Artificial muscle is a kind of common soft driver. Among them, the ones actuated by negative pressure have some advantages in comparison with those actuated by positive pressure, such as naturally limited output force and greater safety. This paper has designed a bending contraction rigid-soft hybrid artificial muscle actuated by negative pressure. It consists of elastic contraction units made of TPU and reinforcements made of PLA. It is formed of several contraction units with equal volume through serial connection. Its deformation is affected by geometrical parameters, material properties, actuating pressure, load, etc. This paper has analyzed the contraction theories of the artificial muscle, then has researched the relationship between contraction performance (turning angle of the endplate) and material properties, actuating pressure, and load through simulation. In order to study the effect of material hardness, artificial muscles made of TPU with different hardnesses have been fabricated. In the load experiment, the artificial muscles with different loads are tested for getting the changes law of turning angle and actuating pressure. The results show that the turning angle increases with the increment of actuating pressure and decreases with the increment of load. But the effect of the hardness of the contraction unit can’t be ascertained. Finally, the artificial muscle has been applied to a soft gripper, and has realized several finger cooperation grasping experiments. The gripper can stably grasp a 2.4 kg load, evidently surpassing the one with a similar structure actuated by positive pressure, whose maximum grasping load is 0.786 kg.
Ductile fracture is the primary failure mode in sheet metal stamping, directly affecting material forming limits and product quality. Accurate prediction of ductile fracture is critical for optimizing stamping process parameters, avoiding crack defects and cutting production costs. It also provides reliable theoretical support for the application of lightweight materials like aluminum alloys in complex forming processes. In this study, a machine learning-calibrated DF-2013 uncoupled ductile fracture model was applied to simulate the stamping process numerically. We conducted cup-forming tests and numerical simulations on 5052 aluminum alloy to develop a method for accurately extracting the equivalent fracture strain point. For 5052 aluminum alloy, the equivalent fracture strain should be extracted at the point where load-bearing capacity drops rapidly. At room temperature and a stamping speed of 5 mm/min, the experimental IE value of 5052 aluminum alloy is 7.887 (accompanied by arc-shaped cracks), while the simulated IE value is 8.101—yielding a prediction error of only 2.71%—and the simulated crack morphology is also arc-shaped. This result further verifies that the DF-2013 uncoupled ductile fracture criterion, calibrated via machine learning, is reliable for predicting ductile fracture in sheet metal forming. This calibrated criterion can thus be further used to predict fracture in the stamping of automotive heat shields. Through systematic analysis of stress-strain distribution contours and thickness variation characteristics during stamping, the fracture positions of heat shields were accurately predicted, providing theoretical support for effectively preventing potential stamping defects. Results indicate that stresses, strains, and thickness reduction rates are generally lower on smooth plate surfaces. In contrast, higher stresses, strains, and thickness reduction rates are observed around the protruding edges of the thermal shield and surrounding components. The primary fracture locations in automotive heat shields are concentrated along the protruding edges and around the periphery of the components.
Investigating the influence of cracks on frost-heave-induced damage of water conveyance canal linings in cold regions is pivotal to the assessment and mitigation of frost hazards. Based on the two-parameter elastic foundation beam theory, this study establishes a frost heave mechanical model for canal linings that explicitly accounts for crack effects, and the model accuracy is validated against existing experimental and numerical results. The results indicate that cracks exert a pronounced influence on lining deformation and internal forces. As the crack depth increases from 0 to 8 cm, the maximum frost heave displacement and bending moment exhibit increases of approximately 25% and 17.6%, respectively. Within 0.5 m of the slope crest, the shear force first decreases and then increases with increasing crack depth, accompanied by a reversal in its direction. In the region 1.5–3 m from the slope toe, the shear force increases continuously. For relatively deep cracks, the spatial distribution of frost heave displacement becomes increasingly nonuniform, showing larger values as the crack location shifts toward the slope toe. Meanwhile, a sharp amplification of shear force is observed at the slope toe, accompanied by a substantial increase near the slope crest. Structural responses induced by a single crack are consistently more severe than those associated with a crack band, resulting in higher peak frost heave displacement, bending moment, and shear force. Within a crack band, enlarging the crack spacing leads to a gradual attenuation of these responses, highlighting that a dominant crack governs the frost-heave-induced damage of the concrete lining.
Currently, DED-Arc manufactured components are not covered by design guidelines, and design factors such as residual stress factors are not defined for such components. This hinders industrial use, especially for components with a remaining surface waviness required by industry. For the first time the stress state of a high-strength, low-alloy, large-scale DED-Arc component was characterised in the as-built state and after cutting off the component from the substrate plate. Complementary methods of residual stress analyses were applied to gain a holistic insight into the residual stress distributions of a thick-walled part. In the as-built state, direction-dependent and position-dependent tensile residual stresses were found for the component at the level of the yield strength of the part. The additive manufacturing strategy continuous spiral deposition has no significant influence on the residual stresses in bead threshold area compared to the residual stresses of the remaining component. For this case, bead threshold is no structural imperfection. By removing the part from the substrate plate, the residual stresses are significantly redistributed. Tensile residual stresses are then present at a moderate level. Compressive residual stresses were determined in the volume of the deposited material. The general consideration of “high” tensile residual stresses in such thick-walled components is rather conservative. Therefore, design guidelines should take the manufacturing condition into account.
The adhesion between a rigid substrate and spline-defined elastic punches is investigated with focus on the asymptotic normal stress near the contact edge. Interfacial stress distributions are obtained from automated finite element simulations in Abaqus using Python scripting. Based on these results, a surrogate-based optimization framework is developed in which a narrow feedforward neural network predicts the characteristics of the asymptotic normal stress solution from the punch geometry. The asymptotic normal stress solution allows for the semi-analytical determination of the energy release rate for edge-initiated interfacial defects, which is a primary governing factor of adhesion strength. The optimization aims to minimize the asymptotic normal stress. The results show that the proposed approach accurately captures the highly nonlinear geometry-stress relationship and identifies spline-based punch geometries with improved adhesion performance compared to a straight cylindrical punch. This framework can be used to design new geometries with improved adhesion characteristics. The data and code will be provided in the Supplemental Material for reproducibility and further exploration.
The mechanical behavior of twistless and twisted PET yarns used for tire cord construction has been investigated by means of monotonic and cyclic uniaxial tests conducted at room temperature. Under monotonically increasing strain, the force-strain curves exhibit a characteristic shape, with a change in concavity that appears at strain values below 2% and involves a stiffening behavior for higher strains. A new material model is here developed that includes, in addition to viscosity and plasticity, a nonlinear elastic behavior in the fiber direction aimed at capturing the stiffening behavior. This model is used in numerical simulation accounting for the local anisotropy, defined pointwise by the filament direction, which follows coaxial helices. The material parameters of the proposed constitutive model are identified using the experimental response of monotonic tests on twistless yarns and on a twisted yarn characterized by a specific construction. The model has been subsequently validated by simulating monotonic tests on twisted yarns of different constructions and cyclic tests on twistless and twisted yarns.
The present study uses the Extended Finite Element Method (XFEM) to model and to predict the crack propagation behavior in graphene nanoplatelet reinforced polymer composite (GNPRC) plate. The effective elastic properties of the GNPRC such as elastic modulus and Poisson’s ratio are determined using Modified Halphin-Tsai Model and Rule of mixture, respectively. The numerical framework employs four-noded quadrilateral elements, level set functions for crack tracking. The enrichment function is used to capture both displacement discontinuities and crack tip singularities. Stress intensity factors are calculated using the interaction integral method, and crack growth is modeled based on Paris’ law. The fracture energy and fracture toughness used in the simulations are adopted from experimental data reported in previous studies. An in-house MATLAB code was developed to implement the XFEM framework, and SIF was validated against published results for carbon nanotube reinforced polymer composites. Parametric analyses are performed on edge and center cracked plates under various loading conditions, considering different graphene nanoplatelet weight fractions. It is observed that higher graphene nanoplatelet concentrations improve both fracture energy and toughness, resulting in extended crack propagation paths and enhanced resistance to failure.
This study aims to shed light on a current topic that has not been previously addressed in the literature. This study presents the free vibration of short-fiber-reinforced composite micro columns with variable cross-section, considering the size effect. The composite micro columns are formed by a polymer matrix reinforced with short-fibers. Short-fibers are randomly dispersed throughout the polymer matrix of composite micro columns. The Halpin-Tsai model is used to compute the effective elasticity modulus, and the rule of mixture is used to get the effective mass density. The micro columns’ cross-section shows a linear variation in both the width and height axes. Furthermore, the modified couple stress theory is adopted to study the size effect, a crucial parameter at small scales. The assumptions of Bernoulli-Euler beam theory are considered because micro columns are treated as thin structures. The fundamental vibration frequencies of short-fiber-reinforced tapered micro columns are determined using the Rayleigh-Ritz method. The effects of the following factors on the variation of composite micro columns’ fundamental vibration frequencies with clamped-free and clamped-clamped boundary conditions are examined in detail: the height variation ratio, the material length scale parameter, the width variation ratio, the double taper ratio, the fiber-to-matrix elasticity modulus ratio, the fiber-to-matrix mass density ratio, the fiber volume fraction, and the fiber length-to-diameter ratio.
The torque-tension relationship is fundamental to evaluating the performance of bolted joints. Inaccurate estimation of this relationship can result in insufficient clamping force or excessive tightening, thereby impairing the integrity and reliability of bolted joints. Although numerous analytical models have been developed for conventional threads, their applicability to diverse thread geometries is often restricted by oversimplified assumptions regarding the distribution of bearing contact pressure. In practical applications, the mechanical response of bolted joints is further complicated by frictional variability, evolving contact conditions, and service-induced effects, making accurate preload prediction challenging. Although these factors affect long-term behavior, the torque-tension relationship is primarily established during the tightening stage, where the initial contact conditions govern the subsequent mechanical behavior. To address these limitations, an analytical model is proposed wherein the bearing contact pressure is characterized by a quadratic distribution. This assumption offers a more realistic representation compared with conventional uniform or linear assumptions, while explicitly incorporating its interplay with thread geometry and friction behavior. The model is validated through three-dimensional elastic-plastic finite element analysis and controlled bolt-tightening experiments. Results show that the model achieves prediction accuracies of 98.59% for standard threads and 97.90% for arc-locking self-locking threads, showing good agreement with both numerical and experimental data. The consistent prediction performance across different thread configurations demonstrates the robustness of the quadratic pressure distribution assumption. The proposed model provides a more accurate and practically viable method for predicting the torque-tension behavior of bolted joints.
A numerical approach involves utilizing 3D shell elements in place of solid elements to model microscopic primary yarns within a 2D woven fabric. This innovation draws from the proven efficacy of 3D shell elements in simulating the impact behaviour of extended yarns, leading to notable reductions in computational time through decreased degrees of freedom. The microscopic model, utilizing a simplified equivalent fibre concept, is successfully represented by 3D shell elements, confirmed by validating the method on yarn and fabric impact behaviours up to rupture. Comparative analyses between this and a verified mesoscopic model underscore the superior description of microscopic mechanisms by 3D shell elements. Validation is further strengthened through qualitative comparisons with impact tests on yarns.
Residual stresses, resulting from the complex cyclic bending-unbending strain history in deep drawing, are fundamental to the structural integrity and fatigue life of formed Al6061 components. Accurate characterization of these stresses is often challenging due to the highly non-linear interaction between material anisotropy and evolving contact conditions. This study presents a high-fidelity hybrid framework designed to minimize residual stresses and thickness variations through an integrated Finite Element (FE) and Artificial Neural Network (ANN) approach. Eight governing parameters, including tool geometry, blank holder force, and localized friction coefficients, were investigated. To ensure mechanical rigor, the FE model was grounded in experimental true stress-strain data and the Hill'48 anisotropic yield criterion. Numerical predictions were validated using the semi-destructive hole-drilling method (ASTM E 837-99) and ultrasonic thickness gauging, showing a strong correlation with a maximum discrepancy of 4.5%. A comparative analysis demonstrates that while parametric Response Surface Methodology (RSM) adequately models monotonic responses like punch force (R-2 = 0.89), it fails to resolve the history-dependent nature of residual stress fields (R-2 = 0.72). In contrast, the developed MLP neural network exhibits superior generalization (R = 0.903), effectively mapping the non-linear strain paths. The optimized configuration achieved a peak residual stress reduction to 41.25 MPa. The results establish ANN-driven surrogate modeling as a robust, computationally efficient tool for advanced strain analysis and process optimization in precision sheet metal forming.
This study introduces a finite-element-based modal inversion approach for determining Poisson's ratio directly from impulse excitation of vibration (IET) measurements. Rather than estimating Poisson's ratio indirectly through Young's and shear moduli, or relying on closed-form plate solutions that assume ideal boundary conditions, the method uses the ratio between torsional and flexural resonance frequencies measured on a point-supported square plate. Finite-element eigenfrequency analyses are carried out with explicit representation of wire supports and with transverse shear deformation, rotary inertia, and thickness effects taken into account. These simulations are used to build a calibration map that relates the measured frequency ratio to Poisson's ratio across a broad elastic range, extending into negative values. A Gaussian Process surrogate is then employed to obtain a smooth, strictly monotonic forward relation, which allows stable numerical inversion and provides a basis for uncertainty estimation. Validation experiments on metals, ceramics, and glasses show that the Poisson's ratios obtained using this framework are in close agreement with independent ultrasonic measurements. Notably, the method also captures negative Poisson's ratio behavior in an auxetic metamaterial specimen, with all inferred values falling within the auxetic regime. A closer inspection of the modal strain-energy distributions indicates that the elevated shear-energy contribution of the torsional mode is responsible for the pronounced sensitivity of the frequency ratio to Poisson's ratio. Overall, the results point to a practical, robust, and modulus-independent resonance-based route for evaluating Poisson's ratio in both conventional solids and architected auxetic materials under realistic testing conditions.
Accurate estimation of Mode I stress-intensity factors (SIFs) is essential for evaluating the structural integrity and fracture resistance of thick-walled pressure vessels, where longitudinal semi-elliptical surface cracks often serve as primary failure sites. In this study, the Radial Point Interpolation Method (RPIM), a meshfree numerical technique, is employed to investigate the SIF distribution along the crack front of a thick-walled cylindrical vessel subjected to internal pressure and to develop an empirical correlation for the dimensionless SIF parameter T based on geometric and angular parameters. The displacement field is constructed using multiquadric (MQ) radial basis functions combined with first-order polynomial terms, ensuring smooth and accurate stress gradients without the need for meshing. Parametric analyses were conducted for aspect ratios a/b = 0.4, 0.5, and 0.6 and several crack-depth ratios b/t, with a constant thickness-to-inner-radius ratio (t/r i = 0.25). The MQ parameters were optimized through systematic calibration, yielding alpha = 3.0 and q = 1.03, which reduced the average relative error to below 4% compared with finite element (FEM) simulations and reference data. Validation of the RPIM results against Zheng's numerical data demonstrated excellent agreement and numerical stability across all cases. Furthermore, an empirical correlation was developed to relate the dimensionless parameter T to geometric ratios (b/a, b/t, t/r i ) and the crack-front angle (theta), achieving a determination coefficient of R2 = 0.97, with a maximum error of 12.1% and an average error of 3.3%. These findings confirm that RPIM, enhanced through optimized MQ parameters and empirical correlation modeling, provides an accurate and computationally efficient tool for analyzing fracture behavior in thick-walled pressure vessels.
Dual-phase (DP) steels are widely used in automotive manufacturing due to their superior combination of strength and ductility. To support the development of next-generation advanced steels, a deeper understanding of deformation and damage mechanisms at the microstructural scale is essential. In the present study, crack initiation and propagation in DP1000 steel were evaluated using an in situ scanning electron microscopy (SEM) bending test combined with digital image correlation (DIC). High-resolution microstructural imaging captured during successive deformation stages enabled precise tracking of strain localization and crack evolution. A finite element (FE) model was developed in Abaqus to replicate the in situ bending test, allowing direct comparison of load-displacement responses and calculation of stress triaxiality. The model predicted a maximum plastic equivalent strain of similar to 56% at the specimen notch tip, corresponding to the observed location of crack initiation, while the stress triaxiality along the tensile surface during the bending test was approximately similar to 0.33, indicating a moderately triaxial stress state that promotes void nucleation and crack propagation. Experimental results revealed that cracks initiated within the martensite phase at approximately 5% localized strain and propagated through the ferrite phase along a 45 degrees shear band, reaching a maximum localized strain of 35%. With increasing applied load, the maximum localized strain became progressively concentrated around the crack region and remained confined there until the final deformation stage. This progressive strain intensification led to final fracture within the ferrite phase at a maximum localized strain of 75%. SEM observations confirmed damage initiation along the maximum tensile fiber and subsequent crack growth across the specimen. The combined DIC, SEM, and FEM results demonstrated strong agreement and effectively captured both crack initiation and propagation behavior. Overall, the integrated in situ SEM-DIC approach, reinforced by FEM simulation provide valuable insight into micro-scale deformation and fracture mechanisms of DP steels, supporting to the design and optimization of next-generation automotive structural materials.
Engineering components within a fusion reactor are subjected to extreme environments including high heat flux, strong magnetic fields and neutron irradiation. Simulations are required to predict the in-service lifetimes of fusion components and ensuring credibility of these simulations requires validation over testable domains. Divertors are responsible for extracting heat and ash from the fusion reaction and protecting the vacuum vessel from thermal loads. In this work, we conduct an image-based experimental assessment of a divertor armour component design under a steady-state, high heat flux of similar to 5MW/m(2) under vacuum conditions. The heat flux was applied to the water-cooled component using the Heating by Induction to Verify Extremes (HIVE) facility at the UK Atomic Energy Authority. We used digital image correlation (DIC) to measure the surface strain of the component and thermocouples to measure the temperature during the high heat flux pulse. We used synthetic image deformation simulations to analyse sources of random and systematic errors in our DIC measurements and to select DIC processing parameters for subsequent analysis. Our results show that DIC is a valuable tool for the validation of multi-physics simulations by providing information about the geometrical arrangement of components as well as high resolution data indicating areas of disagreement between the simulation and experiment. The results of our study are the first image-based simulation validation dataset for a divertor component under fusion relevant conditions.
This study investigates the nonlinear dynamic stability and internal resonance of osteon micro-beams under localized thermal gradients. Utilizing Nonlocal Strain Gradient Theory (NSGT), the size-dependent behavior of the Haversian system is modeled to bridge microscopic nuances and macroscopic thermal-mechanical responses. The governing equations are derived and solved via the Method of Multiple Scales (MMS) to determine nonlinear frequency-response characteristics. The results indicate that thermal gradients cause frequency reduction and convergence, while the nonlinear response retains a persistent hardening-type behavior at large amplitudes. A critical highlight is the identification of a 1:3 internal resonance threshold. At specific parametric configurations, the system exhibits sophisticated modal coupling, a 'double-peak' resonance profile, and the saturation phenomenon, indicating nonlinear energy transfer between the fundamental and second modes. Furthermore, 3D coupled parametric maps illustrate a 'stability canyon', highlighting osteon dynamic sensitivity under combined thermal and nonlocal influences. The obtained nonlinear vibration characteristics and internal resonance behavior may provide useful insight into how dynamic loading conditions influence stress redistribution and mechanical response at the osteon scale.
Laminated composites are widely used in lightweight structural systems, and in many practical applications they operate while being supported by compliant media such as soil layers, polymeric cores, or elastic subgrades. In such cases, the plate response is strongly governed by the structure-foundation interaction; moreover, a one-parameter Winkler representation may be insufficient because it neglects shear coupling within the supporting medium, which can be captured by the two-parameter Winkler-Pasternak model. Motivated by this need, the present study develops a mixed finite element formulation for the flexural analysis of laminated composites resting on elastic foundations within the framework of Higher-Order Shear Deformation Theory (HSDT). The formulation is established using the Hellinger-Reissner variational principle, where displacement and stress components are treated as independent variables to improve accuracy and numerical robustness. Both Winkler and Pasternak foundation parameters are consistently incorporated to account for normal and shear interactions with the substrate. The model is validated through benchmark comparisons from the literature using different shear deformation functions, and a parametric study is then performed to quantify the effects of geometric ratios, foundation stiffness parameters, and laminate stacking sequence on displacement and stress responses. The numerical results demonstrate that the proposed mixed HSDT framework provides reliable predictions for laminated composites interacting with elastic foundations.
The keyway is a widely employed solution to link a hub with a shaft. This paper underlines the importance of the fillet radius at the keyway base, highlights the combined effect between bending and torsion and verifies the stress concentration factors present in the literature thanks to Finite Element Method. Starting from a first analytical analysis of the shaft, a series of FE analyses were carried out with the aim of understanding why certain shaft failures occurred. In these analyses, the key presence is considered and the torque is transmitted through it. The analysis reveals that standard verification could fail for some configurations and for the precise evaluation of the fatigue behaviour, for this reason a numerical model is always suggested.
Interference-fit joints are widely used in lightweight and high-speed transmission systems due to their ability to transmit high torque, resist fatigue and maintain compact geometry. However, most prior studies focused on solid shafts and similar materials overlooking the combined influence of torsion, friction and geometry in hollow shaft shrink-fits with dissimilar materials. This limitation restricts their applicability to modern engineering systems. This work presents a generalized analytical model for optimizing shrink-fit joints under torsional loading. Closed-form solutions are derived for the optimal hub and shaft aspect ratios, interference value, contact pressure as well as torque capacity ensuring balanced effective stress in both shaft and hub while minimizing material usage. A main contribution of the model is the identification of threshold conditions: (i) a lower limit of the joint strength factor, below which no feasible solution exists, and (ii) upper and lower bounds for the shaft aspect ratio depending on design scenarios. These thresholds provide clear criteria for determining whether a given material combination and geometry can support the required torque transmission. The results showed that increasing friction will reduce the necessary interference while demanding a thicker hub to withstand shear stresses, whereas the contact pressure remains unaffected and depends only on geometry and material properties. Case studies with steel, aluminum, and brass demonstrated the differences between high-strength homogenous joints and low-strength or dissimilar material pairings, with the latter requiring more significant geometric adjustments. Three-dimensional finite element analysis validated analytical predictions within deviations ranging from 3 % to 10 % . This work provides direct design formulas useful for aerospace and automotive lightweight transmission systems. It provides theoretical understanding and practical tools, including closed-form formulas and design charts for efficient, reliable shrink-fit joint design without iterative simulations.
Shape memory alloys (SMAs) have gained significant attention for their unique thermomechanical properties. This paper presents a phenomenological model for the thermoelastic strain-temperature response of Cu-Zn-Al SMAs. The constitutive equations are derived from thermodynamics, and parameters are calibrated at two constant stresses (65 and 100 MPa) using data for the same alloy from the literature. The simulations reproduce, after calibration, the transformation-strain amplitude and the hysteresis width at each stress. A key observation is that fitted parameters vary with the applied stress, which highlights the model's descriptive capability under specified loading and its limitations as a predictive tool without additional functionalization and data.
