【新文速递】2026年1月6日固体力学SCI期刊最新文章

 

今日更新：International Journal of Solids and Structures 2 篇，Journal of the Mechanics and Physics of Solids 1 篇，Thin-Walled Structures 4 篇

International Journal of Solids and Structures

A multi-scale electromechanically coupled FE2 model on the sensing capacities of CNT-based nanocomposite strain sensor: A machine learning accelerated scheme

Xiaodong Xia, Ruiyang Li, Zheng Zhong

doi:10.1016/j.ijsolstr.2026.113829

基于cnt的纳米复合应变传感器传感能力的多尺度机电耦合FE2模型：一种机器学习加速方案

In contrast to the conventional piezoelectric sensor, the CNT-based nanocomposite strain sensor (CNCSS) serves as a new category of high-performance strain sensor. The bottleneck for evaluating sensing capacities of CNCSS lies in the nonlinear electromechanical coupling mechanis m and extra high computational costs of multi-scale simulation. In this paper, a novel multi-scale FE2 model and a machine learning accelerated FE-RNN computational model have both been developed on the strain sensing capacities of high-performance CNCSS. First, a multi-scale electromechanically coupled FE2 model is established for the CNCSS with a realistic configuration. The electromechanically coupled mechanis m is illustrated by a loading-dependent tunneling model, which is highly dependent on the tunneling distance between the adjacent CNTs. The developed coupled FE2 model is able to predict the strain sensing performance of CNCSS with a macroscopic configuration while considering specific microstructural characteristics. Then, an electromechanically coupled recurrent neural network (RNN) surrogate model is utilized to accelerate the FE2 model in the microscopic scale. The developed FE-RNN model can accelerate the microscopic simulation of RVE for a continuous range of microstructural parameters. The predicted sensing characteristics via the developed FE2 model and accelerated FE-RNN model are both highly consistent with the experiment of CNT/epoxy nanocomposite strain sensor under a realistic configuration. Especially at the high strain loading, the predicted results reflect the sharp increase of sensing capacities for CNCSS. The accelerated FE-RNN approach is concluded to possess the advantage over the FE2 model on the structural a nalysis by significantly reducing the computational costs by 97%. The developed FE-RNN scheme is capable of providing rapid design instructions for the microstructure of high-performance strain sensors.

与传统的压电传感器相比，基于碳纳米管的纳米复合应变传感器（CNCSS）是一种新型的高性能应变传感器。评价CNCSS传感能力的瓶颈在于非线性机电耦合机制和多尺度仿真的计算成本过高。本文针对高性能CNCSS的应变传感能力，建立了一种新的多尺度FE2模型和一种机器学习加速的FE-RNN计算模型。首先，建立了具有实际结构的CNCSS的多尺度机电耦合FE2模型。机电耦合机制通过负载相关的隧道模型来说明，该模型高度依赖于相邻碳纳米管之间的隧道距离。所建立的耦合FE2模型能够在考虑特定微观结构特征的同时，预测具有宏观结构的CNCSS应变传感性能。然后，利用机电耦合递归神经网络（RNN）替代模型在微观尺度上加速FE2模型。所建立的FE-RNN模型可以在连续的微观结构参数范围内加速RVE的微观模拟。所建立的FE2模型和加速FE-RNN模型预测的传感特性与实际配置下CNT/环氧纳米复合应变传感器的实验结果高度一致。特别是在高应变载荷下，预测结果反映了CNCSS的传感能力的急剧提高。加速的FE-RNN方法在结构分析上比FE2模型具有优势，计算成本显著降低97%。本文提出的FE-RNN方案能够为高性能应变传感器的微观结构提供快速设计指导。

Study on the damage mechanis m of titanium alloy threads during roll forming based on a machine learning-assisted multi-scale damage model

Xin Song, Ning Han, Huiping Qi, Yong Hu, Wen Yang, Zhenjiang Li, Zhengyi Jiang, Lu Jia

doi:10.1016/j.ijsolstr.2026.113830

基于机器学习辅助多尺度损伤模型的钛合金螺纹滚压成形损伤机理研究

In this study, a multi-scale damage an alysis method coupling an improved GTN and Cohesive Zone Model is developed. The Precise and efficient inversion of model parameters was achieved through a differential evolution algorithm. The reconstructed microstructure via image recognition is introduced into finite element simulations, and the damage evolution patterns in duplex titanium alloys during thread rolling are studied. The results show that the established model accurately reproduces both the macroscopic mechanical response and microcrack propagation. Further predictions indicate that damage concentration occurs predominantly at the thread root regions. The microcrack initiation at α/β phase interfaces and loss of deformation coordination. The study provides a framework linking microstructural mechanis s to macroscopic performance, enabling precise prediction and control of damage during titanium alloy plastic deformation processes.

本文提出了一种结合改进GTN和内聚区模型的多尺度损伤分析方法。通过微分进化算法实现了模型参数的精确高效反演。将图像识别重建的显微组织引入有限元模拟，研究了双相钛合金螺纹轧制过程中的损伤演化模式。结果表明，所建立的模型能较好地再现试件的宏观力学响应和微裂纹扩展。进一步的预测表明，损伤集中主要发生在螺纹根部。α/β相界面处微裂纹萌生及变形配位丧失。该研究提供了一个将微观结构机制与宏观性能联系起来的框架，使钛合金塑性变形过程中的损伤能够精确预测和控制。

Journal of the Mechanics and Physics of Solids

A micro-informed thermodynamically consistent plasticity model for clays accounting for double porosity and fabric

Angelo Amorosi, Yang Yu, Zhongxuan Yang, Fabio Rollo

doi:10.1016/j.jmps.2026.106503

考虑双重孔隙率和织物的粘土微知情热力学一致塑性模型

Clays are natural materials characterised by a nonlinear and irreversible mechanical behaviour that originates from the complex internal microstructure composed by particles often arranged to form clusters. Despite the increasing availability of accurate laboratory techniques to measure the properties of clays at the microscale, most of the existing macroscopic constitutive models disregard their particulate nature, adopting scalar and tensorial variables that are treated as pure mathematical entities aimed at reproducing the mechanical response of this class of materials. In this paper, we develop a new constitutive model formulated within the framework of thermodynamics with internal variables, in which we have selected two scalar internal variables, intra- and inter-cluster void ratios, and a second order fabric tensor, to link the evolution of the porosity and the particles orientation at the microscale with the macroscopic mechanical behaviour of clays. Through a new strategy of initialisation of the internal variables based on direct microscale measurements, and incorporating the two interacting scales of porosity and fabric, the formulation can capture some relevant features of clays behaviour, such as s mall strain irreversibility, anisotropy and critical state, while maintaining the simplicity and the computational efficiency of a single-surface elasto-plastic model.

粘土是一种天然材料，其非线性和不可逆的力学行为源于其复杂的内部微观结构，这些微观结构由经常排列成簇的颗粒组成。尽管越来越多的实验室技术可以精确地测量粘土在微观尺度上的特性，但大多数现有的宏观本构模型忽略了它们的颗粒性质，采用标量和张量变量，这些变量被视为纯数学实体，旨在再现这类材料的力学响应。本文在热力学框架下建立了一个具有内变量的本构模型，选取团簇内和团簇间空隙比两个标量内变量，以及一个二阶织构张量，将孔隙度和颗粒取向的微观演化与粘土的宏观力学行为联系起来。通过基于直接微尺度测量的内部变量初始化策略，结合孔隙率和结构两个相互作用的尺度，该公式可以在保持单表面弹塑性模型的简单性和计算效率的同时，捕获粘土行为的一些相关特征，如小应变不可逆性、各向异性和临界状态。

Thin-Walled Structures

Design and Characterization of the Behavior of an Auxetic Structure for a Biosandwich Core Reinforced by Chamaerops humilis Palm Biofibers: RS M Optimization

Soumia Atoui, Ahmed Belaadi, Aziz Saaidia, Djamel Ghernaout

doi:10.1016/j.tws.2026.114481

棕chamerops Palm生物纤维增强生物夹层结构的设计与性能表征：RS M优化

This work investigates the design, fabrication, and mechanical characterization of auxetic honeycomb structures reinforced with Chamaerops humilis fibers (ChFs) as lightweight sandwich core materials. Auxetic cores with re-entrant geometry were 3D-printed using polylactic acid (PLA) and subsequently infused with bio-based epoxy composites reinforced by short ChFs at varying fiber weight fractions (10, 20, 30, and 40%) and thicknesses (2, 3, 4, and 5 mm). The influence of these parameters on compressive stress, compressive strain, energy absorption capacity (EAC), and Poisson’s ratio was examined through quasi-static compression tests conducted in accordance with ASTM C365 standards. Optimization of mechanical responses was achieved using the Taguchi method with an L16 orthogonal array and Response Surface Methodology (RS M). Maximum compressive stress of 119.29 MPa was attained at 30% fiber weight and 5 mm thickness, while the peak compressive strain of 9.25 occurred at 30% fiber weight and 3 mm thickness. The highest energy absorption capacity recorded was 96.69 × 10³ J/m³ at 30% fiber content and 5 mm thickness. The auxetic nature of the structures was confirmed by negative Poisson’s ratio values ranging from –0.15 to –0.25 across all samples, demonstrating significant lateral expansion under axial load due to the re-entrant geometry. An alysis of variance (ANOVA) identified both fiber weight fraction and core thickness as statistically significant factors influencing mechanical performance (p < 0.05). Microstructural characterization via scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX) validated uniform fiber dispersion within the matrix and elucidated failure mechanis ms, primarily fiber-matrix debonding and fiber pull-out under compression. This comprehensive study confirms the feasibility of ChFs-reinforced auxetic honeycomb structures as highly efficient, lightweight materials with enhanced mechanical properties and energy absorption capacity, making them promising candidates for sustainable aerospace and structural engineering applications where weight reduction and impact resistance are critical.

本研究研究了用Chamaerops humilis纤维（ChFs）作为轻质夹层芯材增强的增塑型蜂窝结构的设计、制造和力学特性。使用聚乳酸（PLA） 3d打印具有可重新进入几何形状的增塑型芯，随后注入由不同纤维重量分数（10,20,30和40%）和厚度（2,3,4和5mm）的短ChFs增强的生物基环氧复合材料。按照ASTM C365标准进行准静态压缩试验，考察这些参数对压应力、压应变、能量吸收能力（EAC）和泊松比的影响。采用L16正交阵列的田口法和响应面法（RS M）对其力学响应进行了优化。在纤维重量为30%、纤维厚度为5 mm时，最大压应力为119.29 MPa；在纤维重量为30%、纤维厚度为3 mm时，最大压应变为9.25 MPa。当纤维含量为30%，纤维厚度为5mm时，吸能量最高为96.69 × 10³J/m³。所有样品的负泊松比值在-0.15至-0.25之间，证实了结构的auxetic性质，表明由于再入几何形状，在轴向载荷下显着的横向膨胀。方差分析（ANOVA）发现纤维重量分数和纤芯厚度是影响机械性能的有统计学意义的因素（p < 0.05）。通过扫描电子显微镜（SEM）和能量色散x射线光谱（EDAX）进行的微观结构表征验证了纤维在基体中的均匀分散，并阐明了破坏机制，主要是纤维与基体的脱粘和纤维在压缩下的拉出。这项综合研究证实了chfs增强的消声蜂窝结构作为高效、轻质材料的可行性，具有增强的机械性能和能量吸收能力，使其成为可持续航空航天和结构工程应用的有希望的候选者，在这些应用中，减轻重量和抗冲击是至关重要的。

Full-scale simulation of containership motion and load responses by whole ship structure FE model one-way coupled with CFD solver

Jialong Jiao, Zhenwei Chen, Hang Xie, Yuefu Yang

doi:10.1016/j.tws.2026.114484

采用全船结构有限元模型单向耦合CFD求解器对集装箱船运动和载荷响应进行全尺寸仿真

Wave-induced ship global loads and hydroelastic responses have long been predicted by simplified model with a backbone beam, where the detailed internal structures of real ship are ignored. This paper presents a simulation method to comprehensively predict wave-induced ship motions, global and local loads and structural responses of a full-scale 21000TEU containership by whole ship structure finite element (FE) model one-way coupled with computational fluid dynamics (CFD) solver. For this purpose, a full-scale FE model of the whole ship structure is established in FEM solver and a numerical wave tank is built in CFD solver. The one-way coupling between CFD and finite element method (FEM) solvers is configured and the simulations are conducted on supercomputing platform. The full-scale simulation results of ship motions, vertical acceleration, slamming pressure and global sectional loads are validated by comparing with tank model experiment and other numerical simulation results. The ship motions, external fluid loads, global and local stress distributions simulated by the full-scale simulations in typical cases of different wave heights are systematically presented and a nalyzed. This study has potential application values for the development of high-fidelity numerical tank technique for ship structural design and seakeeping evaluation.

波浪引起的船舶整体荷载和水弹性响应一直是用带主梁的简化模型来预测的，而忽略了真实船舶内部结构的细节。本文提出了一种利用全船结构有限元（FE）模型单向耦合计算流体力学（CFD）求解器，综合预测21000TEU全尺寸集装箱船波浪运动、整体和局部载荷及结构响应的仿真方法。为此，在有限元求解器中建立了全船结构的全尺寸有限元模型，在CFD求解器中建立了数值波浪舱。建立了CFD与有限元求解器之间的单向耦合，并在超级计算平台上进行了仿真。通过与舱体模型试验和其他数值模拟结果的对比，验证了船舶运动、垂直加速度、冲击压力和整体截面载荷的全尺寸仿真结果。系统地介绍和分析了不同波高典型情况下全尺寸仿真所模拟的船舶运动、外部流体载荷、整体和局部应力分布。该研究对发展高保真数值舱技术用于船舶结构设计和耐波性评价具有潜在的应用价值。

Dynamic evolution of wall pressure reflection coefficient and structural response characteristics of stiffened cylindrical shells subjected to underwater explosion Loads

Yuheng Liu, Kun Zhao, Zhikai Wang, Renjie Huang, Xiongliang Yao, Naji Ma

doi:10.1016/j.tws.2026.114485

水下爆炸荷载作用下加劲圆柱壳壁压反射系数动态演化及结构响应特性

This study investigates the pressure characteristics of the inner wall surface and the evolution mechanis m of the pressure reflection coefficient for stiffened thin-walled cylindrical shell structures subjected to complex fluid-structure interaction phenomena—including wall reflection, diffraction, and interference—under underwater explosion loads at medium interfaces. Based on material strain rate effects, the dynamic evolution mechanis m of the wall pressure reflection coefficient is ana lyzed theoretically. Elastic deformation experiments were conducted to explore how different damage characteristics of the stiffened cylindrical shell structure influence the time-domain features of wall pressure and its reflection coefficient. To further investigate system parameter effects on wall pressure, numerical simulations were performed for cases with plastic s mall deformation and plastic indentation large deformation damage characteristics. The dynamic evolution laws of the wall pressure reflection coefficient at the explosion point were examined under varying load parameters. A semi-empirical formula for the wall pressure reflection coefficient was developed based on load parameters and structural characteristic parameters, revealing strong correlations between the reflection coefficient and the impact response of the stiffened cylindrical shell structure. The findings demonstrate that increased material strain rate enhances the reflection coefficient. For the studied structure at the explosion point with a detonator radius of 1.77R0, the reflection coefficient δ ranges from approximately 1.3∼1.4 under s mall plastic deformation conditions and 1.4∼1.7 under large plastic indentation deformation conditions. Variations in the wall pressure reflection coefficient under different damage characteristics significantly affect the spatial characteristics of the impact response, providing a foundation for damage assess ment and anti-impact protection design of stiffened cylindrical shell structures under underwater explosion loads.

本文研究了介质界面水下爆炸载荷作用下受壁反射、衍射、干涉等复杂流固耦合现象影响的加强型薄壁圆柱壳结构内壁压力特性及压力反射系数的演化机理。基于材料应变率效应，从理论上分析了壁压反射系数的动态演化机理。通过弹性变形试验，探讨了不同损伤特征对加筋圆柱壳结构壁压时域特征及其反射系数的影响。为了进一步研究系统参数对壁面压力的影响，对具有塑性小变形和塑性压痕大变形的情况进行了数值模拟。研究了不同载荷参数下爆炸点壁面压力反射系数的动态演化规律。基于荷载参数和结构特征参数，推导出了壁压反射系数的半经验公式，揭示了反射系数与加筋圆柱壳结构的冲击响应之间存在较强的相关性。结果表明，材料应变速率的增大使反射系数增大。对于所研究的雷 管半径为1.77R0的爆炸点结构，反射系数δ在小塑性变形条件下约为1.3 ~ 1.4，在大塑性压痕变形条件下约为1.4 ~ 1.7。不同损伤特征下壁压反射系数的变化显著影响了冲击响应的空间特征，为水下爆炸荷载作用下加力圆柱壳结构的损伤评估和抗冲击防护设计提供了依据。

A Data-Driven Framework for Real-Time Failure Prediction in Adhesively Bonded Composite Joint with Acoustic Emission Data

Qian Li, Zongyang Liu, Dingcheng Ji, Tian Zhang, Yi Xiong, Wenhao Li, Jing Lin

doi:10.1016/j.tws.2026.114489

基于声发射数据的粘接复合材料接头失效实时预测数据驱动框架

The susceptibility to internal damage of adhesively bonded structures necessitates real-time structural health monitoring (SHM). Existing acoustic emission (AE)-based SHM methods, lacking fracture process modeling and relying on traditional AE feature extraction, fail to quantify progressive damage. To address these limitations, this paper develops an AE-based real-time failure prediction framework. A damage indicator (DI) grounded in the cohesive zone model (CZM) is adopted within the finite element (FE) model, enabling a physically meaningful, robust, and consistent assess ment of failure risk across different types of joints. A Transformer-based deep learning model is developed to simultaneously predict both load and DI, allowing the extraction of deeper physical features from AE signals. The proposed framework is validated on two types of composite joints: single-lap joints with varying adhesive lengths and hybrid-bolted joints with a fixed adhesive length. It achieves lower root-mean-square errors (RMSEs) of 0.84 and 0.03 for load and DI predictions on the baseline signals, which are lower than those of benchmarks. SHapley Additive exPlanations (SHAP) an alysis further demonstrates that cumulative features play significant roles in damage prediction. This framework can serve as a basis for real-time SHM system and improved investigation of damage mechanis ms.

由于粘接结构内部损伤的易损性，需要对其进行实时结构健康监测。现有的基于声发射（AE）的SHM方法缺乏裂缝过程建模，依赖于传统的声发射特征提取，无法量化渐进损伤。为了解决这些限制，本文开发了一个基于ae的实时故障预测框架。在有限元（FE）模型中采用了基于内聚区模型（CZM）的损伤指示器（DI），从而实现了对不同类型节点的失效风险进行物理上有意义的、稳健的、一致的评估。基于变压器的深度学习模型可以同时预测负载和DI，从而从声发射信号中提取更深层次的物理特征。在两种不同粘结长度的单搭接和固定粘结长度的混合螺栓连接上验证了所提出的框架。对于基线信号的负载和DI预测，它实现了较低的均方根误差（rmse），分别为0.84和0.03，低于基准测试。SHapley加性解释（SHAP）分析进一步证明了累积特征在损伤预测中具有重要作用。该框架可作为实时SHM系统和改进损伤机理研究的基础。