【新文速递】2024年3月3日固体力学SCI期刊最新文章

 

今日更新：International Journal of Solids and Structures 1 篇，Journal of the Mechanics and Physics of Solids 1 篇，International Journal of Plasticity 1 篇，Thin-Walled Structures 2 篇

International Journal of Solids and Structures

Pneumatically tunable adherence of elastomeric soft hollow pillars with non-circular contacts

Guangchao Wan, Wanliang Shan

doi:10.1016/j.ijsolstr.2024.112736

具有非圆形触点的弹性软空心支柱的气动可调附着力

Dynamically tunable interfacial dry adhesion plays a significant role in numerous biological functions and industrial applications. Among various strategies, pneumatics-activated adhesive devices draw much attention due to their distinct advantages such as fast speed, reliable performance, large adhesion tunability and easily accessible materials. To understand and predict adhesion strength of pneumatics-activated adhesives, it is necessary to examine their interfacial mechanics that is nonlinearly coupled with the large deformation of the devices under pressure. However, previous studies have only focused on axisymmetric cases in which the outline of the contact area is circular, whereas the tunable adherence of non-circular contact controlled by pneumatics remains elusive. In this work, through a combination of experiments and simulations, we study the effect of non-circular contact geometry on tunable dry adhesion of pressure-activated soft hollow pillars. Specifically, elliptical, square, and rectangular contact shapes are considered and their effects on tunable adhesion of the soft hollow pillars are compared to that of circular contact geometry thoroughly. The results show that soft hollow pillars with elliptical, square, and rectangular contact surfaces demonstrate rich interfacial delamination behaviors that depend on the contact outline geometry and internal pressure. Among all contact geometries, elliptical contact has the highest adhesion tunability yet requires lowest activating pressure owing to the non-uniform curvature distribution of the contact outline. However, when the eccentricity increases, the elliptical contact has reduced tunability of adhesion caused by the contact of opposing sides of the sidewall upon buckling. For square and rectangular contacts, they have the lowest adhesion tunability and need higher activating pressure than those of circular and elliptical contact since the 90-degree edges of the sidewall prohibit buckling instability. Our findings greatly broaden the design space of pneumatics-activated adhesive devices by adding the contact geometry of the soft hollow pillars as a new design parameter, which can provide valuable guidance to tunable adhesive design for various applications in manufacturing and robotics.

动态可调的界面干附着力在众多生物功能和工业应用中发挥着重要作用。在各种策略中，气动激活粘合剂装置因其速度快、性能可靠、粘合力可调节性大和材料易得等独特优势而备受关注。要了解和预测气动活化粘合剂的粘合强度，有必要研究其界面力学，因为界面力学与设备在压力下的大变形呈非线性耦合。然而，以往的研究只关注接触区域轮廓为圆形的轴对称情况，而由气动控制的非圆形接触的可调粘附性仍然难以捉摸。在这项工作中，我们通过实验和模拟相结合的方法，研究了非圆形接触几何形状对压力激活的软空心支柱的可调干附着力的影响。具体来说，我们考虑了椭圆形、正方形和长方形接触形状，并将它们对软质空心柱可调粘附性的影响与圆形接触几何形状的影响进行了彻底比较。结果表明，具有椭圆形、正方形和矩形接触面的软质空心支柱表现出丰富的界面分层行为，这些行为取决于接触轮廓几何形状和内部压力。在所有接触几何形状中，椭圆形接触具有最高的粘附可调性，但由于接触轮廓的曲率分布不均匀，所需的启动压力也最低。然而，当偏心率增大时，椭圆形触点的粘附可调性会降低，原因是弯曲时侧壁的对立面会发生接触。对于方形和矩形触点，由于侧壁的 90 度边缘阻碍了屈曲不稳定性，因此它们的附着力可调性最低，所需的激活压力也高于圆形和椭圆形触点。我们的发现大大拓宽了气动激活粘合装置的设计空间，增加了软质空心支柱的接触几何形状作为新的设计参数，这将为制造和机器人领域各种应用的可调粘合剂设计提供有价值的指导。

Journal of the Mechanics and Physics of Solids

Exploring static responses, mode transitions, and feasible tunability of Kagome-based flexible mechanical metamaterials

Jian Li, Ronghao Bao, Weiqiu Chen

doi:10.1016/j.jmps.2024.105599

探索基于 Kagome 的柔性机械超材料的静态响应、模式转换和可行的可调谐性

We consider the static responses of the uniaxially compressed flexible mechanical metamaterials, which integrate soft hinges and rigid bodies, constructed from the Kagome lattice. First, we experimentally find that the static responses of the regular-Kagome-based structure significantly differ from those of the twisted-Kagome-based structure with a very small twisting angle. Following this, we establish a theoretical model, which is combined with the deflated continuation algorithm for bifurcation analysis, to delve into the static responses and potential bifurcation behavior of these structures. We then experimentally and numerically investigate the mode transitions between various stable modes, and systematically study the role of the twisting angle in the occurrence of bifurcations. Our findings indicate that mode transitions can be feasibly realized according to the calculated bifurcation diagrams. They also provide direct evidence of a crucial physical mechanism that the transition between different stable deformation states can occur through multiple pathways but must pass through at least one unstable deformation state. Moreover, by introducing the twisting angle or stiff defects, the response of the structure can be modulated, thereby enhancing the programmability and tunability of Kagome-based flexible mechanical metamaterials. Our research also reveals that novel phenomena such as meta-beam buckling and multi-phase dominated deformations can be triggered within these flexible structures, which offers valuable insights for future metamaterial designs and applications.

我们考虑了单轴压缩柔性机械超材料的静态响应，这种超材料将软铰链和刚体结合在一起，由卡戈米晶格构建而成。首先，我们通过实验发现，基于常规卡戈米结构的静态响应与基于扭曲卡戈米结构的极小扭曲角的静态响应存在显著差异。随后，我们建立了一个理论模型，并将其与用于分岔分析的放气延续算法相结合，深入研究了这些结构的静态响应和潜在分岔行为。然后，我们通过实验和数值方法研究了各种稳定模式之间的模式转换，并系统地研究了扭转角在分岔发生中的作用。我们的研究结果表明，根据计算出的分岔图，模式转换是可以实现的。它们还直接证明了一种重要的物理机制，即不同稳定变形状态之间的转换可以通过多种途径发生，但必须至少经过一种不稳定变形状态。此外，通过引入扭转角或刚性缺陷，可以对结构的响应进行调制，从而增强基于 Kagome 的柔性机械超材料的可编程性和可调性。我们的研究还揭示了在这些柔性结构中可以触发元梁屈曲和多相主导变形等新现象，这为未来的超材料设计和应用提供了宝贵的启示。

International Journal of Plasticity

Quantifying Dislocation Drag at High Strain Rates with Laser-Induced Microprojectile Impact

Qi Tang, Mostafa Hassani

doi:10.1016/j.ijplas.2024.103924

利用激光诱导微弹丸冲击量化高应变速率下的位错拖曳力

As deformation rate increases, the thermally activated dislocation glide gives way to a continuous glide of dislocations governed by their interactions with phonons. Understanding the dislocation-phonon drag regime is critical for designing metallic materials for extreme deformations rates. However, it has proven challenging to study empirically, partly due to the resource intensive nature of the experimental approaches targeting this regime. Here, we develop an impression-based experimental approach combining laser-induced microprojectile impact (Hassani et al., 2020a) and spherical nanoindentation to characterize the dislocation-phonon drag regime. We also utilize a physically based constitutive framework that, when integrated our experimental measurements, can quantify the dislocation-phonon drag regime. We isolate the effect of dislocation-phonon drag by leveraging the similar deformation geometries and length scales but different operative mechanisms during spherical nanoindentation and microprojectile impact. We discuss mechanistic contributions to the plastic work for microprojectile impacts in a range of impact velocities producing strain rates up to 109 s−1. We also develop a deformation mechanism map focused on the transition from thermal activation to dislocation drag for a model FCC metal, copper.

随着形变速率的增加，热激活的位错滑行让位于位错与声子相互作用下的连续滑行。了解差排-声子阻力机制对于设计适用于极端变形率的金属材料至关重要。然而，事实证明对其进行经验研究具有挑战性，部分原因是针对该机制的实验方法需要大量资源。在此，我们开发了一种基于压痕的实验方法，结合激光诱导微弹丸冲击（Hassani 等人，2020a）和球形纳米压痕来表征位错-声子阻力机制。我们还利用了一个基于物理的构成框架，该框架与我们的实验测量相结合，可以量化差排-声子阻力机制。我们利用球形纳米压痕和微弹丸冲击过程中相似的变形几何形状和长度尺度以及不同的作用机制，分离出差排-声子阻力的影响。我们讨论了在一系列冲击速度（应变率高达 109 s-1）下微弹丸冲击塑性功的机理贡献。我们还绘制了一张变形机理图，重点关注模型 FCC 金属铜从热激活到位错拖曳的转变过程。

Thin-Walled Structures

Data-Driven PSO-CatBoost Machine Learning Model to Predict the Compressive Strength of CFRP- Confined Circular Concrete Specimens

Nima Khodadadi, Hossein Roghani, Francisco De Caso, El-Sayed M. El-kenawy, Yelena Yesha, Antonio Nanni

doi:10.1016/j.tws.2024.111763

预测 CFRP 承压圆形混凝土试件抗压强度的数据驱动型 PSO-CatBoost 机器学习模型

This work articulates the development of a sophisticated machine-learning model for the prediction of compressive strength in Carbon Fiber-Reinforced Polymer Confined-Concrete (CFRP-CC) specimens. Despite extensive empirical studies conducted over the last three decades, prevailing predictive models predominantly rooted in linear or nonlinear regression analyses are constrained by their dependency on limited data scopes. Addressing this deficiency, our research delineates the formulation of an innovative Particle Swarm Optimization- Categorical Boosting (PSO-CatBoost) algorithm, underpinned by an expansive database encompassing 916 experimental outcomes from 116 scholarly articles, spanning the period from 1991 to mid-2023. This innovative approach effectively combines the strengths of Particle Swarm Optimization and the CatBoost algorithm. It carefully evaluates various vital factors that affect the compressive strength of CFRP-CC. The uniqueness of our approach is further accentuated through the application of SHapley Additive exPlanations (SHAP) and Permutation Feature Importance (PFI) methodologies, thereby elucidating the relative importance of each contributory feature. In an unprecedented comparative analysis, the PSO-CatBoost model is rigorously benchmarked against six contemporary machine learning paradigms: CatBoost, XgBoost, AdaBoost, GBoost, Extra Trees, and Random Forest. Furthermore, this model is assessed against six empirical models for further comparison. The model exhibits superior predictive efficacy, evidenced by an exemplary coefficient of determination R-squared of 0.9847, surpassing the methodologies. This research introduces a new predictive model for CFRP-CC and represents a significant shift in concrete research, moving towards a more sophisticated, data-driven, and machine learning-focused methodology. This work thus establishes a new benchmark in the predictive modeling realm for CFRP-CC compressive strength, offering a robust and comprehensive analytical tool for both researchers and practitioners in the field. Lastly, a graphical user interface was designed for modeling the compressive strength of CFRP-CC to facilitate practical use.

这项工作阐明了如何开发一种复杂的机器学习模型，用于预测碳纤维增强聚合物密实混凝土（CFRP-CC）试样的抗压强度。尽管在过去三十年中进行了大量的实证研究，但主要植根于线性或非线性回归分析的主流预测模型因其对有限数据范围的依赖性而受到限制。针对这一不足，我们的研究阐述了一种创新的粒子群优化-分类提升（PSO-CatBoost）算法，该算法以一个庞大的数据库为基础，该数据库涵盖了从 1991 年到 2023 年中期的 116 篇学术论文中的 916 项实验结果。这一创新方法有效地结合了粒子群优化和 CatBoost 算法的优势。它仔细评估了影响 CFRP-CC 抗压强度的各种重要因素。通过应用 SHapley Additive exPlanations（SHAP）和 Permutation Feature Importance（PFI）方法，进一步突出了我们方法的独特性，从而阐明了每个贡献特征的相对重要性。在前所未有的比较分析中，PSO-CatBoost 模型与六种当代机器学习范式进行了严格的基准比较：CatBoost、XgBoost、AdaBoost、GBoost、Extra Trees 和 Random Forest。此外，该模型还与六个经验模型进行了评估，以作进一步比较。该模型表现出卓越的预测功效，其判定系数 R 方为 0.9847，超越了各种方法，堪称典范。这项研究为 CFRP-CC 引入了一个新的预测模型，代表了混凝土研究领域的重大转变，即向更复杂、数据驱动和以机器学习为重点的方法转变。因此，这项工作在 CFRP-CC 抗压强度预测建模领域建立了一个新的基准，为该领域的研究人员和从业人员提供了一个强大而全面的分析工具。最后，为了便于实际使用，还设计了 CFRP-CC 抗压强度建模的图形用户界面。

Enhancing bond performance of CFRP-steel epoxy-bonded interface by electrospun nanofiber veils

Furui Zhu, Lu Ke, Zheng Feng, Jiale Zhou, Chuanxi Li, Rundan Zhang

doi:10.1016/j.tws.2024.111765

利用电纺纳米纤维纱提高 CFRP-钢环氧树脂粘结界面的粘结性能

The epoxy-bonded interfaces between carbon fiber reinforced polymer (CFRP) and steel usually have insufficient strength and toughness, and the toughening of bonded interface is a key problem for the usage of CFRP in steel structures. In this study, electrospun nanofiber veils were first proposed to enhance the bond performance of CFRP-steel epoxy-bonded interfaces. Firstly, shear tests were conducted on neat epoxy and nano-modified single-lap aluminum-aluminum joints to determine the optimal areal density and number of layers of nanofiber veils, as well as the optimal curing processes. Then, a series of neat epoxy and nano-modified CFRP-steel double-lap joints with different bond lengths were tested to investigate the size effect of the bond behavior. The displacement and strain field evolution of the joints were captured by the digital image correlation (DIC) technique, allowing for visualization of the detailed failure process. The failure modes, load-displacement curves, CFRP strain distributions, and bond-slip relationships of the CFRP-steel joints were obtained. Both the tests on aluminum-aluminum and CFRP-steel joints show that the optimal modification strategy is incorporating 3 layers of nanofiber wels with an areal density of 4.5 g/m2, with 5 h room-temperature and 2 h 80°C high-temperature curing. The primary failure mode of CFRP-steel joints is CFRP delamination accompanied by CFRP-adhesive interface or steel-adhesive interface debonding. The bond strengths of the modified joints with 3 layers of 1.5 g/m2 and 4.5 g/m2 nanofiber veils are increased by 7% and 25% compared to those of un-modified joints, respectively. The 4.5 g/m2 nanofiber veils modified bonded interface has an effective bond length of about 152 mm, with a corresponding ultimate bearing capacity of 117 kN. Different from the triangular (brittle) shape of most neat epoxy interfaces, the nano-modified interfaces have trapezoidal (ductile) bond-slip relationships, providing superior cracking resistance. Moreover, a comparison with the bond strength of SiO2 nano-particles and carbon nanotubes (CNTs) modified joints revealed that nanofiber veil modification comes to higher bond strength in most cases. The proposed electrospun nanofiber veil modification technique provides a great insight into the interfacial toughening of CFRP-steel composite structures.

碳纤维增强聚合物（CFRP）与钢之间的环氧树脂粘结界面通常强度和韧性不足，粘结界面的增韧是碳纤维增强聚合物在钢结构中应用的关键问题。本研究首次提出了电纺纳米纤维纱来增强 CFRP 与钢环氧树脂粘结界面的粘结性能。首先，对纯环氧树脂和纳米改性单层铝-铝接头进行了剪切试验，以确定纳米纤维网的最佳面积密度和层数，以及最佳固化工艺。然后，测试了一系列具有不同粘接长度的纯环氧树脂和纳米改性 CFRP-钢双搭接接头，以研究粘接行为的尺寸效应。通过数字图像相关（DIC）技术捕捉了接头的位移和应变场演变，从而实现了详细失效过程的可视化。获得了 CFRP-钢接头的破坏模式、载荷-位移曲线、CFRP 应变分布和粘结-滑移关系。铝-铝和 CFRP-钢接头的测试表明，最佳改性策略是加入 3 层面积密度为 4.5 g/m2 的纳米纤维，并进行 5 小时室温固化和 2 小时 80°C 高温固化。CFRP 与钢接头的主要失效模式是 CFRP 分层，同时伴有 CFRP 粘接界面或钢粘接界面脱粘。与未改性接头相比，使用 3 层 1.5 g/m2 和 4.5 g/m2 纳米纤维纱的改性接头的粘接强度分别提高了 7% 和 25%。4.5 g/m2 纳米纤维纱改性粘接界面的有效粘接长度约为 152 mm，相应的极限承载能力为 117 kN。与大多数纯环氧树脂界面的三角形（脆性）不同，纳米改性界面具有梯形（韧性）的粘结滑移关系，从而提供了优异的抗开裂性能。此外，与二氧化硅纳米颗粒和碳纳米管（CNTs）改性接头的粘接强度相比，纳米纤维面纱改性在大多数情况下具有更高的粘接强度。所提出的电纺纳米纤维面纱改性技术为 CFRP-钢复合材料结构的界面增韧提供了重要的启示。