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 shear failure of concrete is a sudden brittle failure, which is difficult to be forewarned. To investigate the shear crack mechanisms in concrete, this study first systematic compared acoustic emission (AE) behavior during direct shear tests, compression shear tests (Z-shaped specimens), and three point bending shear tests. AE parameters (amplitude, cumulative count and energy), average frequency (AF)-rise time/amplitude (RA) analysis, K-means clustering, and b-value analysis were integrated to classify cracks and characterize damage progression. The correlation between the shear crack propagation mechanism of concrete and AE parameters was revealed. The AE activity during concrete shear failure was successfully characterized, providing valuable insights into the damage development and evolution processes. The research findings establish a quantitative framework for using AE technology to detect shear cracks and monitor real-time damage evolution in concrete structures.
作者：
Da Hu*;Xuejuan Xiang;Junjie Huang;Kai Qi;Yongsuo Li;...
期刊：
Journal of Pipeline Systems Engineering and Practice,2025年16(3):03125001 ISSN：1949-1190
通讯作者：
Da Hu
作者机构：
[Yongsuo Li] Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;[Xian Yang; Xiaoqiang Liang] Associate Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;[Kai Qi] Master’s Student, School of Civil Engineering, Univ. of South China, No. 28, Changsheng West Rd., Hengyang 421001, China;Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;[Xuejuan Xiang; Junjie Huang] Master’s Student, School of Civil Engineering, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China
通讯机构：
[Da Hu] P;Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China
关键词：
Rectangular top pipe tunnel;Experimental analysis method;Empirical formula method;Numerical simulation method;Theoretical analysis method
摘要：
The jacking force in the construction process of rectangular pipe jacking tunnels is characterized by its intermittent, discontinuous, and unstable nature. This force not only determines the speed of tunneling but also controls the rate at which soil stress is released, leading to deformation of the formation and land subsidence, thereby impacting the surrounding environment. To accurately calculate and predict the jacking force of rectangular pipe jacking tunnels, this study conducts a comprehensive investigation and analysis of relevant literature on the calculation methods employed both domestically and internationally. The calculation methods are categorized into four types: experimental analysis methods, numerical simulation methods, theoretical formula methods, and empirical formula methods. The research content of each of these methods is analyzed and organized, and the existing research is summarized in terms of its problems and shortcomings. Furthermore, suggestions for future research on the calculation method of the jacking force are proposed, aiming to provide a technical reference for the theoretical research and engineering practice of calculating and predicting the jacking force of rectangular pipe jacking tunnels.
摘要：
The existence of multiple cracks accelerates chloride ion penetration within damaged concrete, substantially shortening the lifespan of the structure. Therefore, this paper conducts an in-depth analysis of chloride migration mechanisms in cracked concrete subjected to multiple cracks under drying-wetting cycles. Firstly, a series of accelerated chloride diffusion experiments were conducted on prestressed concrete beams subjected to multiple cracks. The analysis examines how crack width, depth, and density affect chloride concentration distribution. Then, a chloride diffusion coefficient prediction model incorporating the effects of multiple cracks was established using the crack interaction function and verified through experimental data. Finally, this paper explored the distribution patterns of chloride concentration and convection zones in concrete subjected to multiple cracks under various environmental conditions. The experimental results showed that crack width exerts the strongest effect on chloride diffusion, followed by crack depth, while crack density has the smallest impact. At the same depth of diffusion, the chloride concentration in concrete specimens with crack width of 0.3 mm increased by 45 % and 25 % on average compared with those with crack width of 0.1 mm and 0.2 mm, respectively. The dry-wet time ratio and initial moisture saturation significantly affect chloride concentration distribution, with the depth of the convection zone showing a negative correlation with initial moisture saturation.
The existence of multiple cracks accelerates chloride ion penetration within damaged concrete, substantially shortening the lifespan of the structure. Therefore, this paper conducts an in-depth analysis of chloride migration mechanisms in cracked concrete subjected to multiple cracks under drying-wetting cycles. Firstly, a series of accelerated chloride diffusion experiments were conducted on prestressed concrete beams subjected to multiple cracks. The analysis examines how crack width, depth, and density affect chloride concentration distribution. Then, a chloride diffusion coefficient prediction model incorporating the effects of multiple cracks was established using the crack interaction function and verified through experimental data. Finally, this paper explored the distribution patterns of chloride concentration and convection zones in concrete subjected to multiple cracks under various environmental conditions. The experimental results showed that crack width exerts the strongest effect on chloride diffusion, followed by crack depth, while crack density has the smallest impact. At the same depth of diffusion, the chloride concentration in concrete specimens with crack width of 0.3 mm increased by 45 % and 25 % on average compared with those with crack width of 0.1 mm and 0.2 mm, respectively. The dry-wet time ratio and initial moisture saturation significantly affect chloride concentration distribution, with the depth of the convection zone showing a negative correlation with initial moisture saturation.
期刊：
Measurement Science And Technology,2025年36(4):046133 ISSN：0957-0233
通讯作者：
Zhang, S
作者机构：
[Zhang, Sheng] Hunan City Univ, Sch Management, Yiyang 413000, Hunan, Peoples R China.;[Zhang, Liang; Huang, Ning; Zhang, Sheng; Deng, Zongwei] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.;[Zhang, Liang; Zhang, Sheng; Deng, Zongwei] Hunan City Univ, Higher Educ Inst Hunan Prov, Key Lab Green Bldg & Intelligent Construct, Yiyang 413000, Hunan, Peoples R China.;[Chen, Qianqian] Hunan Commun Polytech, Inst Civil Engn, Changsha 410000, Hunan, Peoples R China.
通讯机构：
[Zhang, S ] H;Hunan City Univ, Sch Management, Yiyang 413000, Hunan, Peoples R China.;Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.;Hunan City Univ, Higher Educ Inst Hunan Prov, Key Lab Green Bldg & Intelligent Construct, Yiyang 413000, Hunan, Peoples R China.
关键词：
rock classification;wavelet scattering transform;support vector machine;sensitivity analysis;deep learning
摘要：
In geological exploration and tunnel/underground engineering, precise, rapid, and intelligent rock lithology identification is crucial. A wavelet scattering transform-support vector machine (WST-SVM) rock image classification method is proposed that combines WST with SVM to address the limitations of conventional convolutional neural networks reliant on annotated samples. The method extracts multi-scale features from rock images using WST and trains an SVM classifier, achieving superior performance in test accuracy, macro-average precision, recall, and F1-score on a dataset of six rock types. Parameter analysis reveals that increasing invariant scale, decomposition transformations, and quality factor enhances feature matrix dimensionality and computational time. This approach reduces the need for extensive annotated samples and provides a practical solution for improving the accuracy and efficiency of rock lithology identification in geological exploration and tunnel engineering.
期刊：
JOURNAL OF COMPUTING IN CIVIL ENGINEERING,2025年39(3):04025017 ISSN：0887-3801
通讯作者：
Hu, D
作者机构：
[Hu, Da; Li, Yongsuo; Hu, D] Hunan City Univ, Hunan Engn Res Ctr Struct Safety & Disaster Preven, 518 Yingbin East Rd, Yiyang 413000, Peoples R China.;[Weng, Xiaoxuan; Tan, Ze; Liu, Jing] Hunan City Univ, Coll Civil Engn, Yingbin East Rd, Yiyang 413000, Hunan, Peoples R China.;[Qi, Kai] Univ South China, Coll Civil Engn, Henyang 421001, Hunan, Peoples R China.
通讯机构：
[Hu, D ] H;Hunan City Univ, Hunan Engn Res Ctr Struct Safety & Disaster Preven, 518 Yingbin East Rd, Yiyang 413000, Peoples R China.
关键词：
Prediction of jacking force;Pipe jacking tunnel;Deep-learning;Convolutional neural network;Long-term and short-term memory network
摘要：
The advancement of computer technology has led to the increased utilization of new algorithms, such as machine learning, in various fields including underground engineering. The estimation of jacking force plays a critical role in the construction of rectangular jacked tunnels. Conventional prediction techniques often rely on empirical models and statistical analysis, posing challenges in accurately forecasting the jacking force for intricate tunnel structures. To overcome this obstacle, a method for predicting tunnel jacking force is proposed, which integrates a convolutional neural network (CNN) and long short-term memory network (LSTM). By utilizing geometric and operational parameters as inputs, the CNN extracts data features, which are subsequently inputted into the LSTM network for time-series modeling. This model effectively processes continuous jacking force data by comprehending the complex correlations within the data set, resulting in more precise predictions of future jacking force values. Comparative analysis with traditional methods such as the artificial neural network, single CNN model, and LSTM network demonstrates that the CNN-LSTM model significantly reduces prediction errors in tunnel jacking force estimation, thereby enhancing model accuracy. Consequently, the efficacy of the CNN-LSTM model has been validated, showcasing the benefits of employing deep-learning techniques for predicting jacking force in pipe jacking tunnel construction.
期刊：
International Journal for Numerical and Analytical Methods in Geomechanics,2025年 ISSN：0363-9061
通讯作者：
Ni, PP
作者机构：
[Liu, Jing; Liang, Xiaoqiang; Hu, Da; Li, Yongsuo] Hunan City Univ, Hunan Engn Res Ctr Struct Safety & Disaster Preven, Yiyang, Peoples R China.;[Xiang, Xuejuan; Liu, Jing; Liang, Xiaoqiang; Huang, Junjie; Hu, Da; Li, Yongsuo] Hunan City Univ, Sch Civil Engn, Yiyang, Peoples R China.;[Ni, Pengpeng; Ni, PP] Sun Yat sen Univ, Sch Civil Engn, State Key Lab Tunnel Engn, Guangzhou, Peoples R China.;[Ni, Pengpeng; Ni, PP] Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai, Peoples R China.
通讯机构：
[Ni, PP ] S;Sun Yat sen Univ, Sch Civil Engn, State Key Lab Tunnel Engn, Guangzhou, Peoples R China.;Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai, Peoples R China.
关键词：
box jacking tunnel;jacking force;soil arching effect;stress transfer
摘要：
During the construction of box jacking tunnel, stress transfer caused by the soil arching effect is an important factor, affecting the jacking force. This study proposes a jacking force prediction method for box jacking tunnels under the complete and incomplete soil arching effect in sandy soils, which is divided into three soil domains, i.e., an external stable region, an elastic arch, and an internal loosened body. Three-dimensional numerical analyses for box jacking tunnel at various cover depths are also investigated to show the stress changes in the soil around the tunnel and the evolution of soil arch formation. Finally, through theoretical derivation and case analysis, the ratio between the influence range of soil arching and the width of loosened soil, f 0 / f 0 f 1 f 1 ${{{f_0}} \mathord{/ {\vphantom {{{f_0}} {{f_1}}}} \kern-\nulldelimiterspace} {{f_1}}}$ , is found to increase with increasing the tunnel size and internal friction angle of soil. The f 0 / f 0 f 1 f 1 ${{{f_0}} \mathord{/ {\vphantom {{{f_0}} {{f_1}}}} \kern-\nulldelimiterspace} {{f_1}}}$ coefficient can be preliminarily determined to be approximately 1.4, with a marginal difference of 6.7% compared with the Terzaghi's proposal of 1.5. Results show that in sandy and silty soil strata, the proposed method outperforms the other methods, in terms of accuracy and adaptability. This study can serve as a theoretical reference for the design and construction of box jacking tunnels.
作者机构：
[Cheng, Xiaokang; Xiao, Junyi; Peng, Jianxin; Zhang, Jianren] Changsha Univ Sci & Technol, Sch Civil Engn, Key Lab Bridge Engn Safety Control, Dept Educ, Changsha 410114, Hunan, Peoples R China.;[Xiao, Junyi] Guangzhou Vocat Coll Technol & Business, Sch Emergency Technol, Guangzhou 511442, Guangdong, Peoples R China.;[Yang, Yiming] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.;[Dong, You] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Peoples R China.
通讯机构：
[Peng, JX ] C;[Yang, YM ] H;Changsha Univ Sci & Technol, Sch Civil Engn, Key Lab Bridge Engn Safety Control, Dept Educ, Changsha 410114, Hunan, Peoples R China.;Hunan City Univ, Sch Civil Engn, Yiyang 413000, Hunan, Peoples R China.
关键词：
Post-tensioned concrete structures;Chloride wet-dry environment;Performance degradation;Concrete creep;Prestress loss
摘要：
The shrinkage, creep of concrete, and relaxation of prestressing tendons lead to prestress loss in prestressed concrete (PC) structures under conventional environments. The prestress loss of PC structures is also affected by corrosive environments resulting from alternating wet and dry. Therefore, a new model for predicting prestress loss under alternating damp and dry chloride environments is proposed. The model considers the coupled effects of corrosion on concrete creep and the remaining cross-sectional area of steel reinforcement/prestressing tendons. A 300-day experimental study is conducted on a series of post-tensioned prestressed concrete beams subjected to a cyclic wet-dry corrosive environment to discuss prestress loss. The effectiveness of the model is verified through experimental results. The results indicate that the existing codes underestimate the long-term prestress loss of PC structures in corrosive environments. The proposed model can accurately predict the long-term prestress loss of PC beams. Compared with conventional environments, the creep coefficient of concrete under a dry-wet alternating corrosive environment increases by 15 %, resulting in a 12.4 % increase in the long-term prestress loss of the structure.
The shrinkage, creep of concrete, and relaxation of prestressing tendons lead to prestress loss in prestressed concrete (PC) structures under conventional environments. The prestress loss of PC structures is also affected by corrosive environments resulting from alternating wet and dry. Therefore, a new model for predicting prestress loss under alternating damp and dry chloride environments is proposed. The model considers the coupled effects of corrosion on concrete creep and the remaining cross-sectional area of steel reinforcement/prestressing tendons. A 300-day experimental study is conducted on a series of post-tensioned prestressed concrete beams subjected to a cyclic wet-dry corrosive environment to discuss prestress loss. The effectiveness of the model is verified through experimental results. The results indicate that the existing codes underestimate the long-term prestress loss of PC structures in corrosive environments. The proposed model can accurately predict the long-term prestress loss of PC beams. Compared with conventional environments, the creep coefficient of concrete under a dry-wet alternating corrosive environment increases by 15 %, resulting in a 12.4 % increase in the long-term prestress loss of the structure.
期刊：
Desalination and Water Treatment,2025年322:101161 ISSN：1944-3994
通讯作者：
Li, ZP
作者机构：
[Yin, Quan; Zhou, Yi; Li, Zhiping] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Peoples R China.;[Yin, Quan; Zhou, Yi; Li, Zhiping] Hunan City Univ, Hunan Engn Res Ctr Struct Safety & Disaster Preven, Yiyang 413000, Peoples R China.;[Ma, Lidong] Sinohydro Engn Bur 8 Co Ltd, Changsha 410004, Hunan, Peoples R China.
通讯机构：
[Li, ZP ] H;Hunan City Univ, Sch Civil Engn, Yiyang 413000, Peoples R China.
关键词：
Magnetic amino-functionalized biochar;Hexavalent chromium;Removal performance;Potential mechanisms
摘要：
Magnetic amino-functionalized sludge biochar (Fe@NBC) was prepared via a one-step method for efficient Cr(VI) removal from tailing wastewater. Static adsorption research was conducted to investigate the impacts of solution pH, coexisting ion, reaction times, pollutant concentrations, and reaction temperature on removing Cr(VI) from tailing wastewater. Spectroscopic analysis was used to research the removal mechanisms of Cr(VI). Compared with the original sludge biochar, Fe@NBC exhibited a more developed pore structure and richer reactive sites. Adsorption experiments showed that Fe@NBC achieved higher adsorption and reduction rates of Cr(VI) than BC, with faster reaction equilibrium time. The efficiencies of removing Cr(VI) on Fe@NBC decreased with increasing solution pH. The efficiencies of removing Cr(VI) by Fe@NBC decreased with increasing SO 4 2- concentration, while Cl - and NO - 3 held almost no impact on removing Cr(VI). The process of removing Cr(VI) by Fe@NBC followed pseudo-second-order kinetic model and Langmuir model. Thermodynamics suggested that Cr(VI) removal on Fe@NBC was a spontaneous and endothermic processes. The main mechanisms for Cr(VI) removal by Fe@NBC were coordination and reduction, while pore filling and electrostatic interactions played secondary roles. This work demonstrated that Fe@NBC, a magnetic amino-functionalized sludge biochar, was a highly efficient and environmentally friendly material for removing Cr(VI) from tailing wastewater.
Magnetic amino-functionalized sludge biochar (Fe@NBC) was prepared via a one-step method for efficient Cr(VI) removal from tailing wastewater. Static adsorption research was conducted to investigate the impacts of solution pH, coexisting ion, reaction times, pollutant concentrations, and reaction temperature on removing Cr(VI) from tailing wastewater. Spectroscopic analysis was used to research the removal mechanisms of Cr(VI). Compared with the original sludge biochar, Fe@NBC exhibited a more developed pore structure and richer reactive sites. Adsorption experiments showed that Fe@NBC achieved higher adsorption and reduction rates of Cr(VI) than BC, with faster reaction equilibrium time. The efficiencies of removing Cr(VI) on Fe@NBC decreased with increasing solution pH. The efficiencies of removing Cr(VI) by Fe@NBC decreased with increasing SO 4 2- concentration, while Cl - and NO - 3 held almost no impact on removing Cr(VI). The process of removing Cr(VI) by Fe@NBC followed pseudo-second-order kinetic model and Langmuir model. Thermodynamics suggested that Cr(VI) removal on Fe@NBC was a spontaneous and endothermic processes. The main mechanisms for Cr(VI) removal by Fe@NBC were coordination and reduction, while pore filling and electrostatic interactions played secondary roles. This work demonstrated that Fe@NBC, a magnetic amino-functionalized sludge biochar, was a highly efficient and environmentally friendly material for removing Cr(VI) from tailing wastewater.
摘要：
During shield tunnel construction, karst development along the tunnel axis and in the surrounding area frequently poses a significant threat to engineering safety. To address this challenge, this study proposes multiple grouting systems and systematically analyzes the key mechanical properties of five grout formulations through orthogonal experiments, identifying the optimal formulations for engineering applications. A predictive model was established using linear regression, and its accuracy was validated through independent single-factor experiments. The results indicate the following: (1) Water content is the primary factor influencing fluidity, with its significance varying by system composition. The lake mud-cement grout exhibits the highest compressive pstrength. Moderate sand addition enhances strength, but excessive amounts significantly reduce fluidity. Additives demonstrate system dependency: HY-4 effectively improves fluidity, while sodium silicate significantly increases strength but reduces fluidity. (2) The developed model demonstrates good goodness of fit, with coefficients of determination (R(2)) ranging from 0.74 to 0.95, without significant autocorrelation or multicollinearity. Validation experiments confirm the model's high predictive accuracy, with overall trends consistent with the measured data. (3) The lake mud-cement grout (A3B1C3) is recommended for reinforcement projects prioritizing stability, achieving a 28-day compressive strength of 4.74 MPa. The on-site wet clay-cement grout (A2B3C1) is suitable for high-permeability formations, with a strength of 1.1 MPa and a fluidity of 292.5 mm, both exceeding standard requirements. The findings provide optimized formulations and theoretical references for grouting reinforcement in karst tunnel projects.
关键词：
Wind loading;wind turbine structure;extended foundation;transient response;response frequency
摘要：
To study the transient response characteristics of wind turbine structures–extended foundations under wind loads in mountainous areas, this paper develops a simplified analytical model based on soil–structure interaction theory. It explores the effects of constraint conditions, wind speed, and foundation shear wave speed on the transient response behavior. By analyzing the time–domain and frequency–domain trends of tower top displacement, foundation horizontal displacement, and foundation rotation angle, the relationship between foundation shear wave speed and the safe wind speed of the wind turbine is clarified. The results indicate that different constraint conditions lead to variations in the calculated resonance frequency, maximum tower top displacement, and acceleration response spectrum. Furthermore, based on the analysis of the tower top acceleration response curve, the influence interval of frequency can be categorized into three distinct ranges: stable range, small influence range, and large influence range. Wind speed primarily influences the vibration amplitudes of the three displacement components, while the overall trend of the time-displacement waveform remains unchanged. The foundation shear wave speed primarily affects the displacement of the foundation itself, exerting a smaller influence on the displacements of the wind turbine structure. Notably, the total displacement at the tower top decreases as the shear wave speed increases. Moreover, the safe wind speed of the wind turbine shows a positive correlation with the foundation shear wave speed, indicating a linear relationship between the two variables.
摘要：
A series of experiments were carried out to explore the impact of waste glass on the durability of concrete. In this study, waste glass was incrementally incorporated to replace sand as the fine aggregate in creating 240 concrete specimens, with substitution rates of 0%, 10%, 30%, and 50%. The concrete specimens were subjected to early strength testing on the 3rd and 7th day, followed by evaluation of strength and permeability after curing for 28 days with dry-wet cycles. Furthermore, ultrasonic wave analysis was conducted on the waveform, and the concrete’s internal phases and chemical composition were characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS). The results led to the following observations: (1) The inclusion of glass sand lowered the early compressive strength of concrete, with the lowest drop being 24.78%. However, when it was cured for 28 days and the content of glass sand was not more than 30%, the change rate of its compressive strength was between −2.85% and 3.19%, so it was practically negligible. (2) Glass sand substitution rates ranging from 10% to 30% greatly enhanced the strength of concrete under dry-wet cycles, and the 50% substitution rate significantly improved the permeability properties, although it adversely affected the strength.
摘要：
To investigate the dynamic characteristics and safe operation speed threshold of metro train passing through curved bridge (CB) considering resilient wheels, the mechanical connection characteristics of rim and web are discussed firstly. Based on the train-track-bridge interaction theory, the coupled dynamic model of metro train-CB considering resilient wheels is established. Then, the vehicle-bridge coupled dynamic characteristics under the excitation of long-short wave track irregularity are researched. Finally, from the perspective of dynamics, the safe operating speed threshold of metro trains passing through curved bridge considering resilient wheels (RW) is discussed. Results show that the vertical wheel-rail force of RW is reduced, but the lateral wheel-rail force is amplified compared with the solid wheels (SW). The vertical vibration acceleration of the wheel is reduced, but the lateral vibration acceleration is increased. It is recommended that the speed of metro trains running on curved bridge is not more than 60km/h. The vehicle-bridge coupling dynamic response is aggravated with the speed and load of metro train. The vibration of the inner side of the curved bridge is greater than that of the outer side, and the vibration reduction effect of the RW on the inner side is more significant than that on the outer side. The RW has a vibration absorption effect on the wheel-rail vertical and the vibration of the curved bridge force within 40-140Hz.
摘要：
Reasonable prediction of chloride concentration in the interfacial zone of precast and cast-in-place concrete structures is crucial for assessing the durability of such structures. In this paper, the machine learning-based deterministic model is first proposed to predict the chloride concentration in the interfacial zone using seven machine learning methods. Then, an uncertainty prediction model of chloride concentration in the interfacial zone is developed considering the aleatory uncertainty of input parameters and epistemic uncertainty of model itself. Finally, the effectiveness of the proposed prediction model is validated by using the collected database containing 2505 sets of data. The research results indicate that the deep neural network (DNN) model performs the best in predicting chloride concentration in the interfacial zone among the seven machine learning (ML) models, achieving an R 2 value as high as 0.9847. The proposed uncertainty prediction method not only demonstrates high prediction accuracy but also effectively accounts for uncertainty in the prediction process. The obtained prediction interval coverage probability (PICP) of the proposed method reaches to 0.9457 for the collected database. Moreover, rising dropout rate can improve the interval coverage at the expense of interval clarity, but the overall prediction performance still improves. Additionally, the prediction performance of uncertainty model for chloride concentration in interfacial zone is more sensitive to epistemic uncertainty than aleatory uncertainty in this case study.
Reasonable prediction of chloride concentration in the interfacial zone of precast and cast-in-place concrete structures is crucial for assessing the durability of such structures. In this paper, the machine learning-based deterministic model is first proposed to predict the chloride concentration in the interfacial zone using seven machine learning methods. Then, an uncertainty prediction model of chloride concentration in the interfacial zone is developed considering the aleatory uncertainty of input parameters and epistemic uncertainty of model itself. Finally, the effectiveness of the proposed prediction model is validated by using the collected database containing 2505 sets of data. The research results indicate that the deep neural network (DNN) model performs the best in predicting chloride concentration in the interfacial zone among the seven machine learning (ML) models, achieving an R 2 value as high as 0.9847. The proposed uncertainty prediction method not only demonstrates high prediction accuracy but also effectively accounts for uncertainty in the prediction process. The obtained prediction interval coverage probability (PICP) of the proposed method reaches to 0.9457 for the collected database. Moreover, rising dropout rate can improve the interval coverage at the expense of interval clarity, but the overall prediction performance still improves. Additionally, the prediction performance of uncertainty model for chloride concentration in interfacial zone is more sensitive to epistemic uncertainty than aleatory uncertainty in this case study.
作者机构：
[Yao, Qi; Ren, Heng] Hunan City Univ, Sch Civil Engn, Yiyang 413000, Peoples R China.;[Wei, Mingxing; Li, Peng; Ren, Heng] Hunan Univ Sci & Technol, Coll Resources Environm & Safety Engn, Xiangtan 411201, Peoples R China.;[Zhu, Yongjian] Key Lab Gas & Roof Disaster Prevent & Control Sout, Xiangtan 411201, Peoples R China.
通讯机构：
[Ren, H ] H;Hunan City Univ, Sch Civil Engn, Yiyang 413000, Peoples R China.;Hunan Univ Sci & Technol, Coll Resources Environm & Safety Engn, Xiangtan 411201, Peoples R China.
关键词：
Excavation disturbance;Weakening of damage;Rock-anchor combination;Failure mode;Stress intensity factor
摘要：
In response to the insufficient research on the damage weakening evolution law of surrounding rock during roadway (tunnel) excavation and retreat, as well as the inadequate understanding of the anchoring mechanism of rock bolts in such rock masses, a series of triaxial loading-unloading and uniaxial reloading experiments were conducted on sandstone specimens using the RMT-150C rock mechanics testing system. Microstructural characteristics of the damaged rock mass were investigated through scanning electron microscope (SEM) analysis, revealing the damage weakening mechanism of the rock. Through laboratory experiments and theoretical analysis, in combination with the failure characteristics of rock-anchor composite bodies, the underlying causes of changes in failure modes were analyzed to explore the anchoring mechanism of bolts in damaged rock. The experimental results indicate that during the triaxial loading-unloading tests, the degree of rock damage varied depending on the axial unloading point, exhibiting a trend of first decreasing and then increasing. For damaged rock masses, the presence of bolts did not alter the failure modes, which manifested as splitting failure at low damage levels and shear slip failure at high damage levels. However, the bolts did influence the characteristics of the failure, with the failure features of damaged rock being more diverse under the influence of bolts. The failure mode of the rock is related to the degree of damage, which can be represented by the ratio η of wing crack length to main crack length. When η is large, splitting failure occurs, whereas smaller η leads to shear slip failure. Bolts can reduce the stress intensity factor at the crack tip to some extent, inhibiting the propagation of wing cracks. This study effectively explains, from a microscopic perspective, the relationship between the failure modes of rock-anchor composite bodies and the anchoring effect of bolts.
作者机构：
[Ziwei Zhou] School of Civil Engineering, Hunan City University, Yiyang, Hunan 413000, China;Hunan Engineering Research Center of Development and Application of Ceramsite Concrete Technology, Hunan City University, Yiyang 413000, China;[Jianxin Peng] School of Civil Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China;[Yiming Yang] School of Civil Engineering, Hunan City University, Yiyang, Hunan 413000, China<&wdkj&>Hunan Engineering Research Center of Development and Application of Ceramsite Concrete Technology, Hunan City University, Yiyang 413000, China
通讯机构：
[Jianxin Peng] S;School of Civil Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China
摘要：
This study aims to propose a hybrid physics-based and data-driven model for predicting flexural capacity of corroded prestressed concrete (PC) structures, aiming to improve the rationality and applicability of flexural capacity assessment. First, a self-adaptive physics-informed deep neural network framework is developed. Then, based on a collected database containing 100 sets of measured data, the proposed model is compared with three deep learning (DL) models, two machine learning (ML) models and two traditional mechanism-based prediction models. After that, the score analysis, error analysis, and generalization performance evaluation are conducted. Finally, the importance analysis of input parameters is analyzed by using SHapley Additive exPlanations (SHAP) method. The results indicate that the proposed method significantly improves prediction accuracy compared to DL and ML models, with the mean absolute percentage error (MAPE) reduced by 28.88% compared to the second-best model. Compared to conventional mechanism-based models, the proposed method achieves substantial reductions in mean absolute error (MAE), root mean squared error (RMSE), and MAPE, with the MAPE reduced by over 83%. Moreover, the proposed method exhibits good generalization performance, with the average relative error between predicted and measured values being less than 6%. In addition, SHAP analysis reveals that the beam height, cross-sectional area of tensile non-prestressing reinforcement and prestressing reinforcement have a significant influence on the prediction results among all input parameters. These findings not only enhance the reliability of flexural capacity prediction for corroded PC structures but also provide a solid data foundation for similar research. The proposed hybrid framework also offers a new perspective for predicting other structural performance indexes.
This study aims to propose a hybrid physics-based and data-driven model for predicting flexural capacity of corroded prestressed concrete (PC) structures, aiming to improve the rationality and applicability of flexural capacity assessment. First, a self-adaptive physics-informed deep neural network framework is developed. Then, based on a collected database containing 100 sets of measured data, the proposed model is compared with three deep learning (DL) models, two machine learning (ML) models and two traditional mechanism-based prediction models. After that, the score analysis, error analysis, and generalization performance evaluation are conducted. Finally, the importance analysis of input parameters is analyzed by using SHapley Additive exPlanations (SHAP) method. The results indicate that the proposed method significantly improves prediction accuracy compared to DL and ML models, with the mean absolute percentage error (MAPE) reduced by 28.88% compared to the second-best model. Compared to conventional mechanism-based models, the proposed method achieves substantial reductions in mean absolute error (MAE), root mean squared error (RMSE), and MAPE, with the MAPE reduced by over 83%. Moreover, the proposed method exhibits good generalization performance, with the average relative error between predicted and measured values being less than 6%. In addition, SHAP analysis reveals that the beam height, cross-sectional area of tensile non-prestressing reinforcement and prestressing reinforcement have a significant influence on the prediction results among all input parameters. These findings not only enhance the reliability of flexural capacity prediction for corroded PC structures but also provide a solid data foundation for similar research. The proposed hybrid framework also offers a new perspective for predicting other structural performance indexes.
摘要：
This study investigates the impact of basalt fiber on the mechanical properties of reinforced concrete members, with a specific focus on their behavior under large eccentric compression. A series of large eccentric compression tests were conducted on basalt fiber-reinforced concrete (BFRC) members with varying parameters. The failure characteristics, ultimate bearing capacity, cracking load, crack width, and other relevant factors were thoroughly analyzed. The results indicate that the mechanical properties of BFRC components are significantly improved compared to traditional concrete using basalt fiber reinforced concrete. Specifically, the ultimate bearing capacity increased by up to 30.3%, while the cracking load exhibit ed a notable increase of up to 42.9%. Notably, BFRC members displayed enhanced loading characteristics, including delayed crack initiation, a greater number of cracks, and a smaller maximum crack width. A comprehensive data simulation was performed, leading to the development of a calculation formula for the maximum crack width of BFRC members under large eccentric compression.
作者：
Yongsuo Li;Xiaoxuan Weng;Da Hu*;Ze Tan;Jing Liu
期刊：
Journal of Pipeline Systems Engineering and Practice,2025年16(3):04025046 ISSN：1949-1190
通讯作者：
Da Hu
作者机构：
[Yongsuo Li; Da Hu] Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;Professor, School of Civil Engineering, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;[Xiaoxuan Weng; Ze Tan; Jing Liu] Master’s Student, School of Civil Engineering, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;[Yongsuo Li] Professor, School of Civil Engineering, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;[Da Hu] Professor, School of Civil Engineering, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China
通讯机构：
[Da Hu] P;Professor, Hunan Engineering Research Center of Structural Safety and Disaster Prevention for Urban Underground Infrastructure, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China;Professor, School of Civil Engineering, Hunan City Univ., No. 518, Yingbin East Rd., Yiyang 413000, China
摘要：
The long-term settlement of deep pipelines is a crucial factor in the construction of rectangular shield tunnels. Conventional prediction techniques primarily depend on empirical models and statistical analyses, which often fail to accurately forecast pipeline deformation and settlement in intricate environments. To tackle this challenge, this article introduces a long-term settlement prediction model for pipelines based on long short-term memory (LSTM) networks, incorporating time decay and multiscale improved self-attention mechanisms (ISA), referred to as the LSTM-ISA model. Initially, settlement data that matched theoretical expectations were selected from 69 sets of monitoring data to create a data set for predicting pipeline settlement during shield tunnel construction. The LSTM-ISA model was then developed, using the LSTM network to capture temporal dependencies in time-series data. The time-decay mechanism gives greater importance to more recent data, while the multiscale self-attention mechanism identifies features across various time scales. The model’s effectiveness and reliability were tested using actual measurement data from the Changsha Metro Line 6 project and compared with predictions from traditional LSTM and LSTM-SA networks. The findings indicate that the LSTM-ISA model surpasses both the LSTM and LSTM-SA models, achieving a 12.9% and 30.7% decrease in mean squared error (MSE) and a 6.4% and 21.8% decrease in mean absolute error (MAE), respectively. These results imply that the LSTM-ISA model can serve as an effective tool for providing early warnings regarding long-term pipeline settlement caused by the construction of rectangular shield tunnels.
摘要：
Lead-zinc tailings are waste materials generated from mineral processing and smelting, and their long-term accumulation poses potential threats to the environment and soil. To achieve resource recycling and sustainable development, this study used lead-zinc tailings and clay as raw materials and glass powder as a modifier to prepare modified lead-zinc tailing sintered bricks. Through full-factor experiments and single-factor experiments, the effects of the material proportions, the sintering temperature, and the holding time on the properties of the sintered bricks were investigated. The results show that the addition of glass powder significantly enhanced the compressive strength of the sintered bricks, reduced their water absorption rate, and improved their volume shrinkage rate. The optimal preparation conditions were as follows: 9% glass powder content, 90% lead-zinc tailings content, a sintering temperature of 1060 °C, and a holding time of 60 min. The resulting sintered bricks met the MU30-strength-grade requirements of the national standard for ordinary sintered bricks (GB/T5101-2017). The sintering temperature has a significant impact on brick performance; the compressive strength first increases, and then decreases, the water absorption rate continues to decrease, and volume change shifts from expansion to contraction. The influence of holding time was relatively weaker, but as the holding time increased, the compressive strength and the water absorption rate of the sintered bricks gradually stabilized. XRD and SEM analyses indicated that the minerals in the lead-zinc tailings decomposed and recrystallized during the sintering process. The liquid phase melt from the glass powder filled the pores and enhanced skeletal strength, thereby improving the microstructure and properties of the sintered bricks. The research findings provide a theoretical basis and practical guidance for the efficient utilization and building material application of lead-zinc tailings.
摘要：
Reasonable assessment of flexural capacity and reliability is an important prerequisite for ensuring the normal use of corroded prestressed concrete (PC) structures. In this paper, a theory-informed deep neural network (TIDNN)-based model is first developed to predict the flexural capacity of corroded PC beams. Then, a TIDNN-based time-dependent reliability analysis method is proposed considering the aleatory uncertainty of input parameters and the epistemic uncertainty of model. In addition, the effectiveness of the proposed prediction method of flexural capacity is validated by using the collected database, and a simple case analysis of corroded PC beam is used to illustrate the application of the proposed reliability assessment approach. The research results indicate that the prediction performance of the proposed TIDNN method for predicting flexural capacity is significantly better than the deep neural network (DNN), radial basis function (RBF) neural network, and the physics-based prediction model. The proposed uncertainty prediction method of flexural capacity has high accuracy and coverage ability, and the coverage rate for the collected database is 97.37 %. Moreover, the cumulative failure probability is more sensitive to aleatory uncertainty than epistemic uncertainty. Additionally, the cumulative failure probability increases with the rising dropout rate, and the magnitude of this increase gradually intensifies.
Reasonable assessment of flexural capacity and reliability is an important prerequisite for ensuring the normal use of corroded prestressed concrete (PC) structures. In this paper, a theory-informed deep neural network (TIDNN)-based model is first developed to predict the flexural capacity of corroded PC beams. Then, a TIDNN-based time-dependent reliability analysis method is proposed considering the aleatory uncertainty of input parameters and the epistemic uncertainty of model. In addition, the effectiveness of the proposed prediction method of flexural capacity is validated by using the collected database, and a simple case analysis of corroded PC beam is used to illustrate the application of the proposed reliability assessment approach. The research results indicate that the prediction performance of the proposed TIDNN method for predicting flexural capacity is significantly better than the deep neural network (DNN), radial basis function (RBF) neural network, and the physics-based prediction model. The proposed uncertainty prediction method of flexural capacity has high accuracy and coverage ability, and the coverage rate for the collected database is 97.37 %. Moreover, the cumulative failure probability is more sensitive to aleatory uncertainty than epistemic uncertainty. Additionally, the cumulative failure probability increases with the rising dropout rate, and the magnitude of this increase gradually intensifies.
