The main purpose of this work is to develop a three-dimensional (3D) viscoelastic rod model for hard-magnetic soft (HMS) rods under large deformation which are widely used active structures in soft robotics. To do so, the Simo’s viscoelasticity theory has been rationally incorporated into the geometrically exact 3D curved rod model. The proposed model includes the deformation modes of axial tension, shear, bending, and torsion, which is applicable to the HMS rods with arbitrarily initial curved and twisted geometries under 3D large deformation. The viscoelastic constitutive equations of the HMS rod in the present formulation are formulated, which include the general relaxation functions. To obtain the expression for the magnetic load, the rotation-based magnetic free energy density is introduced, and the governing equations of the HMS rod with magnetic load and body force are presented. To obtain the numerical implementation, an implicit time integration algorithm that simply extends the generalized-α method for the rotation group, and the corresponding variational formulation and its linearization of the rod model are derived. To validate the model, five numerical examples, including 2D dynamic buckling, 3D static, and 3D dynamic problem are presented. The dynamic problems include the dynamic snap-through behavior of a bistable HMS arch and damped oscillation of a quarter arc cantilever under 3D deformation. The simulation results show good agreement with the results reported in the literature.

In this study, lightning strike damage of woven carbon fibre-reinforced polymer laminates (W-CFRPs) and woven composite honeycomb sandwich panels (W-CHSPs) are simulated using the proposed sequential thermal-electrical–mechanical finite element (FE) coupling model incorporating dielectric breakdown of materials. Surface current with an amplitude of 200 kA and corresponding lightning shockwave overpressure were applied on each composite. The FE model coupled with LaRC05 criterion was used to study the failure behaviours of intralaminar damage and interlaminar delamination of the W-CFRPs and W-CHSPs. A series of lightning strike tests were performed to validate the FE model. Detailed lightning damage assessments and mechanisms were characterized by a combination of visual inspection, image processing, ultrasonic scanning and micro computed tomography (Micro-CT) and showed good agreements with the FE-predicted results. It can be concluded that shockwave overpressure significantly impacts lightning-induced damages, thereby supporting the effectiveness of the newly proposed sequential thermal-electrical–mechanical coupling model, which demonstrates improved predictive accuracy.

There has been an increasing interest among the material research community in the pursuit of enhancing the designability of mechanical properties. The existing approaches usually resorted to sophisticated algorithms (such as machine learning) for the reverse design of materials with specific properties. Different from these existing approaches, here we propose a new approach to create lattice metamaterials with continuously controllable mechanical properties by continuously adjusting the geometric parameters of a unique cell topology originated from the projection of four-dimensional hypercubes. The cells contain an inner region and an outer region, each with different deformation characteristics. For example, the inner region is a stretching-dominated simple cubic (SC) unit cell, while the outer region is a bending-dominated body-centered cubic (BCC) unit cell. Specifically, both stiffness and strength isotropy can be simultaneously realized. The proposed lattice metamaterial exhibits intriguing feature of dual stress plateaus. These plateaus can be effectively controlled by adjusting the geometric parameters of inner and outer regions, which enables these lattice metamaterials to hold promising application prospects in the energy absorption scenarios, such as vehicle and pedestrian protection. Such lattice metamaterial design can be used to realize the gradient distribution of mechanical properties through continuous transition of cell topology without introduction of inefficient interfaces, providing a new approach for the design of heterogeneous metamaterials used in the scenarios involving non-uniform stress distribution.

Under cyclic loads, superelastic shape memory alloys (SMAs) exhibit stress–strain responses featured by functional fatigue, i.e., degradation of superelasticity and accumulation of irrecoverable deformation as cycling number increases, together with an asymmetry between tensile and compressive responses. Comprehensive understanding and modeling of these material complexities are crucial for the design and analysis of various superelastic SMA structures in practical applications. This work has developed a novel constitutive model based on irreversible thermodynamics to account for functional fatigue with tension–compression asymmetry. A potential function, defined as a weighted sum of two potentials that are calibrated against the tensile and compressive responses respectively, is employed to generate the asymmetric responses, and functional fatigue is represented by degradation of superelastic properties and growth of plastic strain as martensitic transformation accumulates. The model is adopted in numerical simulations for superelastic SMA tubes under cyclic lateral compression, which is experimentally investigated as a model problem. The agreement between simulations and experiments shows the validity and effectiveness of this constitutive modeling. Through additional finite element simulations incorporating this model, the effects of tension–compression asymmetry under cycling and diameter-to-thickness ratio of the tubular geometry upon mechanical responses of laterally compressed SMA tubes are also unveiled.

In this paper, a series of enhanced physics-informed neural networks (PINN) models without labeled data is proposed to solve the weakly and fully coupled thermomechanical problems. In these models, to better predict the thermal and mechanical responses, PINNs consisting of different deep neural networks (DNN) representing temperature, displacement, and stress are specifically constructed. Furthermore, to elevate the accuracy and avoid possible training failure, several advanced algorithms are developed to ensure the effectiveness of imposing boundary conditions, refining sampling distributions, and enhancing training strategy. A notable aspect of the enhanced PINNs is their independence from expensive, labeled data, relying solely on the temporal and spatial information embedded within the sampling points. The effectiveness and accuracy of the enhanced PINNs are validated through extensive numerical examples, including heat conduction and both weakly and fully coupled thermomechanical problems. The comparation between original PINN and enhanced PINN illustrates the necessity of involving these enhanced methods. The results demonstrate the significant potential of PINN methodologies in engineering areas involving complex thermomechanical processes.

Renewable and degradable polymers have emerged in everyday applications ranging from mundane eating utensils to high-tech medical devices. However, the current literature lacks a thorough experimental characterization of the mechanical behavior change due to degradation. In this work, we characterize the microscopic chemical changes due to photo-degradation and resulting stress effects on the mechanical behavior of cellulose acetate, a renewable and degradable polymer that is used in various consumer products. Specifically, we photo-degrade this polymer under (i) traction-free conditions and (ii) under applied stress. A key finding of this work is that upon photo-degradation, this material undergoes chain scission, which affects its mechanical properties and may be further affected by the applied stress.

Digital image correlation (DIC) is an increasingly popular and effective non-contact method for measuring full-field displacements and strains of deformable bodies under load. Current DIC methods applied to bodies undergoing large displacements and rotations require a large measurement area for both the reference (i.e., undeformed) image and the deformed images. This can limit the resulting resolution of the displacement and strain fields. To address this issue, we propose a two-stage dynamic DIC method capable of measuring displacements and strains under material convection with high resolution. During the first stage, the reference image is assembled from smaller, high-resolution images of the undeformed object obtained using a spatially-fixed or moving frame. Following capture, each sub-image is rigidly translated and rotated into its appropriate place, thereby producing a full, high-resolution image of the reference body. In stage two, images of the loaded and deformed body, again obtained using a small camera frame with high resolution, are aligned with matching regions of the undeformed composite image using BRISK feature detection before performing DIC. We demonstrate the method on a contact problem whereby an elastomeric roller travels along a rigid surface. In doing so, we obtain fine-resolution measurements of the state of strain of the region of the roller sidewall in contact with the substrate, even as new material convects through the region of interest. We present these measurements as a series of images and videos capturing strain evolution as the roller transitions from static loads to a fully dynamic steady-state, documenting the effectiveness of the method.

The fragmentation-reconstitution (FR) metamaterial has recently been shown to be a suitable candidate for producing Poisson’s ratio discontinuity at the original state. A new FR metamaterial is introduced herein that additionally permits sign-switching of Poisson’s ratio upon stress reversal along one axis. This was achieved by the use of rotating rhombi in which every rhombus can be further fragmented into six sub-units. The latter consists of two non-rotating smaller rhombi and four rotating isosceles triangles. While results show that the metamaterial exhibits sign-switching of Poisson’s ratio upon stress reversal along one axis due to differing mechanism, this is not so for loading in then other on-axis direction due to the dimension being maximum in that direction. Instead, there are two compression pathways which can lead to either fragmentation or reconstitution modes of deformation. The predisposition for each pathway is proposed by means of charge attachments. The uniqueness of this metamaterial avails its use for applications that are not attainable by other materials and metamaterials.

The paper explores the stability of a tower obtained by stacking identical rectangular blocks on top of each other with an inherent randomness due to slight positional offsets between successive blocks. With probabilistic modeling techniques, the diffusive behavior of the stacking process is studied and the collapse is seen as a first passage time problem. In the considered model, alignment errors are idealized as independent Gaussian random variables with zero mean and given standard deviation. We derive expressions for the joint probability density functions of block positions, and analyze their correlation. The study extends to the stochastic stability of a stack of given height, by exploring the statistical characteristics of the center of gravity of the part of tower above each block. Eventually, the probabilistic analysis of collapse is developed to quantify the statistics of the number of blocks that can be heaped up before the tower topples. Although this problem may initially appear playful, it offers an illustrated introduction to first passage problems on a non homogenous process. From a practical standpoint, this analysis offers a simple understanding of the influence of alignment errors on the overall stability of a stack, which may find several fields of application.

The performance enhancement of functionally graded thermoelectric (FGTE) devices is significantly influenced by contact studies of the FGTE materials. It is unclear how the finite thickness and the punch geometry influence the FGTE materials’ contact behaviors. This paper investigates the frictionless contact problem between three types of rigid punches (flat, triangular, and cylindrical) and the FGTE strip with finite thickness. The electric-thermo-elastic parameters of the FGTE strip vary in the thickness direction according to an exponential function. Based on the Fourier integral transform and the transformation matrix method, the problem is transformed into the numerical solution of three sets of singular integral equations. The presence of singular features on either side of the punch demands the adoption of specific collocation strategies. The distribution of the normal current density, the normal energy flux, and the normal contact stress is obtained by adjusting multiple electric-thermo-elastic parameters. The contact stresses in the case of punches with varying shapes can be effectively controlled by modulating the coefficient of thermal expansion and the strip thickness, whereas the effect of the electrical conductivity, the shear modulus, and the thermoelectric load on these stresses depends on whether they are increased or decreased