
今日更新:Journal of the Mechanics and Physics of Solids 3 篇,Mechanics of Materials 2 篇,International Journal of Plasticity 1 篇,Thin-Walled Structures 2 篇
Modeling the Influence of Hydrogen on Ni201 Plastic Behavior through Integration of Experimental Observations and Multiobjective Optimization
Leonidas Zisis, Krzysztof S. Stopka, Mohammad Imroz Alam, Zachary D. Harris, Michael D. Sangid
doi:10.1016/j.jmps.2025.106345
基于实验观察和多目标优化的氢对Ni201塑性行为影响建模
Hydrogen is a promising alternative to traditional fossil fuels due to its abundance, high energy density, and clean energy profile. However, hydrogen can degrade the mechanical properties of materials, hindering its widespread implementation. This work develops a crystal plasticity finite element model (CPFE) model to assess the influence of hydrogen on the macroscale behavior of pure nickel, Ni201. The model is based on existing mechanis ms, including hydrogen-enhanced localized plasticity (HELP) and hydrogen-enhanced strain-induced vacancies (HESIV), as well as the defactant theory, which attempts to explain these mechanis ms within a thermodynamic framework. Monotonic tensile tests were performed at hydrogen concentrations of 0, 3000, 4000, and 5000 appm, from which yield strength, initial work hardening, and work hardening rate evolution were extracted to inform development of the crystal plasticity constitutive equations. The model parameters were calibrated using a state-of-the-art multiobjective UNSGA-III algorithm. Although the model assumes a uniform distribution of hydrogen and does not incorporate time-dependent processes such as ingress and diffusion, it captures the non-linear increasing trend of the three abovementioned metrics as a function of hydrogen concentration.
氢因其丰富、高能量密度和清洁能源特性而成为传统化石燃料的一种很有前途的替代品。然而,氢会降低材料的机械性能,阻碍了它的广泛应用。本工作建立了一个晶体塑性有限元模型(CPFE)模型来评估氢对纯镍Ni201宏观尺度行为的影响。该模型基于现有的机制,包括氢增强局部塑性(HELP)和氢增强应变诱导空位(HESIV),以及试图在热力学框架内解释这些机制的defactant理论。在0、3000、4000和5000 appm的氢浓度下进行单调拉伸试验,从中提取屈服强度、初始加工硬化和加工硬化速率演变,为晶体塑性本构方程的发展提供信息。模型参数使用最先进的多目标UNSGA-III算法进行校准。尽管该模型假设氢的均匀分布,并且不考虑诸如进入和扩散等与时间相关的过程,但它捕获了上述三个指标作为氢浓度函数的非线性增长趋势。
A Mechano-Immunological Framework for Lymph Node Remodeling During Inflammation and Homeostasis
Ming-Yue Wang, Bo Li, Xi-Qiao Feng, Huajian Gao
doi:10.1016/j.jmps.2025.106347
炎症和体内平衡期间淋巴结重塑的机械免疫框架
During the immune response, lymph nodes (LNs) undergo significant coupled evolutions in their geometric structures, cellular compositions, and mechanical properties. The efficiency of the immune response (IR) is governed by the interplay between internal cellular activity and mechanical deformation throughout the inflammation–homeostasis process. While mechanical forces are known to play a crucial role in LN remodeling, the underlying mechanis ms of mechano-immunology synergy within LNs remain poorly understood. Here, we propose a mechano-immunology theory that conceptualizes LNs as integrated, dynamically evolving structures during IR and establish a mechano-immunological landscape to quantify distinct LN states. This framework introduces a novel paradigm for evaluating IR efficiency based on metrics derived from mechano-chemo-biological mechanis ms. We identify the range of mechanical properties that optimize IR efficiency and propose that immune exhaustion in tumor-draining LNs arises from mechanical damage, leading to an immune anergic state. Using the proposed mechano-immunological methodology, we demonstrate that this anergic state can be mitigated by modulating collective immune cell migration to align with the optimal IR efficiency range, thereby offering potential therapeutic strategies to enhance IR efficiency.
在免疫应答过程中,淋巴结(LNs)在其几何结构、细胞组成和力学性能方面经历了显著的耦合演化。免疫反应(IR)的效率是由内部细胞活动和整个炎症稳态过程中的机械变形之间的相互作用决定的。虽然已知机械力在LN重塑中起着至关重要的作用,但LN中机械免疫协同作用的潜在机制仍然知之甚少。在这里,我们提出了一种机械免疫学理论,该理论将LN概念化为IR过程中集成的、动态演变的结构,并建立了一个机械免疫学景观来量化不同的LN状态。该框架引入了一种基于机械-化学-生物机制衍生的指标来评估红外效率的新范式。我们确定了优化IR效率的机械特性范围,并提出肿瘤引流LNs中的免疫衰竭是由机械损伤引起的,导致免疫无能状态。利用提出的机械免疫学方法,我们证明了这种无能状态可以通过调节集体免疫细胞迁移来减轻,以符合最佳IR效率范围,从而提供潜在的治疗策略来提高IR效率。
High-performance Programmable Combinatorial Lattice Materials
Jian Zhao, Robert O. Ritchie, Jian Xiong
doi:10.1016/j.jmps.2025.106351
高性能可编程组合晶格材料
A long-standing challenge in modern materials design is overcoming inefficient and arbitrary trial-and-error approaches. To tackle this challenge, this study introduces a novel concept of “combinatorial lattices” and establishes a comprehensive performance library to enable systematic, property-driven design. Through a combination of theoretical modeling, finite element simulations, and experimental validation, this study demonstrates the effectiveness of this approach in facilitating both anisotropic design and tradeoff design across multiple mechanical properties. The resulting combinatorial lattices achieve stiffness and strength values up to 66.0% of the Hashin–Shtrikman upper bound and 60.2% of the Suquet bound, respectively. Notably, the combinatorial lattices exhibit relative strengths approaching—or even exceeding—the empirical upper bounds predicted by the Gibson-Ashby model. The energy absorption per unit volume surpasses that of comparable-density lattices by more than threefold, and the CFE reaches a remarkable 151%. Beyond superior static performance, the Kelvin+BCC lattice demonstrates exceptional damage tolerance under 5 cyclic loading, retaining 99.5% of its initial strength and 79.9% of its initial stiffness after repeated compression at high strain levels. This work provides a programmable mechanomaterial design framework that proactively integrates geometric combinatorics with performance-driven criteria, offering a robust pathway for the development of high-performance lattice structures and advanced materials.
现代材料设计的一个长期挑战是克服低效和任意的试错方法。为了应对这一挑战,本研究引入了“组合格”的新概念,并建立了一个全面的性能库,以实现系统的、属性驱动的设计。通过理论建模、有限元模拟和实验验证的结合,本研究证明了该方法在促进各向异性设计和跨多种力学性能权衡设计方面的有效性。所得到的组合格的刚度和强度值分别达到Hashin-Shtrikman上限的66.0%和Suquet上限的60.2%。值得注意的是,组合晶格表现出接近甚至超过吉布森-阿什比模型预测的经验上限的相对优势。单位体积的能量吸收是同密度晶格的3倍以上,CFE达到了惊人的151%。除了优异的静态性能外,Kelvin+BCC晶格在5次循环加载下表现出优异的损伤容忍度,在高应变水平下反复压缩后,其初始强度保持了99.5%,初始刚度保持了79.9%。这项工作提供了一个可编程的机械材料设计框架,主动将几何组合学与性能驱动标准相结合,为高性能晶格结构和先进材料的开发提供了一条强大的途径。
An artificial neural network-based thermo-mechanically coupled model for elastocaloric cooling of shape memory alloys
Xingyu Zhou, Ziang Liu, Chao Yu, Guozheng Kang
doi:10.1016/j.mechmat.2025.105485
基于人工神经网络的形状记忆合金弹热冷却热-机耦合模型
Environment-friendly and high-efficiency elastocaloric solid-state cooling has emerged as a promising alternative to traditional vapor-compression refrigeration. Owing to the high entropy change during martensite transformation, NiTi shape memory alloy (S MA) is a competitive candidate for the core components of solid-state cooling systems. In the design of elastocaloric cooling devices manufactured by S MAs, a thermo-mechanically coupled constitutive model accounting for the internal heat production, heat exchange and their influences on the subsequent deformation is needed. However, the concepts in classical plasticity are often employed in the existing physics-based constitutive models, and a series of complex mathematical equations are involved. Such complexity brings inconvenience for the construction, implementation, and application of the constitutive models. To overcome these shortcomings, an artificial neural network (ANN)-based model is developed in this work to reproduce the thermo-mechanically coupled deformation of S MAs. In the proposed model, the components of strain tensor in principal space, ambient temperature and the maximum equivalent strain in the deformation history from the initial state to the current loading state are chosen as the input features, and the components of the stress tensor in principal space and the internal heat source are set as the outputs. The proposed ANN-based model is implemented into the finite element program ABAQUS by deriving its consistent tangent modulus and writing a user-defined material subroutine (UMAT). The thermal response and deformation of S MA under various loading paths and at different ambient temperatures are used to train the ANN model, which are generated from the existing physics-based constitutive model (numerical experiments). To validate the capability of the proposed model, the predicted thermal and mechanical responses of a S MA tube subjected to pure tension, pure torsion and tension-torsion combined multi-axial loading conditions at various loading rates are compared with the corresponding numerical experiments. The proposed model is further verified by predicting the elastocaloric cooling performances of typical S MA structures, including the helical springs and thin plates with holes.
环境友好和高效的弹性热固态冷却已经成为传统蒸汽压缩制冷的一个有前途的替代方案。由于马氏体相变过程中的高熵变化,NiTi形状记忆合金(S MA)成为固态冷却系统核心部件的有竞争力的候选材料。在S MAs制造的弹热冷却装置的设计中,需要一个考虑内部产热、换热及其对后续变形影响的热-机械耦合本构模型。然而,现有的基于物理的本构模型往往采用经典塑性的概念,并涉及一系列复杂的数学方程。这种复杂性给本构模型的构建、实现和应用带来了不便。为了克服这些缺点,本文建立了一种基于人工神经网络(ANN)的模型来再现s ma的热-机械耦合变形。在该模型中,选择主空间应变张量分量、环境温度分量和从初始状态到当前加载状态的变形历史中的最大等效应变分量作为输入特征,主空间应力张量分量和内部热源分量作为输出特征。提出的基于人工神经网络的模型通过推导其一致切线模量并编写用户自定义材料子程序(UMAT)在有限元程序ABAQUS中实现。利用S MA在不同加载路径和不同环境温度下的热响应和变形来训练基于现有物理本构模型(数值实验)的人工神经网络模型。为了验证该模型的有效性,将不同加载速率下S MA管在纯拉伸、纯扭转和拉伸-扭转复合多轴加载条件下的热响应和力学响应预测结果与相应的数值实验进行了比较。通过预测典型S MA结构(包括螺旋弹簧和带孔薄板)的弹热冷却性能,进一步验证了所提模型的有效性。
Fatigue Life Prediction of powder bed fused–laser beam AlSi10Mg: Incorporating Critical Defects via Crystal Plasticity Modelling
Kamin Tahmas bi, Mohammadreza Yaghoobi, Meysam Haghshenas
doi:10.1016/j.mechmat.2025.105486
基于晶体塑性模型的粉末床熔合AlSi10Mg激光束疲劳寿命预测
The current study provides a microstructurally-based computational framework to predict the fatigue life of additive manufactured (AM), i.e., powder bed fused–laser beam (PBF-LB), AlSi10Mg specimens using the crystal plasticity finite element method (CPFEM). The fractography an alysis, electron backscatter diffraction (EBSD), uniaxial and cyclic responses, and fatigue life of specimens were used to inform the computational framework. CPFE simulation was used to compute fatigue indicator parameters (FIPs) as fatigue driving forces. A new fatigue criterion is introduced based on FIPs, which was calibrated using experimental fatigue data. The proposed fatigue measure was evaluated versus the specimens with critical defects of various sizes and locations subjected to different stress amplitudes. The results show that the developed framework can capture the fatigue life of samples with different critical defect locations and sizes along with different stress amplitudes for both high-cycle fatigue (HCF) and very high-cycle fatigue (VHCF) regimes.
本研究提供了一个基于微观结构的计算框架,利用晶体塑性有限元法(CPFEM)预测增材制造(AM),即粉末床熔融激光束(PBF-LB), AlSi10Mg试样的疲劳寿命。采用断口分析、电子背散射衍射(EBSD)、单轴和循环响应以及试样的疲劳寿命为计算框架提供信息。CPFE模拟计算疲劳指标参数(FIPs)作为疲劳驱动力。提出了一种新的基于FIPs的疲劳判据,并利用试验疲劳数据进行了标定。针对不同尺寸和位置的临界缺陷试件,在不同应力幅值的作用下,对所提出的疲劳测量方法进行了评价。结果表明,所开发的框架可以捕捉高周疲劳和甚高周疲劳两种状态下,不同临界缺陷位置和尺寸、不同应力幅值下试样的疲劳寿命。
Investigation of twin-dislocation interactions using a novel discrete dislocation plasticity framework
Hai Xin, Zebang Zheng, Mei Zhan, Yudong Lei, Pandi Zhao, Yuyang Wang, Fei Ma, Gaihuan Yuan, M.W. Fu
doi:10.1016/j.ijplas.2025.104465
用新的离散位错塑性框架研究双位错相互作用
Twinning-induced strain localization fundamentally governs a material’s ductility and failure mechanis ms, complementing the role of dislocation slip in hexagonal close-packed crystals. This localization not only accommodates externally applied deformation through stress redistribution but also generates heterogeneous stress that significantly influences nearby dislocation evolution. In conventional dislocation-scale modeling approaches, such as discrete dislocation plasticity (DDP), twinning is typically represented by introducing twin boundaries and regions with reoriented crystal lattices. These models, however, often neglect the associated strain fields generated during the twinning process, resulting in an incomplete description of twinning-dislocation interactions. To address this limitation, a novel DDP model incorporating twin-induced heterogeneous deformation was developed. The model explicitly includes different stages of twinning, such as nucleation, propagation, and growth, and implements the twin-induced stress field using the classical Eshelby inclusion solution. A new superposition framework was further constructed to capture these stress contributions within the DDP formulation accurately. Based on this model, the experimentally observed characteristic twin-induced dislocation arrays in single crystals and bicrystal were successfully reproduced. Moreover, through comparison with the twin-free model, twin-dislocation interactions in polycrystals were quantitatively ana lyzed, demonstrating the capability of the model to resolve complex plasticity mechanis ms across different microstructures.
孪晶引起的应变局部化从根本上控制了材料的延展性和破坏机制,补充了位错滑移在六方密排晶体中的作用。这种局部化不仅通过应力重分布适应外部施加的变形,而且还产生非均质应力,显著影响附近位错的演变。在传统的位错尺度建模方法中,如离散位错塑性(DDP),孪生通常通过引入具有重定向晶格的孪晶边界和区域来表示。然而,这些模型往往忽略了孪晶过程中产生的相关应变场,导致对孪晶-位错相互作用的描述不完整。为了解决这一限制,开发了一种新的包含双诱导非均质变形的DDP模型。该模型明确地包含了孪生的不同阶段,如成核、扩展和生长,并使用经典的Eshelby夹杂解实现了孪生诱发应力场。进一步构建了一个新的叠加框架,以准确捕获DDP公式中的这些应力贡献。基于该模型,成功地再现了实验中观察到的单晶和双晶中 特征性的双致位错阵列。此外,通过与无孪晶模型的比较,定量分析了多晶中的孪位错相互作用,证明了该模型能够解决不同微观结构的复杂塑性机制。
Enhancing interfacial adhesion of induction welded CF/PA66 joints via fabricating a hierarchical micro-nano porous structure on heating element
Tenghui He, Jianhui Su, Xueyan Zhang, Fuyun Liu, Xiaohui Han, Jin Yang, Yunhua Deng, Bo Chen, Xiaoguo Song, Caiwang Tan
doi:10.1016/j.tws.2025.113940
在加热元件上制备微纳层次化多孔结构提高CF/PA66感应焊接接头的界面附着力
The development of efficient and reliable bonding techniques for thermoplastic composites was crucial for lightweight and high-performance structural applications in industries such as automotive and aerospace. This study investigated the use of aluminum mesh as a heating element (HE) for the induction welding of thermoplastic composites, aiming to produce lightweight and high-strength joints. A hierarchical micro-nano porous structure was developed on the HE surfaces via an anodization and acid etching (AAE) treatment to enhance the interfacial adhesion between the HE and resin matrix. The results showed that the hierarchical micro-nano porous structure significantly increased HE surface roughness and hydroxyl adsorption, improving wettability and promoting mechanical interlocking between HE and the resin matrix during welding. Interface ana lysis further demonstrated that this micro-nano structure also facilitated stronger Al-O-C bond interactions between HE and resin matrix. As a result, under the synergistic effect of mechanical interlocking and chemical bonding at the HE/PA66 interface, the lap shear strength (LSS) of the AAE-treated joints increased by 45.5 %, reaching 16.06 MPa. Digital image correlation (DIC) technique ana lysis revealed that the hierarchical micro-nano porous structure effectively alleviated strain concentration at the weld seam. Overall, the introduction of the hierarchical micro-nano porous structure on the HE surfaces significantly improved weld seam uniformity and joint strength, providing an innovative solution for the efficient and reliable joining of thermoplastic composites.
开发高效可靠的热塑性复合材料粘接技术对于汽车和航空航天等行业的轻量化和高性能结构应用至关重要。本研究利用铝网作为加热元件(HE)进行热塑性复合材料的感应焊接,旨在生产轻量化和高强度的接头。通过阳极氧化和酸蚀(AAE)处理,在HE表面形成层次微纳多孔结构,以增强HE与树脂基体之间的界面附着力。结果表明,分层微纳多孔结构显著提高了HE表面粗糙度和羟基吸附,改善了HE的润湿性,促进了HE与树脂基体在焊接过程中的机械联锁。界面分析进一步表明,这种微纳结构也促进了HE与树脂基体之间更强的Al-O-C键相互作用。结果表明,在HE/PA66界面机械联锁和化学结合的协同作用下,aae处理接头的搭接抗剪强度(LSS)提高了45.5%,达到16.06 MPa。数字图像相关(DIC)技术分析表明,分层微纳多孔结构有效地缓解了焊缝应变集中。总体而言,在HE表面引入分层微纳多孔结构显著改善了焊缝均匀性和接头强度,为热塑性复合材料的高效可靠连接提供了创新的解决方案。
Size-driven transitions in ballistic limit velocity and energy absorption mechanis ms for plain weave fabrics
Xuan Zhou, Xintian Li, Kaiying Wang, Guangfa Gao, Lizhi Xu
doi:10.1016/j.tws.2025.113941
平纹织物的弹道极限速度和能量吸收机制中尺寸驱动的过渡
Aramid plain weave fabrics are extensively utilized in flexible protective systems. In this study, ballistic tests were conducted using spherical projectiles of different diameters to impact aramid fabrics with varying yarn fineness. The effects of projectile and yarn dimensions on the ballistic performance of the fabric were ana lyzed. Combined with numerical simulations, the study elucidated the energy transformation and distribution mechanis ms during the penetration process, revealed the transition mechanis m of yarn failure modes, and identified the critical threshold of size effect. Furthermore, a predictive model for the ballistic limit velocity (V50) of single-layer plain weave fabrics was established, incorporating both size effects and the shape of the projectile nose. The results indicate that, for the same type of fabric, as the projectile diameter increases, both V50 and specific energy absorption (SEA) increase. Compared to fabrics with coarser yarns, those with finer yarns exhibit relatively higher SEA, although the former shows higher V1. As the projectile diameter decreases and yarn fineness increases, the failure mode of the plain fabric gradually shifts from a thrusting mode to a windowing mode. A projectile-to-yarn width ratio of approximately 9 marks the transition point of the fabric failure mode and the critical threshold of the size effect. Compared to conventional models, the revised ballistic limit velocity model demonstrates significantly improved prediction accuracy, with a maximum error within 22%.
芳纶平纹织物在柔性防护系统中得到了广泛应用。本研究采用不同直径的球形弹丸对不同纱线细度的芳纶织物进行了弹道测试。分析了弹丸和纱线尺寸对织物弹道性能的影响。结合数值模拟,阐明了穿透过程中能量转换和分布机制,揭示了纱线破坏模式的转变机制,并确定了尺寸效应的临界阈值。此外,建立了考虑尺寸效应和弹丸鼻部形状的单层平纹织物弹道极限速度(V50)预测模型。结果表明,对于同一种织物,随着弹丸直径的增大,V50 和比能量吸收(SEA)均增大。与粗纱织物相比,细纱织物的 SEA 相对较高,但前者的 V1 较高。随着弹丸直径减小和纱线细度增加,平纹织物的破坏模式逐渐从推挤模式转变为开窗模式。弹丸与纱线宽度比约为 9 时,标志着织物破坏模式的转变点和尺寸效应的临界阈值。与传统模型相比,改进后的弹道极限速度模型预测精度显著提高,最大误差在 22%以内。