International Journal of Applied Mechanics最新文献

Machine learning has sparked significant interest in the realm of designing mechanical metamaterials. These metamaterials derive their unique properties from microstructures rather than the constituent materials themselves. In this context, we introduce a novel data-driven approach for the design of an orthotropic cellular metamaterials with specific target properties. Our methodology leverages a Bézier curve framework with strategically placed control points. A machine learning model harnesses the positions of these control points to achieve the desired material properties. This process consists of two main steps. Initially, we establish a forward model capable of predicting material properties based on given designs. Then, we construct an inverse model that takes material properties as inputs and produces corresponding design parameters as outputs. Our results demonstrate that the dataset generated using the Bézier curve-based strategy shows a wide range of elastic distributions. Describing the geometry in terms of design parameters, rather than pixel-based figures, enhances the training efficiency of the networks. The dual-network training approach helps avoid contradictions where specific elastic properties may correspond to various geometric designs. We verify the prediction accuracy of the inverse model concerning elastic properties and relative density. The presented approach holds promise for accelerating the design of cellular metamaterials with desired properties.

The application of the discrete element method (DEM) to continuous medium problems is becoming increasingly widespread. In this work, a parallel computing method with multiple time steps based on overlapping particles is proposed. The domain decomposition method (DDM) with overlapping particles method is used to increase the speed up and shorten the computation time and meet the consistency requirements during data transmission. The multi-time-step method (MTSM) is adopted to tackle the matching of asynchronous step boundary. Data are exchanged at the boundaries in each subdomain with a message passing interface (MPI). The computational efficiency of different step ratios in both serial and parallel computing is studied respectively. Numerical examples show that the DEM can effectively handle large structure deformation problems, and provides a shorter calculation time than that of the finite element method (FEM). The DEM with multiple time steps in different subdomains effectively reduces the computation time than that with a single time step in the entire domain. Under fixed step ratio conditions, using parallel computing can save more time than serial computing. This work develops ideas for expanding the application of DEM for large engineering problems.

Contact between solids is a ubiquitous phenomenon in engineering and an enduring topic in tribology. However, material yield plateau and strain hardening are common in ductile metals but rarely considered in contact mechanics. This work develops a three-phase constitutive model that accurately describes the elastic and plastic behaviors considering both yield plateau and strain hardening, and then constructs a finite element model for the contact of a rigid flat and a corresponding elastoplastic hemisphere. The Taguchi method is employed to conduct numerical simulations of material parameters for finding generalized empirical formulations of dimensionless contact load and area versus dimensionless contact interference in the range of ${\omega }^{\ast }\le 120$. The presented empirical formulations demonstrate good accuracy verified with KE, JG, and Ghaednia’s models. This work fills the gap that the yield plateau has not ever been explored in contact mechanics and provides a basic model for describing the contact behavior of engineering rough surfaces for ductile metal.

Seismic inversion is an important part of the modern geological exploration process. Novel applications of deep learning are capable of handling heterogeneous media, but require too much data for training. In this paper, we focus on the prediction of fracture inclusion location and its parameters in rock media and approach the problem in the multi-task manner. For this, several multi-task convolutional neural network (CNN) architectures are proposed and compared. The direct seismic problem is considered in the heterogeneous fractured geological model based on the well-known Marmousi2 model in a two-dimensional case. The model of the deformable solid medium containing slip planes with nonlinear slip conditions on them and explicit–implicit numerical method is applied to obtain the synthetic seismic dataset for CNN training and validation.

Multilayer materials have found extensive application within the aerospace industry due to their notable mechanical attributes. The operational longevity and dependability of such materials are substantially influenced by the performance characteristics of individual layers. In this study, an indentation method was established for employing a weighting function to simultaneously characterize the elastic modulus, hardness and film thickness of tri-layer materials. The results of numerical simulations indicate that incorporating the substrate effect in such an approach allows for precise assessment of the mechanical properties of tri-layer materials with diverse thicknesses. To validate the method, nanoindentation tests were performed using two tri-layer materials (i.e., Al/Cu/304SS and Cu/Al/304SS). Further, according to numerical and experimental data, the proposed model could be reduced to evaluate the mechanical properties of a bilayer material. The present findings demonstrate the effectiveness and applicability of the proposed indentation method in characterizing multilayer materials, facilitating reliable assessment in practical applications.

A semi-analytical solution is provided to obtain the stress intensity factors (SIFs) of hole-edge cracks with different configurations and the stress fields along the crack propagation direction in an infinite isotropic plane. The complicated solution procedure while using the Muskhelishvili method is improved by expanding an irrational mapping function into an approximate rational function so that singular integral equations could be converted to linear equations. The proposed method used to obtain the SIFs of symmetrical cracks emanating from circular or elliptical holes and a single crack emanating from a circular hole is compared with other methods in the literature. The results show that this method is universal and accurate for hole-edge cracks. In addition, the effects of the lengths of the asymmetrical cracks and the ratio of the semi-axes of the elliptical hole ($a$/$b)$ on the SIFs are studied, which have not been previously reported.

A bladed thin-walled rotor with magnetic bearings in gas turbines has minimal wear to improve the service life. Especially, the rotor system can actively suppress vibrations. Yet, thermal–elastic–magnetic coupling-induced rubbing features of a bladed thin-walled rotor with magnetic bearings are not clear, and blade rubbing behaviors induced by high temperatures always occur in this kind of rotor. This paper establishes a new bladed thin-walled rotor model with distributed electromagnetic actuators to reduce thermoelastic vibrations and develops a solution approach for obtaining the thermal–elastic–magnetic coupling-induced rubbing characteristics of the rotor. The solution approach is verified, and the effectiveness of the distributed electromagnetic actuator model is demonstrated. The magnetic supports require two differential-control actuators at each position to generate the electromagnetic force, due to irregular concave–convex deformations of the rotor. Thereafter blade rub behaviors for the thin-walled rotor system are revealed. Uniform and smaller thermal deformations of the rotor system with the present actuator model avoid tip rub due to preventing thermal energy concentration. With the proper bearing capacity of a single actuator, an adequate number of actuators are required to ensure stability. The proposed theoretical prototype of the bladed thin-walled rotor with distributed electromagnetic actuators prevents blade rubbing caused by high temperatures. The provided solution approach can evaluate the vibration characteristics of a rotating thin-walled rotor with magnetic supports in the high-temperature environment.

A customized MATLAB algorithm is developed for internally separated laminated composite panels experiencing large geometric deformations. The algorithm is designed to calculate nonlinear deflection responses under the effect of combined hygro-thermo-mechanical (HTM) loading. The hygrothermal (HT) load on the panel is in-plane, whereas the mechanical load acts upon the structure transversely. The analysis has adopted various kinematic theories and finite element (FE) techniques to determine the deformations computationally. The deflection behavior of the composite is characterized through a macro mechanical model considering the nonlinearity in geometry with and without accounting for the stretching effects across the panel thickness. Additionally, the changes in composite properties due to the environment and/or loadings are adopted to achieve a realistic response, preserving continuity assumptions between the individual layers of the weakly bonded structure. Moreover, various numerical examples are examined through different models to illustrate the influences of environmental factors and design-specific parameters on the flexural strength of weakly bonded structures. The findings strongly emphasize the necessity of employing diverse kinematic models when examining laminated structures, both with and without HT loading, while also acknowledging the potential for debonding.

Application of porous electrode materials has sparked significant interest as a strategy to mitigate traditional electrode mechanical failure arising from its intercalation-induced large volume change. In this work, a thermal analogy method is employed for implementing the coupled chemo-mechanical model into the finite element (FE) package ABAQUS via user subroutines UMATHT and UMAT, which is used to model the lithium (Li) diffusion and the resulting deformation of the electrode during charge-discharge cycling. This work presents a Direct FE² method for modeling the chemo-mechanically coupled behavior of porous electrode materials by establishing the macro-microscopic scale transitions through concentration and displacement DOFs and the representative volume element (RVE) volume scaling relationship. The two-scale numerical simulations can be implemented in a single computational scheme. Within the present computational framework, the Li diffusion and mechanical deformation in the porous silicon electrode during charging and discharging are easily simulated in the typical FE package. Benchmarked against the traditional direct full-field numerical computational method, the Direct FE² method is validated to present significant computational efficiency improvements through two numerical examples, the constrained expansion and the pre-compression expansion of porous electrode, by 99.27% and 94.55%, respectively, while maintaining the high precision.

To study the impact of on/off-ramps on traffic stability in heterogeneous traffic flow, a novel lattice hydrodynamic model was presented. The new model’s stability condition was determined using the linear stability analysis method. The theoretical results reveal that traffic flow stability is influenced by the proportion of vehicles with different maximum speeds and safe headway, as well as the presence of on-ramps and off-ramps to a certain degree. Through the approximate perturbation method, the mKdV equation and the kink–antikink solution of the traffic density at the jam area are obtained. In order to verify the effectiveness and feasibility of the new model, numerical simulations were conducted to demonstrate on/off ramp effect and different proportions of vehicles which possess bigger maximum velocity or safe space headway affect the traffic stability. The numerical results indicate that in heterogeneous traffic flow scenarios, increasing the ratio of vehicles which possess bigger maximum velocity or bigger safe space headway can lead to a deterioration of traffic stability. The effect of on-ramp could cause traffic instability, while the effect of off-ramp is beneficial for easing traffic congestion.