and parametric studies of single bubble motion characteristics are conducted using computational fluid dynamics, aiming to derive fundamental principles and uncover the underlying mechanisms. The bubble motion principle during the initial detachment from the wall is proposed: while the trajectories of a single bubble may vary, the bubble will ultimately reach an equilibrium position (with a constant distance from the wall) across all parametric cases. Furthermore, the equilibrium position of the bubble is influenced by its diameter, the driving velocity, and the properties of the surrounding solution. Reynolds number (Re) and Capillary number (Ca) are selected as two characterized parameters. Based on the bubble diameter and common solution properties, the discussion cases in the range of 0.288<Re<97.2, 0.005<Ca<0.228. The relationship between Re and Ca can be distinguished by the bubble equilibrium position Ye (the dimensionless number of the distance between the final bubbles and the wall): (1) power law when 0<Ye<0.45; (2) linear when 0.45<Ye<0.95; (3) the bubble is attached to the wall (Ye=0) when the viscous effect is negligible; (4) the bubble is positioned in the center of the microchannel (Ye=1) when the viscous effect dominates. Corresponding, the mechanism can be underlaid by the manipulation forces, including wall-induced, deformable-induced, and shear stress gradient lifting forces and viscous drag force. In conclusion, the motion of the bubble is the combined influence of the wall, inertia, viscosity and surface tension effects.

This paper investigates the nonlinear vibration isolation problem of simply supported beam bridge structures under displacement excitation, employing the Incremental Harmonic Balance Method (IHBM) to derive an approximate analytical solution for the nonlinear vibration response of the beam. The research focuses on a coupled system consisting of a quasi-zero stiffness (QZS) isolator, constructed using a three-spring system, and a simply supported beam bridge. Based on the classical Euler-Bernoulli beam theory, the governing equations of motion under displacement excitation are established and systematically solved using the IHBM, with the entire analytical process thoroughly derived. The study transforms the final solution into a linear matrix equation using generalized coordinates, achieving a procedural and standardized computational process. To validate the reliability of the IHBM approximate analytical results, the study compares the IHBM computational results with numerical solutions obtained using the fourth-order Runge-Kutta method (ODE45). The results demonstrate that the IHBM method exhibits significant advantages in computational stability and result completeness. Additionally, through parametric analysis, the study explores the influence of key isolator parameters on system amplitude, further confirming the effectiveness and engineering practicality of the IHBM in nonlinear vibration isolation research. The research outcomes provide new theoretical foundations and methodological references for the nonlinear vibration isolation analysis of simply supported beam structures, offering important guidance for engineering practice.

With the rapid acceleration of population aging in China, the demand for feeding assistance among individuals with disabilities is becoming increasingly urgent. However, current feeding robots face several limitations such as poor adaptability to complex environments and safety concerns due to rigid structures. In this paper, a new six-degree-of-freedom feeding robot was developed that integrates obstacle avoidance path planning and compliance control. The robotic arm was designed employing a Bi-directional Rapidly-exploring Random Tree (Bi-RRT) algorithm to generate collision-avoidance trajectories, while inverse kinematics was solved using the Denavit-Hartenberg (D-H) parameter. At the control level, an impedance model-based compliance control strategy was introduced, and its compliant behavior under sudden external forces was verified through dynamic simulations. Prototype experiments demonstrated that the robot could effectively avoid obstacles and respond compliantly to external interference. While the robot achieved a 100% feeding success rate with solid and semi-liquid foods, it occasionally experienced spillage when feeding liquids due to structural limitations of the end-effector. This paper provides both a theoretical framework and practical guidance for enhancing the safety and environmental adaptability of feeding robots. Future work will focus on optimizing the end-effector design to further improve performance with liquid foods.

The Natural Element Method (NEM) is a meshless method based on natural neighbor interpolation. This method offers the advantages of simple shape function construction and ease of applying essential boundary conditions. Utilizing dimensional reduction techniques, a methodology for conducting lower bound limit analysis on two-dimensional elastoplastic structures has been developed through the application of NEM. In the lower-bound limit analysis, the elastic stress field is directly obtained using the NEM. The self-equilibrated stress basis vectors are derived from the elastoplastic iteration results of the NEM, and the required self-equilibrated stress field is constructed. The whole solution process of the problem is transformed into a series of sub-problems of nonlinear programming, which are solved through the complex method. Numerical examples demonstrate that the application of the Natural Element Method to lower-bound limit analysis is both feasible and effective.

The influence of friction coefficient and line density on the motion of continuous worm-like system is studied in this paper. Frist, based on the dynamic model and the quasi-static model describing the motion of worm-like system, the two average velocities over one period are respectively derived by employing the square strain wave. Next, through comparing these two average velocities, it is found that the dynamic model cannot be simplified as quasi-static model for small friction or large linear density conditions. Then, the condition under which the influences of these parameters on the motion of worm-like system should be considered is given on the basis of relative error principle of the average velocity. Finally, through a numerical example, the two models are compared for the displacement-time histories over ten periods. It is found that the parameters of friction coefficient and line density have significant influences on the system motion in certain conditions.

For the dynamic process of harvesting energy from water droplet impact by using piezoelectric beams, a water droplet impact force model was developed. Based on the Euler Bernoulli beam theory, an electromechanical coupling prediction model of piezoelectric cantilever beam was established. Droplet impact tests were conducted, the voltage output characteristics and dynamic response characteristics of the piezoelectric beams were analyzed. By comparing the experimental results and model prediction results under different impact conditions (droplet diameter Dd = 2.4~4.4 mm and impact velocity Vd = 1.0~3.4 m/s), the accuracy of the force electromechanical coupling model was verified. Results showed that there is a linear relationship between the maximum deformation of cantilever end and the peak voltage under the impact excitation of water droplets. Water droplets exhibit "rebound" and "splashing" characteristics under low and high Weber number conditions, respectively, and the experimental results are highly consistent with the predicted results of the model, verifying the applicability and accuracy of the model. As the cantilever length increases, the natural frequency and the bending stiffness of the system gradually decreases, the output voltage and the total energy harvested gradually increase; however, the electric energy density shows a trend of first increasing and then decreasing, reaching a maximum of dE = 4.27 mJ/m2 when the cantilever beam length L = 35 mm.

The free vibration analysis of membranes is of significant importance in engineering structures, especially in the design and optimization of membrane structures. This paper presents a new type of triangular element, aiming to improve the computational accuracy in free vibration analysis of membranes. Traditional 3-node triangular elements in membrane vibration analysis typically rely on polynomial shape functions, but this method often suffers from insufficient accuracy in complex vibration modes and high-order frequencies. To address this issue, this paper constructs a 10-node triangular element with the shape function incorporating trigonometric functions. The proposed 10-node triangular element consists of three corner nodes, two points of trisection for every edge, and the centroid node with its shape functions derived using the area coordinate method. The stiffness matrix and mass matrix are derived, and the frequencies and modes for free vibration of the membrane are computed, thereby the dynamic characteristics can be studied. To evaluate the effectiveness of this element, several typical examples are chosen, including the free vibration analysis of rectangular membrane and triangular membrane. By comparing with theoretical solutions and the 3-node element calculations in Ansys, the obtained results show that the 10-node triangular element can approximate the theoretical solutions with few computational elements. And the precision of the presented 10-node element is similar with that of the standard 10-node triangular element. The high precision of the proposed element is demonstrated in analysis of free vibration of membrane, which has the potential of further research and promotion.

The study focuses on the curing process and mechanical behavior of E44 epoxy resin in unconstrained structures. A Fiber Bragg Grating (FBG) sensor is used to monitor the temperature and strain of the resin in the thin-walled encapsulation structure in real-time. Based on curing kinetics, heat conduction, and viscoelastic models, the curing performance parameters and stress relaxation functions are derived, providing essential input data for the numerical simulation of epoxy resin curing behavior. The objective of the study is to develop a finite element simulation model for the epoxy resin encapsulation structure, taking into account residual stress and temperature effects, and to validate the model's accuracy by comparing it with experimentally measured temperature and strain data. The results show that the maximum temperature error does not exceed 10 %, and the maximum strain error is within 30 %, demonstrating the reliability of the analytical method and finite element model. This research provides testing and characterization methods, as well as theoretical support, for the cracking and interface debonding of epoxy resin under high and low-temperature cycling conditions.

For the lightweight design problem of composite grid-stiffened sandwich cylindrical shells, this paper proposes an optimization strategy that couples the differential quadrature method (DQM) with intelligent algorithms. First, the buckling governing equations are established based on the smeared stiffener method and energy principle, which are efficiently solved using DQM and validated through finite element analysis. Subsequently, an artificial neural network (ANN) surrogate model and genetic algorithm (GA) are employed to achieve structural optimization. The results demonstrate that the critical buckling loads obtained via DQM agree well with finite element results, confirming the accuracy of DQM in analyzing the buckling of sandwich cylindrical shells. The ANN-based surrogate model exhibits high reliability in predicting the critical buckling loads of grid-stiffened sandwich shells. Moreover, the genetic algorithm, combined with theoretical results, efficiently yields lightweight design parameters. Case studies show that the optimized structure not only achieves significant weight reduction but also exhibits a substantial increase in critical buckling load.

In the process of energy storage and power generation in molten salt tanks, the ceramic particle layer at the bottom of the tank plays a critical role in load-bearing and thermal insulation. Under cyclic loading, analyzing the effects of particle compression, flow, and contact stress on the overall settlement of the ceramic particle layer provides an important basis for design. In this study, the Hertz-Mindlin contact model in EDEM software was employed to establish a discrete element particle simulation model for the ceramic particle layer at the bottom of the molten salt tank. Simulations were conducted for the compaction backfill process and full-tank working conditions, and a comparative analysis was performed to investigate the effects of pre-compaction processes and particle size distribution on the compression settlement and maximum equivalent stress of the ceramic particles, as well as the influence of randomness in discrete element analysis results. The results indicate that for a ceramic particle layer height of 1.6 m and a particle size range of 5~20 mm, adopting a segmented compaction backfill process under a 50 000-ton tank load results in a maximum internal particle stress of 18.1~21.8 MPa and an overall settlement of 20.44~29.6 mm. As the particle size increases, the maximum stress decreases, with a maximum stress of 12 MPa observed for particle sizes of 15~20 mm. However, the settlement increases significantly, reaching 184 mm. Therefore, a wide particle size distribution range is beneficial for reducing settlement. Considering these factors comprehensively, the optimal configuration is a particle size range of 5~20 mm with a segmented and repeated pre-compaction process. Accounting for the influence of particle randomness, the maximum stress of the ceramic particle layer is 23.16 MPa, and the maximum settlement is 23.5 mm, meeting the design requirements.