Search Results (10,533)

Studying nonlinear oscillations in mechanical systems is fundamental to understanding complex dynamic behavior in engineering applications. While classical analytical methods remain valuable for systems with limited complexity, they become increasingly inadequate when nonlinearities are strong and geometrically induced, as in the case of large-amplitude oscillations. This paper presents a combined numerical and experimental investigation of a mechanical system composed of two coupled pendulums, exhibiting significant nonlinear behavior due to elastic deformation throughout their motion. A mathematical model of the system was developed using the MatLab/Simulink ver.6.1 environment, considering gravitational, inertial, and nonlinear elastic restoring forces. One of the major challenges in accurately modeling such systems is accurately representing damping, particularly in the absence of dedicated dampers. In this work, damping coefficients were experimentally identified through decrement measurements and incorporated into the simulation model to improve predictive accuracy. The simulation outputs, including angular displacements, velocities, accelerations, and phase trajectories over time, were validated against experimental results obtained via high-precision inertial sensors. The comparison shows a strong correlation between numerical and experimental data, with minimal relative errors in amplitude and frequency. This research represents the first stage of a broader study aimed at analyzing forced and parametrically excited oscillations. Beyond validating the model, the study contributes to the design of a robust experimental framework suitable for further exploration of nonlinear dynamics. The findings have practical implications for the development and control of mechanical systems subject to dynamic loads, with potential applications in automation, vibration analysis, and system diagnostics. Full article

Due to the frequent occurrence of coarse-grained structures in large hydrogenation tube sheets, their hydrogen resistance and corrosion resistance deteriorate, significantly shortening their service life. Therefore, microstructure evolution must be strictly controlled during the forging process. High-temperature compression tests were simulated using a Gleeble-1500D thermal simulator to investigate the hot deformation behavior of 14Cr1Mo pressure vessel steel under deformation conditions of 1050–1250 °C and strain rates of 0.01–1 s⁻¹. Based on the experimental data, the flow stress curve of 14Cr1Mo steel was obtained, and its thermal deformation behavior was analyzed. Furthermore, the dynamic recrystallization (DRX) kinetic model and grain size model of 14Cr1Mo steel were established. These models were then integrated into the finite element software Forge^® to validate the accuracy of the DRX models. The results showed excellent agreement between the simulated and experimentally measured grain sizes, with a maximum deviation of less than 8%, confirming the high accuracy of the dynamic recrystallization models. These models provide a theoretical basis for finite element simulation and microstructure control in the manufacturing of super-large pressure vessel tube sheet forgings. Full article

The interaction between thermal fields and mechanical loads in thin-walled cylindrical shells introduces complex dynamic behaviors relevant to aerospace and mechanical engineering applications. This study investigates the axial stress wave propagation in a circular cylindrical shell subjected to combined thermal gradients and time-dependent harmonic compression. A semi-analytical model based on Donnell–Mushtari–Vlasov (DMV) shells theory is developed to derive the governing equations, incorporating elastic, inertial, and thermal expansion effects. Modal solutions are obtained to evaluate displacement and stress distributions across varying thermal and mechanical excitation conditions. Empirical Mode Decomposition (EMD) and Instantaneous Frequency (IF) analysis are employed to extract time–frequency characteristics of the dynamic response. Complementary Finite Element Analysis (FEA) is conducted to assess modal deformations, stress wave amplification, and the influence of thermal softening on resonance frequencies. Results reveal that increasing thermal gradients leads to significant reductions in natural frequencies and amplifies stress responses at critical excitation frequencies. The combination of analytical and numerical approaches captures the coupled thermomechanical effects on shell dynamics, providing an understanding of resonance amplification, modal energy distribution, and thermal-induced stiffness variation under axial harmonic excitation across thin-walled cylindrical structures. Full article

The structural units with different characteristic scales in gradient nanostructured (GS) 316L stainless steel act synergistically to achieve the matching of strength and plasticity, and the intrinsic plasticity of nanoscale and ultrafine grains is fully demonstrated. The macroscopic stress–strain responses of each material unit in the GS surface layer can be measured directly by tension or compression tests on microspecimens. However, the experimental results based on microspecimens do not reflect either the extraordinary strengthening effect caused by non-uniform deformation or the intrinsic plasticity of nanoscale and ultrafine grains. In this paper, a method for constructing depth-dependent constitutive relationships of GS materials was proposed, which combines strain hardening parameter (hardness) with physics-informed neural networks (PINNs). First, the microhardness distribution on the specimen cross-sections was measured after stretching to different strains, and the hardness–strain–force test data were used to construct the depth-dependent PINNs model for the true strain–hardness relationship (PINNs_εH). Hardness–strain–force test data from specimens with uniform coarse grains were used to pre-train the PINNs model for hardness and true stress (PINNs_Hσ), on the basis of which the depth-dependent PINNs_Hσ model for GS materials was constructed by transfer learning. The PINNs_εσ model, which characterizes the depth-dependent constitutive relationships of GS materials, was then constructed using hardness as an intermediate variable. Finally, the accuracy and validation of the PINNs_εσ model were verified by a three-point flexure test and finite element simulation. The modeling method proposed in this study can be used to determine the position-dependent constitutive relationships of heterogeneous materials. Full article

Reservoir-induced landslides threaten infrastructures and downstream communities, making continuous deformation monitoring vital. Time-series InSAR, notably the SBAS algorithm, provides high-precision surface-displacement mapping but suffers from voids due to layover/shadow effects and temporal decorrelation. Existing deep-learning approaches often operate on fixed-size patches or ignore irregular spatio-temporal dependencies, limiting their ability to recover missing pixels. With this objective, a hybrid spatio-temporal Graph Attention (ST-GAT) framework was developed and trained on SBAS-InSAR values using 24 influential features. A unified spatio-temporal graph is constructed, where each node represents a pixel at a specific acquisition time. The nodes are connected via inverse distance spatial edges to their K-nearest neighbors, and they have bidirectional temporal edges to themselves in adjacent acquisitions. The two spatial GAT layers capture terrain-driven influences, while the two temporal GAT layers model annual deformation trends. A compact MLP with per-map bias converts the fused node embeddings into normalized LOS estimates. The SBAS-InSAR results reveal LOS deformation, with 48% of missing pixels and 20% located near the Dasu dam. ST D-GAT reconstructed fully continuous spatio-temporal displacement fields, filling voids at critical sites. The model was validated and achieved an overall R² (0.907), ρ (0.947), per-map R² ≥ 0.807 with RMSE ≤ 9.99, and a ROC-AUC of 0.91. It also outperformed the six compared baseline models (IDW, KNN, RF, XGBoost, MLP, simple-NN) in both RMSE and R². By combining observed LOS values with 24 covariates in the proposed model, it delivers physically consistent gap-filling and enables continuous, high-resolution landslide monitoring in radar-challenged mountainous terrain. Full article

The large-scale utilization of hydrogen energy is currently hindered by challenges in low-cost production, storage, and transportation. This study focused on investigating the impact of the diaphragm cavity profile on the movement behavior and stress distribution of a dual-stage diaphragm compressor. Firstly, an experimental platform was established to test the gas mass flowrate and fluid pressures under various preset conditions. Secondly, a simulation path integrating the finite element method simulation, theoretical stress model, and movement model was developed and experimentally validated to analyze the diaphragm stress distribution and deformation characteristics. Finally, comparative optimization analyses were conducted on different types of diaphragm cavity profiles. The results indicated that the driving pressure differences at the top dead center position reached 85.58 kPa for the first-stage diaphragm and 75.49 kPa for the second-stage diaphragm. Under experimental conditions of 1.6 MPa suction pressure, 8 MPa second-stage discharge pressure, and 200 rpm rotational speed, the first-stage and second-stage diaphragms reached the maximum center deflections of 4.14 mm and 2.53 mm, respectively, at the bottom dead center position. Moreover, the cavity profile optimization analysis indicated that the double-arc profile (DAP) achieved better cavity volume and diaphragm stress characteristics. The first-stage diaphragm within the optimized DAP-type cavity exhibited 173.95 MPa maximum principal stress with a swept volume of 0.001129 m³, whereas the second-stage optimized configuration reached 172.57 MPa stress with a swept volume of 0.0003835 m³. This research offers valuable insights for enhancing the reliability and performance of diaphragm compressors. Full article

This study investigates the long-term performance of flexible anti-collision rings after 12 years of service on the Xiangshan Port Highway Bridge. Stepwise loading–unloading tests at multiple loading rates (0.8–80 mm/s) were performed on the anti-collision rings, with full-field strain measurement via digital image correlation (DIC) technology. The results show that: The mechanical response of the anti-collision ring shows significant asymmetric tension–compression, with the tensile peak force being 6.8 times that of compression. A modified Johnson–Cook model was developed to accurately characterize the tension–compression force–displacement behavior across varying strain rates (0.001–0.1 s⁻¹). The DIC full-field strain analysis reveals that the clamping fixture significantly influences the tensile deformation mode of the anti-collision ring by constraining its inner wall movement, thereby altering strain distribution patterns. Despite exhibiting a corrosion gradient from severe underwater degradation to minimal surface weathering, all tested rings demonstrated consistent mechanical performance, verifying the robust protective capability of the rubber coating in marine service conditions. Full article

This study introduces an analytical framework that integrates the state-space method with generalized thermoelasticity theory to obtain exact solutions for the static and dynamic behaviors of laminated plates featuring imperfect interfaces and resting on a Winkler foundation. The model comprehensively accounts for the foundation-structure interaction, interfacial imperfection, and the coupling between the thermal and mechanical fields. A parametric analysis explores the impact of the dimensionless foundation coefficient, interface flexibility coefficient, and thermal conductivity on the static and dynamic behaviors of the laminated plates. The results indicate that a lower foundation stiffness results in higher sensitivity of structural deformation with respect to the foundation parameter. Furthermore, an increase in interfacial flexibility significantly reduces the global stiffness and induces discontinuities in the distribution of stress and temperature. Additionally, thermal conductivity governs the continuity of interfacial heat flux, while thermo-mechanical coupling amplifies the variations in specific field variables. The findings offer valuable insights into the design and reliability evaluation of composite structures operating in thermally coupled environments. Full article

In this study, growth mechanisms are proposed to understand how banded dendritic crystal aggregates in poly(1,4-butylene adipate) (PBA) transform into straight dendrites upon dilution with a large quantity of poly(ethylene oxide) (PEO) (25–90 wt.%). In growth packing, crystal plates are deformed in numerous ways, such as bending, scrolling, and twisting in self-assembly, into final aggregated morphologies of periodic bands or straight dendrites. Diluting PBA with a significant amount of PEO uncovers intricate periodic banded assemblies, facilitating better structural analysis. Both circularly banded and straight dendritic PBA aggregates have similar basic lamellar patterns. In straight dendritic PBA spherulites, crystal plates can twist from edge-on to flat-on, similar to those in ring-banded spherulites. Therefore, twists—whether continuous or discontinuous—are not limited to the conventional models proposed for classical periodic-banded spherulites. Thus, it would not be universally accurate to claim that the periodic circular bands observed in polymers or small-molecule compounds are caused by continuous lamellar helix twists. Straight dendrites, which do not exhibit optical bands, may also involve alternate crystal twists or scrolls during growth. Iridescence tests are used to compare the differences in crystal assemblies of straight dendrites vs. circularly banded PBA crystals. Full article

The icebreaking process of water-exiting vehicles involves complex nonlinear interactions as well as multi-physical field coupling effects among ice, solids, and fluids, which poses enormous challenges for numerical calculations. Addressing the low solution accuracy of traditional grid methods in simulating large deformation and destruction of ice layers, a numerical model was established based on the FEM-SPH-SALE coupling algorithm to study the dynamic characteristics of the water-exiting vehicle on the icebreaking process. The FEM-SPH adaptive algorithm was used to simulate the damage performance of ice, and its feasibility was verified through the four-point bending test and vehicle breaking ice experiment. The S-ALE algorithm was used to simulate the process of fluid/structure interaction, and its accuracy was verified through the wedge-body water-entry test and simulation. On this basis, numerical simulations were performed for different ice thicknesses and initial velocities of vehicles. The results show that the motion characteristics of the vehicle undergoes a sudden change during the ice-breaking. The head and middle section of the vehicle are subject to greater stress, which is related to the transmission of stress waves and inertial effect. The velocity loss rate of the vehicle and the maximum stress increase with the thickness of ice. The higher the initial velocity of the vehicle, the larger the acceleration and maximum stress in the process of the vehicle breaking ice. The acceleration peak is sensitive to the variation in the vehicle’s initial velocity but insensitive to the thickness of the ice. Full article

To overcome the limitations of traditional image alignment methods in capturing deep semantic features, a deep feature information image alignment network (DFA-Net) is proposed. This network aims to enhance image alignment performance through multi-level feature learning. DFA-Net is based on the deep residual architecture and introduces spatial pyramid pooling to achieve cross-scalar feature fusion, effectively enhancing the feature’s adaptability to scale. A feature enhancement module based on the self-attention mechanism is designed, with key features that exhibit geometric invariance and high discriminative power, achieved through a dynamic weight allocation strategy. This improves the network’s robustness to multimodal image deformation. Experiments on two public datasets, MSRS and RoadScene, show that the method performs well in terms of alignment accuracy, with the RMSE metrics being reduced by 0.661 and 0.473, and the SSIM, MI, and NCC improved by 0.155, 0.163, and 0.211; and 0.108, 0.226, and 0.114, respectively, compared with the benchmark model. The visualization results validate the significant improvement in the features’ visual quality and confirm the method’s advantages in terms of stability and discriminative properties of deep feature extraction. Full article

Circular deep excavations, characterized by their symmetrical geometry, are commonly employed in constructing foundations for large-span suspension bridges and as launching shafts for shield tunneling. However, the mechanical behavior of such excavations under asymmetric surface surcharge remains inadequately understood due to a paucity of relevant investigations. This study addresses this knowledge gap by establishing a three-dimensional finite element model (3D-FEA) based on the anchor deep excavation project of a specific bridge. The model is utilized to investigate the influence of asymmetric surcharge on the forces and deformations within the supporting structure. The results show that both the internal force and displacement cloud diagrams of the support structure exhibit asymmetric characteristics. The distribution of displacement and internal forces has spatial effects, and the maximum values all occur in the areas where asymmetric loads are applied. The maximum values of the displacement, axial force, and shear force of underground continuous walls increase with the increase in the excavation depth. The total displacement curves all show the feature of a “bulging belly”. The maximum displacement is 13.3 mm. The axial force is mainly compression, with a maximum value of −9514 kN/m. The maximum positive and negative values of the shear force are 333 kN/m and −705 kN/m, respectively. The bending moment diagram of different monitoring points shows the characteristics of “bow knot”. The maximum values of the positive bending moment and negative bending moment are 1509.4 kN·m/m and −2394.3 kN·m/m, respectively. The axial force of the ring beam is mainly compression, with a maximum value of −5360 kN, which occurs in ring beams 3, 4, and 5. The displacement cloud diagram of the support structure under symmetrical loads shows symmetrical characteristics. Under different load conditions, the displacement curve of the diaphragm wall shows the characteristics of “bulge belly”. The forms of loads with displacements from largest to smallest at the same position are as follows: asymmetric loads, symmetrical loads, and no loads. These findings provide valuable insights for optimizing the structural design of similar deep excavation projects and contribute to promoting sustainable urban underground development. Full article

Geogrids are frequently utilized in engineering for reinforcement; yet, they are vulnerable to construction damage when employed on coarse-grained soil subgrades. In contrast, waste tire grids are more appropriate for subgrade reinforcement owing to their rough surfaces, integrated steel meshes, robust transverse ribs, extended degradation cycles, and superior durability. Based on the limit equilibrium theory, this study developed formulae for calculating the internal and external frictional resistance, as well as the end resistance of waste tires, to ascertain the interface bearing properties and calculation techniques of waste tire grids. Based on this, a mechanical model for the ultimate pull-out resistance of waste-tire-reinforced soil was developed, and its validity was confirmed through a series of pull-out tests on single-sided strips, double-sided strips, and tire grids. The results indicated that the tensile strength of one side of the strip was approximately 43% of that of both sides, and the rough outer surface of the tire significantly enhanced the tensile performance of the strip; under identical normal stress, the tensile strength of the single-sided tire grid was roughly nine times and four times greater than that of the single-sided and double-sided strips, respectively, and the grid structure exhibited superior anti-deformation capabilities compared to the strip structure. The average discrepancy between the calculated values of the established model and the theoretical values was merely 2.38% (maximum error < 5%). Overall, this research offers technical assistance for ensuring the safety of subgrade design and promoting environmental sustainability in engineering, enabling the effective utilization of waste tire grids in sustainable reinforcement applications. Full article

The accordion honeycomb has unique deformation characteristics in cellular materials. This study develops a three-dimensional equivalent Cauchy continuum model (3D-ECM) based on the variational asymptotic method (VAM) to efficiently predict the mechanical response of the accordion honeycomb. The accuracy of the 3D-ECM is validated via quasi-static compression experiments on 3D-printed specimens and detailed 3D finite element simulations (3D-FEM), showing a strong correlation between simulation and experimental data. Parametric analyses reveal that the re-entrant angle, ligament-to-strut length ratio, and thickness ratios significantly affect the equivalent elastic moduli, providing insights into geometric optimization strategies for targeted mechanical performance. Comparative experiments among honeycomb structures with positive, negative, and zero Poisson’s ratios show that the accordion honeycomb achieves superior dimensional stability and tunable stiffness but exhibits lower energy-absorption efficiency due to discontinuous buckling and recovery processes. Further comparison among different ZPR honeycombs confirms that the accordion design offers the highest equivalent modulus in the re-entrant direction. The findings underscore the accordion honeycomb’s promise in scenarios demanding structural reliability, tunable stiffness, and moderate energy absorption. Full article

UAVs are essential for forest fire detection due to vast forest areas and inaccessibility of high-risk zones, enabling rapid long-range inspection and detailed close-range surveillance. However, aerial photography faces challenges like multi-scale target recognition and complex scenario adaptation (e.g., deformation, occlusion, lighting variations). RGB-Thermal fusion methods integrate visible-light texture and thermal infrared temperature features effectively, but current approaches are constrained by limited datasets and insufficient exploitation of cross-modal complementary information, ignoring cross-level feature interaction. A time-synchronized multi-scene, multi-angle aerial RGB-Thermal dataset (RGBT-3M) with “Smoke–Fire–Person” annotations and modal alignment via the M-RIFT method was constructed as a way to address the problem of data scarcity in wildfire scenarios. Finally, we propose a CP-YOLOv11-MF fusion detection model based on the advanced YOLOv11 framework, which can learn heterogeneous features complementary to each modality in a progressive manner. Experimental validation proves the superiority of our method, with a precision of 92.5%, a recall of 93.5%, a mAP50 of 96.3%, and a mAP50-95 of 62.9%. The model’s RGB-Thermal fusion capability enhances early fire detection, offering a benchmark dataset and methodological advancement for intelligent forest conservation, with implications for AI-driven ecological protection. Full article