International Journal of Mechanics and Materials in Design最新文献

Engineering cementitious composites (ECC) are widely used in concrete structures for resisting impact loads. This paper establishes a peridynamics (PD)-based model for impact crack propagation in ECC, incorporating a failure criterion considering the strain rate effect, to investigate the damage behavior of ECC under impact loading. Firstly, an improved prototype microelastic brittle material (PMB) model considering the strain softening stage is used to model the cementitious matrix of ECC, and the fibers are modeled as one-dimensional rod to establish a PD fully-discrete model of ECC. At the same time, an interface exponential friction attenuation model is introduced. Then, the effectiveness of the model and the PD impact contact algorithm incorporating the strain rate effect was validated through simulations of the four-point bending test on ECC rectangular plates and the drop hammer impact test on plain concrete beams. Finally, the effects of pre-cracks-to-span distance, fiber content, fiber aspect ratio, different strain rate, and impact velocity on the crack propagation and structural deflection of ECC beams under impact loading are investigated.

A novel type of lightweight and high-performance, collinear polymer lattices is presented in which the concept of stayed slender columns is exploited with the aid of material extrusion additive manufacturing (MEX). The stays, preventing lower order buckling, are additively manufactured using the printing strategy bridging. Through conducting experimental test series on representative elements and two-dimensional lattices, it is demonstrated that the 3D printed stayed column lattices exhibit significantly improved compressive strength in comparison with conventional collinear lattices. The potential of introducing deliberate geometric imperfections to affect the structural behaviour is furthermore outlined in the current work.

This study delves into a Bayesian machine learning (ML) framework designed to comprehensively characterize cutting force and residual stress in the micro end milling process across a diverse range of aluminum alloys. The foundation of this investigation rested on acquiring dependable training data through finite element method simulations, encompassing material properties and processing parameters as inputs, while the output targets included residual stress in both the transverse and cutting directions, as well as cutting force divided into feed force and thrust force. The outcomes were remarkable, unveiling high predictive accuracy for both residual stress and cutting force, with a slight advantage in residual stress prediction. Moreover, the study revealed the significant influence of output target values on the weight functions of input parameters, highlighting distinct dependencies between each output target and the corresponding input features. This investigation elucidated that predicting residual stress and cutting force in micro end milling represents a multifaceted process contingent upon the interplay of material properties and processing parameters. The intricate nature of this process underscores the Bayesian ML model’s potential as a robust and highly accurate approach, adept at effectively encapsulating these complex objectives.

Spinodoid topologies are bicontinuous porous microstructures inspired by the natural spinodal decomposition process. They offer a vast design space and are capable of representing anisotropic topologies, which makes them suitable for use in biomedical applications. This work focuses on some fundamental aspects in spinodoid microstructures. As the first, the extent of anisotropy is computed by a universal index and its correlation with spinodoid design parameters, including relative density and the three cone angles, is investigated. In order to do this, the k-means clustering method is utilized to group the topologies based on their level of anisotropy. Within each cluster, the relationship between the statistical features of the design parameters and the extent of anisotropy is analyzed in detail. As one of the findings, it is revealed that topologies created by larger cone angles will lie in low anisotropy category. Although the sensitivity analysis indicates that all the cone angles are equally important in determining the elasticity tensor elements, our findings demonstrate that there are some discrepancies in the probability density function of cone angles in topologies with high anisotropy. In addition, the results show that lower relative densities tend to lead to higher anisotropy in the structures regardless of cone angle values. In the second stage of this work, a data-driven framework for inverse design is proposed. This approach involves generating high-quality samples and utilizing an efficient data-driven framework capable of handling unequal queries. It can identify multiple spinodoid candidates for a desired elasticity tensor, rather than just one. This approach has great advantages, especially in manufacturing, where different topologies may have varying manufacturing costs. This provides designers with more choices to select from. In the final stage, we estimated the statistical distribution of the elasticity tensor components for the generated spinodoid topologies. By measuring the Mahalanobis distance between a query and the estimated distribution, one can determine whether the query belongs to the property space of spinodoid topologies or not. This approach allows for assessing the similarity or dissimilarity of a query to the distribution of the generated spinodoid topologies.

This paper presents the quasi-static free inversion behavior of a new conical tube absorber. The absorber is composed of a multi-component conical tube with a spherical end cap and varying lengths and diameters. When this structure undergoes an axial load, each tube component freely inverts inside the next component like a telescope. Finite element (FE) models were made using ABAQUS explicit code to simulate the deformation and energy absorption of multi-component conical tubes. To verify the accuracy of the FE models, they were validated with experimental tests. As a general framework for a design optimization study, structural parameters such as wall thickness, cap radius, and edge length of the absorber affect the initial peak load and specific energy absorption. To achieve the optimal design for the multi-component conical tube, mathematical models were developed using the response surface method, and the multi-objective optimization procedure was applied to find the optimal values for the design variables. The results of the multi-objective optimization demonstrated improvements in both objective functions compared to existing designs. Specifically, by increasing the cap radius and decreasing the edge length, the initial peak load was reduced, while increasing the wall thickness the specific energy absorption was enhanced.

Vibration characteristics for rotating thin shallow shell blades reinforced with functionally graded graphene platelets (FGGP) under the axial force are conducted. The blade is modeled as four twisted cantilever thin shallow shells, each with a unique shape cylindrical shallow shell panel with a straight or curved boundary as the cantilever side, spherical shallow shell panel and hyperbolic parabolic shallow shell panel. The Halpin–Tsai model, the first-order shear deformation theory and the Rayleigh–Ritz method are used to calculate the frequencies and mode shapes of the blade. The results are validated by comparing them with previous literature and ANSYS. An analysis is conducted on a range of parameters, encompassing graphene properties, rotational velocity, torsional angle, curvature radius, aspect ratio and axial forces, in order to assess their influence on the vibrational properties of the blade. The vibration behaviors of a rotating cylindrical shallow shell panel with a straight cantilever edge are found to be distinctive. The findings indicate that the blade’s stiffness is significantly higher when reinforced with FGGP-X compared to FGGP-U distribution, with FGGP-O distribution exhibiting the lowest stiffness. Furthermore, the study implies that a total layer count exceeding ten has a negligible impact on the degree of graphene distribution. Finally, the study concludes that the curvature and graphene distribution pattern significantly influence the vibration characteristics of the blade.

Due to their superior biocompatibility, flexibility and control strategy compared to the traditional robots, soft robots have been widely used in a wide spectrum of engineering areas, such as biomedical, exploration, aerospace, intelligent devices and other fields. However, the existing soft robot structures mainly focus on employing homogeneous materials, which greatly limits the design flexibilities of soft robots, and correspondingly, the existing theories are usually invalid for calculating heterogeneous large deformation beam models. Therefore, we developed a novel simulation method and an advanced theoretical calculation method for representing the large deformation of both the homogeneous and heterogeneous beams made of magneto-responsive materials prepared by mixing silicon rubber with NdFeB particles. We found the experimental and numerical results agree very well, showing that the heterogeneous beam can demonstrate a better driving performance than the homogeneous beam. Optimal parameters are afterwards obtained based on the developed simulation and theorical methods. Next, we generalize the optimized heterogeneous structure to engineer the flexible gripper and the soft robot. The grasping forces of the gripper are calculated based on the variational model of large deformation beams, which are consistent with the simulation and experimental values. Moreover, the motion mechanism of magnetic soft robot has been revealed through comprehensive force analysis and formulaic rigid body motion analysis. These findings have strengthened our understandings on the deformation of slender structures and the locomotion of magnetic soft robot, which are promising to guide the design and analysis of innovative devices and robots.

This article explores the waveguide phenomenon that possesses trifurcated rigid inlet/outlet and muffler conditions. Additionally, this waveguide is linked to a finite, thin, and flexible shell with the aid of partitioning discs located at the interfaces. The inside of the discs is coated with sound absorbent material, which can be fibrous or perforated, depending on the impedance conditions of the surface. To demonstrate the use of absorbent material at the interfaces, impedance formulation is used. The mode matching procedure is then utilized to find solution, it relies on the orthogonality conditions accompanying the material characteristics of the bounding surface and within the fluid. The study includes modeling the utilization of absorbent material at interfaces, and numerical experiments to analyze the acoustic attenuation. The analysis focuses on a specific configuration with duct region radii and a half length of the chamber at a frequency of 700 Hz. The results demonstrate that the absorption of power and transmission loss versus frequency vary through the fibrous coating and the edge conditions, and changing the clamped ends to pin-jointed ends optimizes the dispersion powers and the loss due to transmission. The study yields useful information to the acoustic dispersion via flexural expansion chamber, highlighting the importance of material properties, edge conditions, and configuration settings in the acoustic attenuation. The mode matching method and numerical experiments presented in this study can be useful for designing acoustic devices with flexible shells, providing a better understanding of the underlying physics and optimizing their performance.

Composite materials offer the unique advantage of allowing customization of their properties based on their load. However, the optimization of composite laminate properties can often be challenging, often leading to quasi-isotropic designs or the use of industry guidelines. This paper presents a novel method for optimizing of a composite cylinder under axial compression. It introduces an innovative approach by merging a tailored differential evolution algorithm with a deep neural network. The key modification is in the method of constraint implementation. The initial population and trial vectors are constrained to balanced laminates using a while loop, effectively shrinking the design space and reducing computational requirements. The advantage of the customization is reflected in the faster convergence of the optimization as well as a much more accurate deep neural network model. It also enabled the differential evolution to escape the local maxima. Using the deep neural network to evaluate candidate solutions, further reduces the computational costs. The technique is validated using linear buckling analysis and applied to design an inter-tank truss structure. The optimization resulted in a drop in the mass of the truss structure from 5.28 to 4.87 kg. The study establishes a general optimization method applicable to various composite cylinders, including short and long, thin and thick cylinders, and honeycomb core sandwiched composite structures.

This study presents a novel and efficient approach for analyzing the nonlinear behavior of nanoscale plates composed of functionally graded (FG) piezoelectric porous materials. Our approach, which focuses on small-scale structures, demonstrates remarkable efficiency and represents the first of its kind. A generalized model for FG piezoelectric nanoplates with porosities satisfies assumptions of the nonlocal Eringen’s theory based on von Kármán strains. The porous distributions are modeled with even and uneven functions. According to Maxwell’s equations, an electric field is approximated by trigonometric and linear functions. A weak form of the piezoelectric nanoplate with porosity is derived via the principle of extended virtual displacement. Isogeometric approach, which provides accurate results, is easy to implement. The influence of porosity coefficient, small-scale parameter, power law exponent, external electrical voltage and geometric parameter on the nonlinear displacement of the piezoelectric porous nanoplate are examined. These results can provide benchmark solutions for the future numerical investigations of electroelastic nanoplates.