作者：
Tao Li*;Yongfei Lin;Ling Zeng;Xiaowei Tang;Gang Yang;...
期刊：
Soil Dynamics and Earthquake Engineering,2026年200:109721 ISSN：0267-7261
通讯作者：
Tao Li
作者机构：
Key Laboratory of Safety Control of Bridge Engineering, Ministry of Education, Changsha University of Science & Technology, Changsha, China;[Ling Zeng] School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha, China;[Xiaowei Tang; Gang Yang] State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian, China;[Shun Liu] China Institute of Water Resources and Hydropower Research, Beijing, China;[Tao Li; Yongfei Lin] Key Laboratory of Safety Control of Bridge Engineering, Ministry of Education, Changsha University of Science & Technology, Changsha, China<&wdkj&>School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha, China
通讯机构：
[Tao Li] K;Key Laboratory of Safety Control of Bridge Engineering, Ministry of Education, Changsha University of Science & Technology, Changsha, China<&wdkj&>School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha, China
摘要：
Static liquefaction will occur in saturated sand-clay mixtures under static loading. Understanding the mechanical behavior of sand-clay mixtures is crucial for evaluating its safety and stability. Through a series of isotropically consolidated undrained triaxial compression tests (CU), the effect of clay content (CC) on static shear strength of sand-clay mixtures were studied under constant sand skeleton void ratio (e s ). Test results demonstrate that static liquefaction happened for specimens with CC = 0 % (pure sand), 3 %, 5 %, 7 %, and 10 % under different confining pressures. By contrast, no static liquefaction occurred for specimens with CC = 12 % and 15 %. When CC = 0 %∼15 %, the peak deviator stress (q peak ) and mean effective stress at the steady state (p ss ') of corresponding specimens raise 305.6 %, 94.4 % and 97.6 % as well as 114.1 %, 987.9 % and 266.2 % under three different confining pressures, respectively. In addition, the microscopic characteristics of sand-clay mixtures with various clay contents were observed. It can be found that when CC ≤ 10 %, the clay particles primarily filled in the inter-sand voids, distributed on the surfaces of sand particles and located at the sand-sand contact points. And these clay particles can lubricate and bond sand particles, which can promote the liquefaction of mixed soil. The bonding effect of clay on sand is further enhanced when CC = 12 % and 15 %, and clay play an inhibitory role in the liquefaction of sand. Finally, a calculation equation of clay participation coefficient was proposed in current study, which can consider the effect of content, particle size and plasticity index of clay on the mechanical properties of sand-clay mixtures. The equation demonstrates excellent fitting results for both steady state data and cyclic stress ratio data in the present study and relevant literature.
Static liquefaction will occur in saturated sand-clay mixtures under static loading. Understanding the mechanical behavior of sand-clay mixtures is crucial for evaluating its safety and stability. Through a series of isotropically consolidated undrained triaxial compression tests (CU), the effect of clay content (CC) on static shear strength of sand-clay mixtures were studied under constant sand skeleton void ratio (e s ). Test results demonstrate that static liquefaction happened for specimens with CC = 0 % (pure sand), 3 %, 5 %, 7 %, and 10 % under different confining pressures. By contrast, no static liquefaction occurred for specimens with CC = 12 % and 15 %. When CC = 0 %∼15 %, the peak deviator stress (q peak ) and mean effective stress at the steady state (p ss ') of corresponding specimens raise 305.6 %, 94.4 % and 97.6 % as well as 114.1 %, 987.9 % and 266.2 % under three different confining pressures, respectively. In addition, the microscopic characteristics of sand-clay mixtures with various clay contents were observed. It can be found that when CC ≤ 10 %, the clay particles primarily filled in the inter-sand voids, distributed on the surfaces of sand particles and located at the sand-sand contact points. And these clay particles can lubricate and bond sand particles, which can promote the liquefaction of mixed soil. The bonding effect of clay on sand is further enhanced when CC = 12 % and 15 %, and clay play an inhibitory role in the liquefaction of sand. Finally, a calculation equation of clay participation coefficient was proposed in current study, which can consider the effect of content, particle size and plasticity index of clay on the mechanical properties of sand-clay mixtures. The equation demonstrates excellent fitting results for both steady state data and cyclic stress ratio data in the present study and relevant literature.
摘要：
With the increase of the density of subway line in big cities, it is common for newly built shield tunnels to cross beneath the existing pile foundations at short distances. When the disturbance generated during the construction of the shield tunnels is transmitted to the bearing stratum of the existing pile tip, a punching shear failure may occur in the bearing stratum. To study the evolution process and final form of the punching shear failure of the bearing stratum, a scaled model test based on the Particle Image Velocimetry (PIV) technology is designed. By using PIV technology to analyze deformation images of the bearing stratum, the failure range and shape of the bearing stratum between the pile tip and tunnel induced by excavation are obtained. Using the failure shape of the bearing stratum provided by the model test, a theoretical failure mechanism based on the spatial discretization technique is constructed. The limit analysis theorem is employed here to calculate the theoretical solution of the punching shear failure surface of the bearing stratum. The good agreement of the failure range for the bearing stratum between the model test and theoretical result indicates that the model test presented here is effective.
With the increase of the density of subway line in big cities, it is common for newly built shield tunnels to cross beneath the existing pile foundations at short distances. When the disturbance generated during the construction of the shield tunnels is transmitted to the bearing stratum of the existing pile tip, a punching shear failure may occur in the bearing stratum. To study the evolution process and final form of the punching shear failure of the bearing stratum, a scaled model test based on the Particle Image Velocimetry (PIV) technology is designed. By using PIV technology to analyze deformation images of the bearing stratum, the failure range and shape of the bearing stratum between the pile tip and tunnel induced by excavation are obtained. Using the failure shape of the bearing stratum provided by the model test, a theoretical failure mechanism based on the spatial discretization technique is constructed. The limit analysis theorem is employed here to calculate the theoretical solution of the punching shear failure surface of the bearing stratum. The good agreement of the failure range for the bearing stratum between the model test and theoretical result indicates that the model test presented here is effective.
作者：
Zhang, Liang;Jiang, Hao;Zhang, Sheng;Bei, Zhenghao;Huang, Ning
期刊：
Measurement,2025年253:117561 ISSN：0263-2241
通讯作者：
Jiang, H
作者机构：
[Zhang, Liang; Huang, Ning; Zhang, Sheng] Hunan City Univ, Coll Civil Engn, 518 Yingbin East Rd, Yiyang 413000, Hunan, Peoples R China.;[Bei, Zhenghao; Jiang, Hao] Changsha Univ Sci & Technol, Sch Civil Engn, 960 Wanjiali South RD, Changsha 410114, Hunan, Peoples R China.
通讯机构：
[Jiang, H ] C;Changsha Univ Sci & Technol, Sch Civil Engn, 960 Wanjiali South RD, Changsha 410114, Hunan, Peoples R China.
关键词：
Tunnel lining detection;Cavity filler;Forward simulation;Generalized S -transform;Wavelet packet analysis
摘要：
Tunnel lining cavities and other defects can cause cracks in tunnel structures and damage to concrete, seriously affecting the safety of driving in tunnels. Due to varying geological conditions, the materials filling different cavity areas in tunnels differ. By formulating corresponding repair measures for different fillers in cavity areas, many unnecessary losses can be avoided. Therefore, this paper proposes a method based on multi-parameter information for identifying and extracting the characteristics of different fillers in tunnel cavity areas through forward simulation using gprMax software and field test analysis. Ground penetrating radar (GPR) is used to detect cavities of different shapes filled with various media, focusing on cavity signals while reducing interference from I-beams, and reconstructing radar signals through migration. Statistical parameters are introduced for analysis, and techniques such as Fast Fourier Transform, generalized S-transform, and wavelet packet transform are employed to extract features from the processed radar signals. The characteristics of the filling medium in the cavity area are extracted from three aspects: frequency, time–frequency, and energy. This method can provide a reference for interpreting the GPR data of tunnel lining cavity filling media in actual engineering applications.
Tunnel lining cavities and other defects can cause cracks in tunnel structures and damage to concrete, seriously affecting the safety of driving in tunnels. Due to varying geological conditions, the materials filling different cavity areas in tunnels differ. By formulating corresponding repair measures for different fillers in cavity areas, many unnecessary losses can be avoided. Therefore, this paper proposes a method based on multi-parameter information for identifying and extracting the characteristics of different fillers in tunnel cavity areas through forward simulation using gprMax software and field test analysis. Ground penetrating radar (GPR) is used to detect cavities of different shapes filled with various media, focusing on cavity signals while reducing interference from I-beams, and reconstructing radar signals through migration. Statistical parameters are introduced for analysis, and techniques such as Fast Fourier Transform, generalized S-transform, and wavelet packet transform are employed to extract features from the processed radar signals. The characteristics of the filling medium in the cavity area are extracted from three aspects: frequency, time–frequency, and energy. This method can provide a reference for interpreting the GPR data of tunnel lining cavity filling media in actual engineering applications.
摘要：
The theory of dynamic reliability, predicated on the first excursion failure criterion, holds significant importance in the domains of seismic and wind resistance of structures, as well as in the assessment of the reliability of machinery and airplanes. This theoretical framework offers a mathematical description of failure probabilities, which serve as critical indicators for the safety evaluations of dynamic systems. However, dynamical systems such as large structures, machines or airplanes are composed of numerous members and nodes that may be influenced by uncertainties related to loads, geometric imperfections, and material properties. The inherent high-dimensional randomness and pronounced nonlinear coupling effects contribute to the complexity and implicit nature of the system failure modes in these systems. Consequently, the computation of the first excursion probability for complex dynamical systems presents a formidable challenge that necessitates comprehensive investigation. To summarize the current methodologies, this paper delineates a state-of-the-art review of dynamic reliability theory, with a particular emphasis on its potential to address the first excursion probability in dynamical systems.
The theory of dynamic reliability, predicated on the first excursion failure criterion, holds significant importance in the domains of seismic and wind resistance of structures, as well as in the assessment of the reliability of machinery and airplanes. This theoretical framework offers a mathematical description of failure probabilities, which serve as critical indicators for the safety evaluations of dynamic systems. However, dynamical systems such as large structures, machines or airplanes are composed of numerous members and nodes that may be influenced by uncertainties related to loads, geometric imperfections, and material properties. The inherent high-dimensional randomness and pronounced nonlinear coupling effects contribute to the complexity and implicit nature of the system failure modes in these systems. Consequently, the computation of the first excursion probability for complex dynamical systems presents a formidable challenge that necessitates comprehensive investigation. To summarize the current methodologies, this paper delineates a state-of-the-art review of dynamic reliability theory, with a particular emphasis on its potential to address the first excursion probability in dynamical systems.
摘要：
This study investigates the coupled responses between the alongwind and acrosswind directions of a variable cross-section bridge tower model through wind tunnel experiments. Uniform and two turbulent flows with four different wind directions are designed to study their influences. The results show a significant coupling effect between the alongwind and acrosswind responses, influenced by incoming flow conditions and structure damping. In uniform flow, two distinct vortex-induced vibration (VIV) regions are observed when the structural damping is low, possibly due to the variable cross-section. When coupled VIV occurs, the responses of both alongwind and acrosswind directions show a hardening non-Gaussian distribution, and the kurtosis value is close to 1.5. The increase of structural damping will weaken the coupling effect, but slightly increase the dominant frequency of the coupling. Turbulence intensity reduces the VIV effect and coupling effect but does not eliminate the coupling in galloping. In particular, the critical wind speed of galloping will decrease with the increase of turbulence intensity. The coupling effect is prominent at 0° wind direction, mainly dominated by the acrosswind direction. However, the coupling effect is weak in other wind directions and is primarily dominated by the alongwind direction. The coupling effect makes the energy transfer between the alongwind and acrosswind directions, which is crucial for designing variable cross-section high-rise buildings and tower structures susceptible to wind-induced vibration.
This study investigates the coupled responses between the alongwind and acrosswind directions of a variable cross-section bridge tower model through wind tunnel experiments. Uniform and two turbulent flows with four different wind directions are designed to study their influences. The results show a significant coupling effect between the alongwind and acrosswind responses, influenced by incoming flow conditions and structure damping. In uniform flow, two distinct vortex-induced vibration (VIV) regions are observed when the structural damping is low, possibly due to the variable cross-section. When coupled VIV occurs, the responses of both alongwind and acrosswind directions show a hardening non-Gaussian distribution, and the kurtosis value is close to 1.5. The increase of structural damping will weaken the coupling effect, but slightly increase the dominant frequency of the coupling. Turbulence intensity reduces the VIV effect and coupling effect but does not eliminate the coupling in galloping. In particular, the critical wind speed of galloping will decrease with the increase of turbulence intensity. The coupling effect is prominent at 0° wind direction, mainly dominated by the acrosswind direction. However, the coupling effect is weak in other wind directions and is primarily dominated by the alongwind direction. The coupling effect makes the energy transfer between the alongwind and acrosswind directions, which is crucial for designing variable cross-section high-rise buildings and tower structures susceptible to wind-induced vibration.
摘要：
A new method was proposed for predicting residual stress in light alloys using truncated conical indentation. In this method, a truncated conical indenter with a cone angle of 120°, insensitive to edge-chamfer and friction effects, was used to test the residual stress of light alloys. Selecting the ratio of indentation work between stressed and unstressed specimens as an analytical parameter, a dimensionless truncated conical indentation (TCI) model related to the ratio of indentation work between stressed and unstressed, material properties, and normalized residual stress was established via dimensional analysis and numerical calculations. The TCI model could predict equi-biaxial residual stress and uniaxial residual stress, and its accuracy was verified in a wide range of light alloys with varying residual stress by numerical simulation. The stability of the TCI model is verified numerically by introducing errors in material parameters. Truncated conical indentation tests were conducted on cruciform specimens and rectangular specimens respectively made of three aluminum alloys. The results exhibited the residual stress predicted by proposed method agrees well with the applied stress, and the relative errors between them were within ±10 % in most cases.
A new method was proposed for predicting residual stress in light alloys using truncated conical indentation. In this method, a truncated conical indenter with a cone angle of 120°, insensitive to edge-chamfer and friction effects, was used to test the residual stress of light alloys. Selecting the ratio of indentation work between stressed and unstressed specimens as an analytical parameter, a dimensionless truncated conical indentation (TCI) model related to the ratio of indentation work between stressed and unstressed, material properties, and normalized residual stress was established via dimensional analysis and numerical calculations. The TCI model could predict equi-biaxial residual stress and uniaxial residual stress, and its accuracy was verified in a wide range of light alloys with varying residual stress by numerical simulation. The stability of the TCI model is verified numerically by introducing errors in material parameters. Truncated conical indentation tests were conducted on cruciform specimens and rectangular specimens respectively made of three aluminum alloys. The results exhibited the residual stress predicted by proposed method agrees well with the applied stress, and the relative errors between them were within ±10 % in most cases.
作者：
Fu, Z. H.;Zhang, W.*;Zhang, Y. F.;Chen, H.;Amer, A.
期刊：
International Journal of Mechanical Sciences,2025年303:110616 ISSN：0020-7403
通讯作者：
Zhang, W.;Zhang, Y
作者机构：
[Amer, A.; Fu, Z. H.; Zhang, Y. F.; Zhang, W.] GuangXi Univ, Dept Mech, Nanning 530004, Peoples R China.;[Amer, A.; Fu, Z. H.; Zhang, Y. F.; Zhang, W.] GuangXi Univ, State Key Lab Featured Met Mat & Life Cycle Safety, Nanning 530004, Peoples R China.;[Chen, H.] Changsha Univ Sci & Technol, Sch Civil & Environm Engn, Changsha 410114, Peoples R China.;[Amer, A.] Menoufia Univ, Fac Sci, Dept Math & Comp Sci, Shibin Al Kawm, Egypt.
通讯机构：
[Zhang, W; Zhang, Y ] G;GuangXi Univ, Dept Mech, Nanning 530004, Peoples R China.;GuangXi Univ, State Key Lab Featured Met Mat & Life Cycle Safety, Nanning 530004, Peoples R China.
关键词：
Mechanical behavior;Twisted bilayer graphene;Titanium matrix;Nanocomposites;Tensile and shear;Molecular dynamics simulation
摘要：
This study investigates the mechanical behavior of twisted bilayer graphene (TBLG) and its reinforced titanium matrix nanocomposites (TBLG-RT) through molecular dynamics (MD) simulations. Young's modulus and shear modulus of TBLG are systematically calculated for the first time, across twist angles from 0° to 30° with 1° increments. Our results demonstrate that while Young's modulus exhibits minimal angular fluctuations, tensile strength displays anisotropic behavior: decreasing in the zigzag direction yet increasing in the armchair direction with larger twist angles. Furthermore, the shear moduli show negligible angular dependence across the studied range. A critical finding is that TBLG manifests transversely isotropic material properties at a critical twist angle of approximately 29°∼30°. Consequently, TBLG with a 29.96° twist configuration is selected for titanium reinforcement in uniaxial tensile and shear simulations. and the TBLG with twist angles of 6.01° and 12.90° are used to verify the angle independence of TBLG-RT. The MD simulations reveal that even minimal TBLG volume fractions induce substantial mechanical property enhancements compared to pure titanium. However, significant discrepancies emerge between conventional micromechanical models (Rule of Mixtures and Halpin-Tsai) and MD-derived results at higher reinforcement fractions. To address this divergence, we propose modified versions of these models calibrated against MD simulation data, enabling more accurate predictions of TBLG-RT composite performance. Furthermore, the modified micromechanical models establish a computational framework for tailoring graphene-reinforced composites across length scales, bridging quantum-scale MD insights with macroscopic engineering applications.
This study investigates the mechanical behavior of twisted bilayer graphene (TBLG) and its reinforced titanium matrix nanocomposites (TBLG-RT) through molecular dynamics (MD) simulations. Young's modulus and shear modulus of TBLG are systematically calculated for the first time, across twist angles from 0° to 30° with 1° increments. Our results demonstrate that while Young's modulus exhibits minimal angular fluctuations, tensile strength displays anisotropic behavior: decreasing in the zigzag direction yet increasing in the armchair direction with larger twist angles. Furthermore, the shear moduli show negligible angular dependence across the studied range. A critical finding is that TBLG manifests transversely isotropic material properties at a critical twist angle of approximately 29°∼30°. Consequently, TBLG with a 29.96° twist configuration is selected for titanium reinforcement in uniaxial tensile and shear simulations. and the TBLG with twist angles of 6.01° and 12.90° are used to verify the angle independence of TBLG-RT. The MD simulations reveal that even minimal TBLG volume fractions induce substantial mechanical property enhancements compared to pure titanium. However, significant discrepancies emerge between conventional micromechanical models (Rule of Mixtures and Halpin-Tsai) and MD-derived results at higher reinforcement fractions. To address this divergence, we propose modified versions of these models calibrated against MD simulation data, enabling more accurate predictions of TBLG-RT composite performance. Furthermore, the modified micromechanical models establish a computational framework for tailoring graphene-reinforced composites across length scales, bridging quantum-scale MD insights with macroscopic engineering applications.
摘要：
Traditional physical-driven modal methods are inappropriate for damage diagnosis of long-span flexible structures with complex mechanical behaviour. This study develops a deep Convolutional Neural Network-based damage diagnosis method for in-service bridges by using dynamic responses under moving loads. The dynamic responses were collected from the critical points on the girders of a cable-stayed bridge specimen under vehicle loading. These collected data was transformed into images based on Gramian Angular Field and Markov Transition Field (MTF). A deep learning algorithm based on VGG-19 was used to extract the damage feature from the data images associated with the structural responses. Finally, the unlabelled vibration data were input into the VGG-19 model for structural damage diagnosis. An experimental study was conducted for the damage diagnosis of a scale specimen of a cable-stayed bridge under moving loads. The acceleration signals of the main girder of the cable-stayed bridge under several damage conditions were monitored. The numerical results show the training accuracy of the deep learning method based on VGG-19 with MTF is up to 88%, and the average accuracy of the test dataset is 86.46% for each classification label. The transfer learning method can increase the classification accuracy up to 97.89%, indicating the advantage of intergrating transfer learning and VGG-19 network for structural damage diagnosis. The combination of VGG-19 and MTF algorithm provides a better solution for structural damage diagnosis of in-service infrastructures with long-term monitoring data.
作者机构：
[Han, Yanqun] School of Civil Engineering, Central South University, Changsha 410075, Hunan, PR China;[Peng, Xulong] School of Civil Engineering, Changsha University of Science and Technology, Changsha 410114, Hunan, PR China
通讯机构：
[Xulong Peng] S;School of Civil Engineering, Changsha University of Science and Technology, Changsha 410114, Hunan, PR China
关键词：
Approximate temperature;Convective-radiative fin;Fin efficiency;Nonlinear heat transfer problem;Temperature-dependent thermal conductivity
摘要：
This article studies the thermal performance of a moving fin with temperature-dependent thermal conductivity in a convective and radiative environment. It corresponds to a nonlinear heat transfer problem related to the nonlinear ordinary differential equation (NODE) for the unknown temperature excess. The NODE is solved by converting it to a nonlinear Fredholm integral equation. An approximate temperature distribution is determined in the quadratic form for arbitrary values of the Biot and Peclet numbers. A comparison of our results with the previous ones indicates satisfactory accuracy of the obtained solution. The fin efficiency is also given explicitly in terms of prescribed parameters and calculated numerically. The heat dissipation to the surrounding medium due to convection and radiation is analyzed for various speeds of a moving fin. The influences of thermal conductivity, heat convection, radiation, and moving speed of the fin on the temperature distribution and thermal performance are elucidated.
This article studies the thermal performance of a moving fin with temperature-dependent thermal conductivity in a convective and radiative environment. It corresponds to a nonlinear heat transfer problem related to the nonlinear ordinary differential equation (NODE) for the unknown temperature excess. The NODE is solved by converting it to a nonlinear Fredholm integral equation. An approximate temperature distribution is determined in the quadratic form for arbitrary values of the Biot and Peclet numbers. A comparison of our results with the previous ones indicates satisfactory accuracy of the obtained solution. The fin efficiency is also given explicitly in terms of prescribed parameters and calculated numerically. The heat dissipation to the surrounding medium due to convection and radiation is analyzed for various speeds of a moving fin. The influences of thermal conductivity, heat convection, radiation, and moving speed of the fin on the temperature distribution and thermal performance are elucidated.
通讯机构：
[Zhou, H ] C;Changsha Univ Sci & Technol, Sch Civil Engn, Changsha 410114, Peoples R China.
关键词：
3D printed concrete;Interlayer interlocking;Theoretical analysis;Failure mode;Tensile strength;Tensile stress-strain curve
摘要：
Interlocking 3D printed concrete printed by tooth-like nozzles exhibits superior interfacial tensile performance. However, the influences of geometric parameters on the interlayer tensile strength of interlocking specimens remains unclear, and there is an urgent need to establish formulas to quantify the influences. To address these issues, this study, based on a novel single-tooth nozzle designed to enhance interlayer performance, comprehensively considers macro-mechanical performance testing and micro-porosity analysis. It reveals the failure modes of interlayer interfacial tension in single-tooth interlocking 3D printed concrete and proposes the tensile strength calculation formulas. Firstly, the theoretical analysis of the interlayer interfacial tensile strength of 3D printed concrete was performed. Then, conducted uniaxial tensile tests and validation experiments, and confirmed the validity of the theoretical formulas. Finally, the stress-strain curves of interlayer interlocking specimens with different single-tooth angles were analyzed. The results indicate that: (1) The interlayer interfacial tensile strength of interlocking 3D printed concrete with single-tooth nozzle is higher than that with square nozzles. (2) The failure cracks of specimens with square nozzle propagated horizontally in a straight line, while those of single-tooth interlocking specimens exhibited a serrated pattern along the interlocking interface. (3) The interlayer interfacial tensile strength formulas can effectively estimate the interlayer interfacial tensile strength of single-tooth interlocking 3D printed concrete. These findings provide methods and empirical insights for subsequent theoretical analysis and the establishment of calculation formulas for the strength of interlocking 3D printed concrete.
Interlocking 3D printed concrete printed by tooth-like nozzles exhibits superior interfacial tensile performance. However, the influences of geometric parameters on the interlayer tensile strength of interlocking specimens remains unclear, and there is an urgent need to establish formulas to quantify the influences. To address these issues, this study, based on a novel single-tooth nozzle designed to enhance interlayer performance, comprehensively considers macro-mechanical performance testing and micro-porosity analysis. It reveals the failure modes of interlayer interfacial tension in single-tooth interlocking 3D printed concrete and proposes the tensile strength calculation formulas. Firstly, the theoretical analysis of the interlayer interfacial tensile strength of 3D printed concrete was performed. Then, conducted uniaxial tensile tests and validation experiments, and confirmed the validity of the theoretical formulas. Finally, the stress-strain curves of interlayer interlocking specimens with different single-tooth angles were analyzed. The results indicate that: (1) The interlayer interfacial tensile strength of interlocking 3D printed concrete with single-tooth nozzle is higher than that with square nozzles. (2) The failure cracks of specimens with square nozzle propagated horizontally in a straight line, while those of single-tooth interlocking specimens exhibited a serrated pattern along the interlocking interface. (3) The interlayer interfacial tensile strength formulas can effectively estimate the interlayer interfacial tensile strength of single-tooth interlocking 3D printed concrete. These findings provide methods and empirical insights for subsequent theoretical analysis and the establishment of calculation formulas for the strength of interlocking 3D printed concrete.
通讯机构：
[Wang, L ] C;Changsha Univ Sci & Technol, Sch Civil Engn, Changsha 410114, Hunan, Peoples R China.
关键词：
Bond strength;Steel fiber reinforce concrete;Machine learning;Genetic algorithm;Gaussian noise;SHAP
摘要：
The bond behavior between steel fiber reinforced concrete (SFRC) and steel rebars significantly influences both serviceability and seismic performance of structures. Accurate prediction of bond strength remains challenging due to the various influencing factors and limitations inherent in experimental data acquisition. To address this challenge, an explainable machine learning-based approach is proposed in the present study to predict the bond strength. A comprehensive dataset is developed incorporating seven key parameters: fiber slenderness ratio, steel fiber length, fiber volume fraction, concrete compressive strength, rebar diameter, cover-to-diameter ratio and bond length-to-diameter ratio. The dataset is categorized into two subsets based on the test methodologies: pullout set and beam bending set. Eight machine learning models are optimized through genetic algorithms (GA) using the pullout set, followed by rigorous evaluation through robustness testing and comparative analysis against established baseline models. Model interpretability is enhanced through Shapley Additive Explanation (SHAP) analysis and partial dependence plot (PDP) visualizations. The effects of different parameters on bond strength between steel rebar and SFRC are clarified. The results show that the GA-optimized XGBoost model achieved superior predictive performance, with R² values of 0.9505 (training set) and 0.9477 (test set), corresponding to RMSE values of 1.1064 MPa and 1.1504 MPa respectively. Model predictions for beam bending tests revealed systematic method discrepancies. SHAP analysis revealed concrete strength, rebar diameter, and cover-to-diameter ratio as the most influential parameters governing bond behavior.
The bond behavior between steel fiber reinforced concrete (SFRC) and steel rebars significantly influences both serviceability and seismic performance of structures. Accurate prediction of bond strength remains challenging due to the various influencing factors and limitations inherent in experimental data acquisition. To address this challenge, an explainable machine learning-based approach is proposed in the present study to predict the bond strength. A comprehensive dataset is developed incorporating seven key parameters: fiber slenderness ratio, steel fiber length, fiber volume fraction, concrete compressive strength, rebar diameter, cover-to-diameter ratio and bond length-to-diameter ratio. The dataset is categorized into two subsets based on the test methodologies: pullout set and beam bending set. Eight machine learning models are optimized through genetic algorithms (GA) using the pullout set, followed by rigorous evaluation through robustness testing and comparative analysis against established baseline models. Model interpretability is enhanced through Shapley Additive Explanation (SHAP) analysis and partial dependence plot (PDP) visualizations. The effects of different parameters on bond strength between steel rebar and SFRC are clarified. The results show that the GA-optimized XGBoost model achieved superior predictive performance, with R² values of 0.9505 (training set) and 0.9477 (test set), corresponding to RMSE values of 1.1064 MPa and 1.1504 MPa respectively. Model predictions for beam bending tests revealed systematic method discrepancies. SHAP analysis revealed concrete strength, rebar diameter, and cover-to-diameter ratio as the most influential parameters governing bond behavior.
摘要：
Orthotropic steel decks (OSDs) are welded structures prone to weld defects, increasing the risk of fatigue fracture. It is crucial to clarify the fatigue evolution mechanism of weld defects throughout the entire lifecycle. In this study, the fatigue propagation behavior of weld defects is investigated from the hidden stage to final fracture. Firstly, a full-scale segmental OSD model with prefabricated defects was utilized to investigated fatigue propagation behavior of surface cracks. Secondly, stress intensity factors (SIFs) of welding defects throughout the entire process were simulated using a refined finite element model. Finally, the crack shape evolution and fatigue life were analyzed at different fatigue stages. The research identifies three stages in the fatigue evolution of hidden defects: the hidden defect stage, the initiation stage of surface crack, and the propagation stage of surface crack. Regardless of the initial aspect ratios, hidden defects evolve into a circular, while surface defects evolve into a flattened semi-ellipse. Compared to the propagation life of surface cracks, the hiding life of cracks account for a significantly larger proportion of the total life, and this proportion increases with both the initial aspect ratio and the hidden depth of the defects.
Orthotropic steel decks (OSDs) are welded structures prone to weld defects, increasing the risk of fatigue fracture. It is crucial to clarify the fatigue evolution mechanism of weld defects throughout the entire lifecycle. In this study, the fatigue propagation behavior of weld defects is investigated from the hidden stage to final fracture. Firstly, a full-scale segmental OSD model with prefabricated defects was utilized to investigated fatigue propagation behavior of surface cracks. Secondly, stress intensity factors (SIFs) of welding defects throughout the entire process were simulated using a refined finite element model. Finally, the crack shape evolution and fatigue life were analyzed at different fatigue stages. The research identifies three stages in the fatigue evolution of hidden defects: the hidden defect stage, the initiation stage of surface crack, and the propagation stage of surface crack. Regardless of the initial aspect ratios, hidden defects evolve into a circular, while surface defects evolve into a flattened semi-ellipse. Compared to the propagation life of surface cracks, the hiding life of cracks account for a significantly larger proportion of the total life, and this proportion increases with both the initial aspect ratio and the hidden depth of the defects.
摘要：
Electrical resistivity tomography (ERT) is a key geophysical technique that provides detailed information on subsurface structures by measuring the distribution of electrical resistivity underground. ERT suffers from limitations in electrode arrangement, interference from environmental and instrument noise, and existing data processing algorithms that fail to adequately consider geological heterogeneity and uncertainty, resulting in insufficient inversion resolution. Traditional ERT methods rely on simplified algorithms and a limited number of observation points, which smooths model details and further reduces resolution. To address the resolution issues in ERT, this article proposes a deep learning inversion method that integrates prior physical information. This method uses low-resolution inversion results as prior knowledge to provide the deep learning algorithm with a constrained initial model, thereby combining the physical basis of traditional methods with the data-driven advantages of deep learning. The method not only retains the strengths of traditional inversion but also enhances the resolution and imaging efficiency of the inversion model using deep learning technology. Synthetic data experiments demonstrate that integrating deep learning significantly improves the model’s ability to detail subsurface structures, especially in the transition zones of shallow structures and the recovery of deep anomalies. Results from measured data indicate that the proposed method not only achieves high-resolution inversion but also maintains good consistency with prior information.
摘要：
Images captured under improper exposure conditions lose their brightness information and texture details. Therefore, the enhancement of low-light images has received widespread attention. In recent years, most methods are based on deep convolutional neural networks to enhance low-light images in the spatial domain, which tends to introduce a huge number of parameters, thus limiting their practical applicability. In this paper, we propose a Fourier-based two-stage low-light image enhancement method via mutual learning (FT-LLIE), which sequentially enhance the amplitude and phase components. Specifically, we design the amplitude enhancement module (AEM) and phase enhancement module (PEM). In these two enhancement stages, we design the amplitude enhancement block (AEB) and phase enhancement block (PEB) based on the Fast Fourier Transform (FFT) to deal with the amplitude component and the phase component, respectively. In AEB and PEB, we design spatial unit (SU) and frequency unit (FU) to process spatial and frequency domain information, and adopt a mutual learning strategy so that the local features extracted from the spatial domain and global features extracted from the frequency domain can learn from each other to obtain complementary information to enhance the image. Through extensive experiments, it has been shown that our network requires only a small number of parameters to effectively enhance image details, outperforming existing low-light image enhancement algorithms in both qualitative and quantitative results.
Images captured under improper exposure conditions lose their brightness information and texture details. Therefore, the enhancement of low-light images has received widespread attention. In recent years, most methods are based on deep convolutional neural networks to enhance low-light images in the spatial domain, which tends to introduce a huge number of parameters, thus limiting their practical applicability. In this paper, we propose a Fourier-based two-stage low-light image enhancement method via mutual learning (FT-LLIE), which sequentially enhance the amplitude and phase components. Specifically, we design the amplitude enhancement module (AEM) and phase enhancement module (PEM). In these two enhancement stages, we design the amplitude enhancement block (AEB) and phase enhancement block (PEB) based on the Fast Fourier Transform (FFT) to deal with the amplitude component and the phase component, respectively. In AEB and PEB, we design spatial unit (SU) and frequency unit (FU) to process spatial and frequency domain information, and adopt a mutual learning strategy so that the local features extracted from the spatial domain and global features extracted from the frequency domain can learn from each other to obtain complementary information to enhance the image. Through extensive experiments, it has been shown that our network requires only a small number of parameters to effectively enhance image details, outperforming existing low-light image enhancement algorithms in both qualitative and quantitative results.
摘要：
A damage assessment method for bridge suspender wires subjected to random variable loads is proposed using a subcycle corrosion fatigue crack growth (CFCG) model. The CFCG analysis is conducted by tracking crack tip opening displacement (CTOD) and crack tip plastic zone size in the time-series loading history. The coupling mechanism between corrosion pit growth and CFCG on a time scale is developed based on the rate competition principle. Following this, a corrosion fatigue life prediction model is established by integrating corrosion fatigue damage size including pit depth and crack length. The accuracy and efficiency of the proposed method are verified by experimental and finite element method (FEM) results. A case study is then conducted on the application of corrosion fatigue life prediction of suspender wires using in-situ monitoring data. The results show that the calculation results of the proposed model are in good agreement with experimental and FEM results, with the maximum life prediction error less than 9%. The proposed model can effectively address the problems of model distortion and low computational efficiency caused by cyclic load sequences reconstruction, and provide theoretical support for the damage assessment of bridge suspenders in service.
A damage assessment method for bridge suspender wires subjected to random variable loads is proposed using a subcycle corrosion fatigue crack growth (CFCG) model. The CFCG analysis is conducted by tracking crack tip opening displacement (CTOD) and crack tip plastic zone size in the time-series loading history. The coupling mechanism between corrosion pit growth and CFCG on a time scale is developed based on the rate competition principle. Following this, a corrosion fatigue life prediction model is established by integrating corrosion fatigue damage size including pit depth and crack length. The accuracy and efficiency of the proposed method are verified by experimental and finite element method (FEM) results. A case study is then conducted on the application of corrosion fatigue life prediction of suspender wires using in-situ monitoring data. The results show that the calculation results of the proposed model are in good agreement with experimental and FEM results, with the maximum life prediction error less than 9%. The proposed model can effectively address the problems of model distortion and low computational efficiency caused by cyclic load sequences reconstruction, and provide theoretical support for the damage assessment of bridge suspenders in service.
作者：
Zhenhao Zhang;Guoqing Wei;Zhe Zeng;Fengwei Teng
期刊：
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering,2025年11(3):031205 ISSN：2332-9017
通讯作者：
Zhang, ZH
作者机构：
[Guoqing Wei; Zhe Zeng; Fengwei Teng] School of Civil Engineering, Changsha University of Science & Technology , Changsha 410114, China;, Qinzhou 535011, China;School of Architecture Engineering, Beibu Gulf University , Changsha 410114, China;[Zhenhao Zhang] School of Civil Engineering, Changsha University of Science & Technology , Changsha 410114, China ;[Zhenhao Zhang] , Qinzhou 535011, China<&wdkj&>School of Architecture Engineering, Beibu Gulf University , Changsha 410114, China
关键词：
random waves;Wiener process;safety threshold;wave period;anti-overturning;capsizing probability
摘要：
This paper investigates the impact of threshold-crossing events on ship capsizing through a probabilistic model that predicts random wave heights. Utilizing statistical data from wave height observations, this paper proposes that random waves can be approximated and modeled using the Wiener process, employing autocorrelation function identification and probabilistic statistical verification methods. The threshold-crossing duration of a random wave is just the period of the wave exceeds a given threshold, which can reflect the frequency property of the stochastic sea waves. And the probability distribution of the period can theoretically be determined using the derived probability density function for the time interval between any two adjacent crossings of the Wiener process and a threshold. Based on the above theories, the capsizing probabilities of a civil ship sailing in different wave areas are analyzed under different safety thresholds considering certain ratios of the ship's intrinsic period and wave period. The research results can provide a reference for the anti-overturning design of the ships under the action of random waves.
摘要：
Internal damage imaging in concrete structures has consistently presented significant challenges as a complex multi-component material. To enhance the accuracy and efficiency of internal damage identification in concrete structures, an improved plane wave imaging technique based on the wavenumber algorithm is proposed in the paper. The introduction of the wavenumber algorithm provides a mathematical solution to the inverse problem for the assumed forward wave propagation model, which is more rigorous than the ray-based theory in mathematics. By comparing with the total focusing method and the conventional plane wave imaging technique, the proposed imaging technique exhibits significant advantages in imaging different types of damage in concrete structures. Subsequently, the 3D damage state of the simulated reinforcement steel debonding in concrete structures was reconstructed employing the proposed imaging technique. The enhanced imaging efficiency and optimized imaging quality settled the proposed imaging technique a promising candidate for future internal damage identification of concrete structures.
Internal damage imaging in concrete structures has consistently presented significant challenges as a complex multi-component material. To enhance the accuracy and efficiency of internal damage identification in concrete structures, an improved plane wave imaging technique based on the wavenumber algorithm is proposed in the paper. The introduction of the wavenumber algorithm provides a mathematical solution to the inverse problem for the assumed forward wave propagation model, which is more rigorous than the ray-based theory in mathematics. By comparing with the total focusing method and the conventional plane wave imaging technique, the proposed imaging technique exhibits significant advantages in imaging different types of damage in concrete structures. Subsequently, the 3D damage state of the simulated reinforcement steel debonding in concrete structures was reconstructed employing the proposed imaging technique. The enhanced imaging efficiency and optimized imaging quality settled the proposed imaging technique a promising candidate for future internal damage identification of concrete structures.
摘要：
The quantitative evaluation of bolt pre-load is crucial for the maintenance and prevention of accidents in bolt-connected structures. This study introduces the coda wave interferometry (CWI) method and the nonlinear coda wave interferometry (NCWI) method for quantitative evaluation of bolt pre-load. Experimental tests across three different scales of bolt pre-load changes were conducted on a bolt to compare the performances of CWI and NCWI in the quantitative evaluation of bolt pre-load. The results demonstrate that both CWI and NCWI can effectively characterize changes in bolt pre-load. For CWI, the relative velocity change (triangle v/v) exhibits a linear relationship with the bolt pre-load. Meanwhile, for NCWI, the effective nonlinear level, denoted as alpha Delta v / v \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\alpha }_{\Delta v/v}$$\end{document} , demonstrates a quadratic dependence on the bolt pre-load. In CWI, the calculation of triangle v/v is dependent on the correlation coefficient between the coda waves of signals before and after bolt pre-load changes. It is prone to failure when there are significant changes in bolt pre-load. Conversely, NCWI demonstrates enhanced robustness in evaluating bolt pre-load changes across a range of magnitudes.
摘要：
Bridge steel, frequently employed in cross-sea bridge construction, exhibits excellent weldability, superior strength, and toughness. The service life and stability of steel structures are influenced by the presence of corrosive ions within marine environments, necessitating an in-depth examination of the corrosion mechanisms affecting bridge steel. In this study, Q370qD bridge steel was subjected to heat treatment to evaluate the influence of microstructural variations on its corrosion behavior. The microstructure of untreated steel (alloy F) predominantly consists of granular ferrite. Subsequent high-temperature heat treatment induces a partial transformation in the steel microstructure (alloy A), yielding lath carbide-free bainite. Post-immersion tests show both alloy surfaces densely covered with γ - FeOOH , α - FeOOH , and a mixture of Fe 3 O 4 and Fe 2 O 3 . Over time, γ - FeOOH undergoes partial conversion into the more stable α - FeOOH form, enhancing the protective barrier against the matrix for both alloys. Alloy F exhibits a significant reduction in corrosion rate compared to alloy A. The proportion of α - FeOOH in alloy A initially decreases then increases with prolonged exposure, while in alloy F, it consistently rises. The corrosion resistance of alloy A surpasses that of alloy F, which is attributed to the lath-shaped carbide-free bainite’s effectiveness in obstructing Cl − penetration and thereby improving corrosion resistance.
作者机构：
[Long, Chengyun; Long, CY] South China Univ Technol, Shien Ming Wu Sch Intelligent Engn, Guangzhou 511442, Peoples R China.;[Cai, Zizheng; Zhao, Bing; Zhou, Weichao; He, Daji] Changsha Univ Sci & Technol, Sch Civil Engn, Dept Mech, Changsha 410114, Peoples R China.
通讯机构：
[Long, CY ] S;[Zhao, B ] C;South China Univ Technol, Shien Ming Wu Sch Intelligent Engn, Guangzhou 511442, Peoples R China.;Changsha Univ Sci & Technol, Sch Civil Engn, Dept Mech, Changsha 410114, Peoples R China.
摘要：
Accurate assessment of the thermal buckling behavior of microdevices is critical for the safe and secure operation of MEMS. However, the coupling of shearing and size effects on the thermal buckling of microbeams remains elusive and needs to be clarified. Here, we propose a theoretical model for the thermal buckling of microbeams that considers both the shearing and size effects, based on the modified gradient elasticity theory combined with the Timoshenko beam model. The explicit analytical forms of the deflection, the bending angle, the shearing angle and the critical buckling temperature rise are presented. The results show that the bending angle increases with the length/thickness ratio while the shearing angle decreases. It is confirmed that the shearing effect cannot be ignored in the thermal buckling of the doubly clamped microbeams with low aspect ratio. The size effect is captured in the thermal buckling of microbeams, which shows an increase in thermoelastic strength with the size reduction. The coupling effect on thermal buckling shows a weakening of the shearing effect by the size effect as the microbeam size decreases. This work could provide a theoretical reference for the design and monitoring of microdevices operating in high temperature environments.
