International Journal of Solids and Structures最新文献

The multilevel helical structures in various engineering and natural fields offer excellent deformation flexibility and load bearing capabilities. Understanding the interplay between the local frictional contact and the geometric characteristics of the helical structure under complex external loads has attracted considerable interest. In this work, the effect of local frictional contact behaviors on the bending in multilevel helical structures is investigated by using a combination of theoretical modeling, finite element (FE) simulations, and experiments. In the case of pure bending, the kinematic parameters of the bent multi-stage helix are derived concisely by the idea of the kinematic analogy. The bending stiffness of the multi-stage helix is further obtained. In the case of the combined tension/torsion and bending, the 3D thin rod model incorporating Coulomb’s friction is established to describe the mechanical responses. It is found that the relationship between equivalent bending stiffness and the laying angle exhibits nonlinearity. A comparison with the classical Papailiou model reveals that, for helical structures at large laying angles, the influence of friction is primarily determined by the internal force in the tangential direction, which is the core assumption of the Papailiou model. However, in the case of small laying angles, the helical twisting characteristics and the contribution of the internal forces and moments in the other two directions (normal and binormal directions) to the friction cannot be ignored. Subsequently, a multilevel frictional contact transmission formulation is proposed according to the force action–reaction principle. Based on the above formulation, the non-simplified thin rod equations with Coulomb’s friction are extended to describe the multilevel stick-slip bending behaviors of the second stage cable (3*3). The dissipation capacity of helical structures is evaluated quantitatively under the hysteretic bending. Finally, the theoretical model is verified by FE simulations and experimental results. This work provides insights for unveiling the intrinsic relationship between the nonlinear bending and local frictional contact behaviors in the multilevel helical structures.

Biodegradable polymer-based stents simultaneously provide scaffolding, drug release, and biodegradation to eliminate chronic inflammation. The most important factors hindering the wide use of these stents are thick struts, low radial strength, and large footprints formed on the inner wall of the artery as a result of stent expansion. Negative Poisson’s Ratio (NPR), also known as the Auxetic design, has shown great potential to provide radial strength with less strut thickness. However, a detailed mechanical evaluation proving improvement in stent performance parameters is not available in the literature. In this study, the performance parameters of two stent designs based on the Auxetic geometry with PLLA were analyzed under in-vivo conditions using an in-silico model consisting of the artery, crimper, and expander FE model. For this purpose, one design utilizes Auxetic unit cell, which is already available in the literature, while the other uses a newly proposed Hybrid design combining Auxetic and Chevron type geometries. Additionally, a specially heated coaxial balloon-catheter system was considered as a deployment tool between glass transition and body temperature, and carried out for thin-strut stent simulations. The Hybrid design is shown to resolve the foreshortening problem of Auxetic design and collapse pressure of commercial PLLA stents. In this present study validates the potential of Hybrid design to overcome problems for polymer-based biodegradable stents.

Elastomeric solid materials typically exhibit a pronounced viscoelastic response. In this paper we consider a large deformation viscoelasticity theory for isotropic elastomeric materials which uses a multi-branch multiplicative decomposition of the deformation gradient. We then describe the numerical implementation of the theory in the open-source finite element program FEniCSx. Several example simulations which demonstrate the capability of the theory and its numerical implementation to model stress-relaxation, creep, stretch-rate sensitivity, hysteresis, damped inertial oscillations, and dynamic column buckling are shown. The source codes for these simulations are provided. The theory and the codes presented in this paper lay the foundation for future extensions of the theory and its numerical implementation to include the effects of coupling with thermal, electrical, and magnetic fields — extensions which are of central importance in modeling the response of soft-active materials.

This study aims to investigate the influence of the roller dies’ characteristics of shapes on the forming results in the roller-based flexible multi-point three-dimensional stretch bending forming (FSBRD) process for thin-walled profiles, as well as the prediction of mold-induced impressions during the FSBRD process. Considering the specific contact mode, an L-shaped section profile’s flange was selected as the research object to analyze the impact of the roller dies’ slot’s geometric parameters on the product. A classification model of the contact between the profile’s flange and the roller die was established for the vertical bending process, and the maximum theoretical interference value (i_max) was calculated to predict the extent of local deformation after contact. Subsequently, finite element software was used to model the process and analyze the changes in equivalent plastic strain (PEEQ) of the deformation results when using roller dies with slots of different parameters, including straight, inclined, and arc-shaped slots. The analysis results indicate that the width of the straight slot has a significant influence on the forming quality of the product, as a smaller slot width leads to larger local dimples on the product surface. Replacing the straight slot with an inclined or arc-shaped slot improves the abrupt changes in local PEEQ, resulting in reduced macroscopic local dimples. The simulation results align with the analytical model’s variation of i_max. This study defined the theoretical contact angle γ and introduced the concept of the contact area and the local theoretical interference zone, providing a reasonable explanation for the observed PEEQ variations. Furthermore, based on the conclusions of the research above, modified experiments were designed, resulting in favorable forming effects. The validation of the simulation results was performed by comparing the local dimples in the contact zone of the actual experimental results.

The quantification of uncertainties in the mechanical response of composite structures can be a computationally demanding task. This is due both to the number of uncertain parameters in a real study case and the complexity of the model to be analysed. In this paper, an efficient global/local approach to estimate the uncertainties of the quantities of interest in specific regions of interest with limited computational effort is proposed. This is achieved by refining only locally the model taking advantage of Refined Structural Theories. At the same time, since the variance of the uncertain parameters is usually relatively small, the stochastic analysis is dealt with a sensitivity study carried out both in the global and in the local model. In this way, it is possible to assess the influence of global and local uncertain parameters in the same submodeling analysis. The methodology presented is applied to several study cases of interest. The results focus on obtaining probabilistic distributions of the stress field that can be later used in failure criteria to evaluate the subsequent distribution of the failure index. Furthermore, a damage tolerance study case is investigated, showing good correlation with the reference Monte Carlo simulations.

The numerical simulation of sheet metal forming processes depends on the accuracy of the constitutive model used to represent the mechanical behaviour of the materials. The formulation of these constitutive models, as well as their calibration process, has been an ongoing subject of research. In recent years, there has been a special focus on the application of data-driven techniques, namely Machine Learning, to address some of the difficulties of constitutive modelling. This review explores different methodologies for the application of Machine Learning algorithms to sheet metal constitutive modelling. These methodologies include the use of machine learning algorithms in the identification of constitutive model parameters and the replacement of the constitutive model by a metamodel created by a machine learning algorithm. A discussion about the merits and limitations of the different methodologies is presented, as well as the identification of some possible gaps in the literature that represent opportunities for future research.

The performance and reliability of many structures and components depend on the integrity of interfaces between dissimilar materials. Interfacial toughness Γ is the key material parameter that characterizes resistance to interfacial crack growth, and Γ is known to depend on many factors including temperature. For example, previous work showed that the toughness of an epoxy/aluminum interface decreased 40 % as the test temperature was increased from −60 °C to room temperature (RT). Interfacial integrity at elevated temperatures is of considerable practical importance. Recent measurements show that instead of continuing to decrease with increasing temperature, Γ increases when test temperature is above RT. Cohesive zone finite element calculations of an adhesively bonded, asymmetric double cantilever beam specimen of the type used to measure Γ suggest that this increase in toughness may be a result of R-curve behavior generated by plasticity-enhanced toughening during stable subcritical crack growth with interfacial toughness defined as the critical steady-state limit value. In these calculations, which used an elastic-perfectly plastic epoxy model with a temperature-dependent yield strength, the plasticity-enhanced increase in Γ above its intrinsic value Γ_o depended on the ratio of interfacial strength σ* to the yield strength σ_yb of the bond material. There is a nonlinear relationship between Γ/Γ_o and σ*/σ_yb with the value Γ/Γ_o increasing rapidly above a threshold value of σ*/σ_yb. The predicted increase in toughness can be significant. For example, there is nearly a factor of two predicted increase in Γ/Γ_o during micrometer-scale crack-growth when σ*/σ_yb = 2 (a reasonable choice for σ*/σ_yb). Furthermore, contrary to other reported results, plasticity-enhanced toughening can occur prior to crack advance as the cohesive zone forms and the peak stress at the tip of the original crack tip translates to the tip of the fully formed cohesive zone. These results suggest that plasticity-enhanced toughening should be considered when modeling interfaces at elevated temperatures.

The prediction of creep behavior plays a critical role in the design of thermoplastic materials intended for prolonged use. The creep modulus, which describes the relationship between stress and strain that a material experiences over time, is a key property to determine the long-term thermo-mechanical performance of thermoplastics. Due to the time-consuming and resource-intensive nature of testing for this property, the present work investigates the potential of data-driven techniques as an alternative approach. To accomplish this, a dataset comprising more than 400 distinct thermoplastic grades was obtained from CAMPUS® online open database. Then, various interpretable machine learning models (linear regression, decision trees, random forests, XGBoost, and LightGBM) were evaluated to predict the long-term creep modulus with data from brief tests. To accurately assess the models’ ability to generalize to new data, rigorous model evaluation techniques such as cross-validation and group-splitting were employed, showing that various algorithms can predict the creep modulus with $R^{\text{2}}$ scores above 0.99. Interestingly, linear regression not only matches but, in some cases, also surpasses the performance of more complex models, while being the most simple and interpretable. The present work demonstrates that machine learning can bypass the most lengthy creep tests; reducing costs, energy consumption, material waste, and product development time.

The work focuses on the numerical investigation of compressive mechanical behaviors and energy absorption properties of high entropy alloys (HEAs) with stochastic bicontinuous nanostructures (SBNs) and octet nanostructures (ONs). The study reveals a strong correlation between mechanical behaviors and the relative density of the nanostructures. The findings show that for both ONs and SBNs, the plateau stress increases with increasing the relative density, while an opposite trend is observed for densification strain. The maximum energy absorption capacity is achieved for ONs and SBNs at a relative density 0.6. Additionally, the energy absorption capacity of ONs is higher than that of SBNs across all relative densities, attributed to the higher plateau stress in ONs compared to SBNs. The distinction in mechanical characteristics is further explored by considering the dislocation evolution in ONs and SBNs. The study shows in SBNs that the dislocation increases rapidly, leading to a significant release of stored elastic energy and low plateau stress. Conversely, in ONs, the dislocation increases monotonically, allowing for a gradual release of stored elastic energy and maintenance of high plateau stress. Furthermore, the evolution of atomic configurations demonstrates that intrinsic and extrinsic stacking faults dominate planar defects in ONs, while several types of planar defects play a role in SBNs, including intrinsic stacking fault, extrinsic stacking fault, twin boundary, and hexagonal close-packed laths. The study also shows the effect of temperature on the energy absorption capacity.

The Maugis analysis is applied to adhesive contact between a cylinder with various wave profiles and a semi-infinite, elastic half-plane. We extend the analysis of Waters, Lee and Guduru, who consider the adhesive contact of a Hertzian indenter on a semi-infinite, elastic half-space with axi-symmetric, wave profiles. This work gives the closed-form contact mechanical solution for continuous, line contact without the need for any approximation. The resulting semi-analytical model serves to complement existing (numerical) models of adhesive line contact with the static load-area response as a reference. Herewith we analyse adhesion-induced loading-unloading hysteresis and contrast semi-analytical and numerical result to assess the limit of the former analysis. We confirm that roughness-induced dissipation vanishes with increasing wave roughness and decreasing Maugis parameter due to an increase in the range of adhesion and cavitation. Instability and cavitation are mutually exclusive at a given load-area locus yet occur successively in the same contact. An interesting result is that the Johnson parameter, that is known to govern the amplification of adhesion in the JKR-limit, bounds the load-area envelope irrespective of Maugis parameter. However, the Johnson parameter does not control the occurrence of roughness-induced dissipation and thus interface toughening.