Acta Mechanica Solida Sinica最新文献

This study investigates the structural, electronic, vibrational, and mechanical properties of cubic InTe using density functional theory and density functional perturbation theory. The results reveal the metallic character of cubic InTe, as indicated by its electronic structure and density of states. The dynamic stability of the material is confirmed by phonon dispersion analysis, with no imaginary frequencies observed. The Debye temperature (172.276 K) and melting temperature (1092.832 K) suggest excellent thermal resistance. A shear modulus of 18.20 GPa, Poisson’s ratio of 0.343, and Pugh’s ratio ((B/G)) of 2.87 support mechanical stability and indicate ductility. Isotropic dielectric properties, with Born effective charges of −3.768 for both In and Te atoms, highlight potential ferroelectric applications. These findings emphasize InTe’s suitability for electronic and construction applications.

Grinding technology is widely applied in the manufacturing and mechanical processing sectors. Different from conventional three-dimensional rough surface friction models, ground metals exhibit a striated surface morphology, which can be simplified as a two-dimensional plane strain friction issue. Due to surface morphology diversity and loading condition complexity, numerical modeling and experimental approaches have difficulty achieving rapid prediction of line-contact surface friction behavior. Therefore, this study innovatively proposes a hybrid physics-data-driven model integrating finite element analysis (FEA) with machine learning (ML), enabling efficient and accurate prediction of line-contact friction behavior on two-dimensional rough surfaces. An extensive friction behavior database was generated through finite element simulations. Based on this dataset, the random forest (RF) algorithm was used to achieve high-precision prediction of the friction coefficient. Furthermore, a comprehensive analysis was performed on the effects of surface roughness, normal load, yield strength, and local friction coefficient on friction behavior. The RF model exhibits excellent performance in predicting friction coefficients and also accurately identifies the most influential features governing friction behavior. Residual analysis further verifies our model’s reliability, as the RF predictions agree with the FEA results, demonstrating remarkable adaptability and accuracy. Feature importance analysis results reveal that the local friction coefficient and normal load are the main factors influencing friction behavior, but the surface roughness and yield strength exhibit a relatively minor influence. The study innovatively identifies the coupling effects of key parameters through contour maps. Namely, the influence of local friction coefficient decreases with increasing normal load but becomes significantly more pronounced with elevated material yield strength. By integrating ML, our proposed model maintains the high accuracy of FEA while capturing the complexity of interfacial responses through data-driven approaches. Our study advances traditional tribological research from “experience-driven” to “data-intelligence-driven,” thus providing novel insights for understanding and predicting complex friction behaviors, as well as for optimizing frictional design in engineering applications.

To address the challenges associated with multi-sided shells in traditional isogeometric analysis (IGA), this paper introduces a novel isogeometric shell method for trimmed CAD geometries based on toric surfaces and Reissner–Mindlin shell theory. By utilizing toric surface patches, both trimmed and untrimmed elements of the CAD surfaces are represented through a unified geometric framework, ensuring continuity and an accurate geometric description. Toric-Bernstein basis functions are employed to accurately interpolate the geometry and displacement of the trimmed shell. For singularities and corner points on the toric surface, the normal vector is defined as the unit directional vector from the center of curvature to the corresponding control point. Several numerical examples of polygonal shells are presented to evaluate the effectiveness and robustness of the proposed method. This approach significantly simplifies the treatment of trimmed shell IGA and provides a promising solution for simulating complex shell structures with intricate boundaries.

This paper presents a novel surface model based on the Gurtin–Murdoch theory and Kerr-type differential relations, which is established and numerically simulated. By employing the principles of equivalent force and mechanical equilibrium, a differential equation for the contact pressure-deflection relationship between a rigid indenter and an elastic thin beam is derived. The study investigates pressure distribution within the contact area and deformation patterns outside this region. The relationship between indentation parameters is analyzed from two perspectives: clamped and simply-supported boundaries, with a detailed comparison to classical cases. The findings reveal that the normalized contact pressure and load–displacement relationship of elastic thin beams are influenced not only by the half-width ratio and indentation depth but also by the material’s surface elasticity. Similar to classical contact scenarios, an increase in surface elasticity leads to the separation of the indenter from the beam’s center when the contact half-width exceeds a certain threshold (e.g., a ratio of 4 to the beam thickness). This results in a negative normalized contact pressure and the formation of two independent, symmetric contact strips. Notably, the relationship between displacement and contact half-width remains largely unaffected by surface elasticity, aligning with classical indentation contact results. The methodology and outcomes of this research provide a foundation for analyzing the structures and properties of nanostructured materials, offer insights for the design of future nanostructured devices, and present innovative approaches to addressing practical engineering challenges.

In pressurized nuclear power plants, metallic tubes such as steam generator (SG) tubes are subject to complex mechanical and environmental loads that can lead to crack initiation and propagation. Evaluating the structural integrity of SG tubes requires non-destructive assessment of crack size and location. Current inversion schemes can determine crack shape but lack position information, and reconstruction using a single coil has low efficiency. While array probes improve defect detection, reconstruction research based on array signals is challenging due to the complexity of processing multiple sets of signals. This study proposes a simple and effective array reconstruction scheme utilizing signals from two adjacent coils near the crack, enabling simultaneous determination of both crack shape and location through interpolation techniques. Numerical results validate this new crack sizing method, showing accurate reconstruction of both size and location.

Multi-cell structures and corrugated tubes illustrate excellent energy absorption capacities. Besides, bamboo with continuously changing contours demonstrates superior impact-resisting capacities. As a result, a bionic multi-cell double corrugated (BMDC) tube, inspired by Buddha bamboo, is investigated to assess whether it is an ideal energy absorber candidate. Compared to a corrugated tube, a BMDC contains an outer structure, an inner structure, and diaphragms, which are like webs bridging the inner and outer structures. A basic numerical model is correlated using a physical experiment, followed by an investigation of BMDC tubes’ energy absorption performance under axial loading, considering thickness and mass effects. Results indicate that the EA, MCF, and SEA of a BMDC containing 5 diaphragms (BMDC-5) with a 1.5 mm thickness can improve their respective responses by 112.89, 112.89, and 83.32% higher compared to a BMDC with no diaphragm (BMDC-0). In addition, the BMDC-5 with 0.156 kg mass generates the highest EA, MCF, and SEA, which is 79.78% higher than a BMDC-0 with the same mass. The parametric analysis illustrates that diaphragms’ amplitude and diameter have a decisive influence on energy absorption characteristics. This study emphasizes that BMDC tubes are innovative and practical, possessing excellent energy absorption performance.

The advantages of guided wave detection, such as its ability to propagate over long distances and penetrate deeply, have led to its application in the field of anisotropic damage detection in carbon fiber-reinforced polymer (CFRP). Due to the anisotropy of CFRP, traditional guided wave-based detection methods have difficulty in precisely locating the defect. In this study, we proposed a novel deep learning-based detection method for CFRP by employing image recognition technology for guided wave field inspection. This method is capable of rapidly and accurately extracting defective features from the structure, thereby facilitating precise damage identification. To avoid time-consuming sample data generation by simulation for CFRP, the steady-state guided wave field of the aluminum plates was simulated instead. The isotropic wave field data were then stretched and applied for neural network training.

Odd elasticity introduces active moduli to the antisymmetric components of the elastic tensor, which describe the asymmetric coupling between different deformation modes in a medium and quantify the work extracted during quasi-static strain cycles. The introduction of active moduli renders the elastic tensor non-Hermitian, breaking the Maxwell-Betti reciprocity and enabling the observation of phenomena that cannot occur in traditional passive media. Here, we develop an analytical dynamic model for odd elastic circular plates to investigate the effects of odd elasticity on motion in rotationally symmetric geometries. We report a novel nonreciprocal rotating wave and explore the effects of different odd elastic moduli on chiral deformation. Nonreciprocal rotating waves represent a distinct dynamic mode, exhibiting unidirectional propagation with amplitude increasing or decreasing exclusively along a specific direction. The amplitude change during motion reveals the system’s non-conservation of energy.

The Lithium-ion deintercalation induces a significant volume change in battery electrodes during charging and discharging processes, which in turn generates a large diffusion-induced stress (DIS). This stress can cause microstructural damage, consequently degrading battery performance. This work simplifies the particles making up the electrode into spheres and studies the impact of the surface microstructure on the distribution of diffusion-induced stress. A mechanical-chemical coupling model was established to study the DIS in secondary particles, which were constructed by adding convex particles to the ball-shaped particle surfaces of the electrode material. It is observed that an increase in the number of convex particles results in a higher concentration of lithium ions within the electrode material, along with the first principal stresses within the material particles. In addition, the convex particles increase the local stresses around the ball-shaped particle surface. Therefore, a round surface on the electrode material particles is beneficial for preventing potential fractures.