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2025 Vol. 55, No. 7
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2025, 55(7): 1-10.
doi: 10.3724/j.gyjzG25070801
Abstract:
Conventional structural inspection highly relies on human inspector with engineering experience， lacks safety guarantee， and is time-labor-consuming. Recently， advanced robotics， computer vision， and deep learning techniques have provided innovative solutions. This study proposed a generalized vision-based intelligent agent navigation for structural damage inspection， and established an interactive experimental environment for visual navigation agent integrating structural damage. A multi-modal information fusion network of optical image and depth information was designed， and a deep reinforcement learning network was developed based on the A3C algorithm with auxiliary tasks of collision prediction and reward prediction， in which a long-term memory module was embedded before the output layers of policy network and value network， and a decoupling module of value network was introduced based on universal successor representation. The model performance， effectiveness， and generalization ability were validated under various structural damage scenarios， and the results showed that it could achieve accurate mapping from observed images to navigation strategies and address conventional navigation limitations of lacking long-term memory and poor generalization ability in open environments.
Conventional structural inspection highly relies on human inspector with engineering experience， lacks safety guarantee， and is time-labor-consuming. Recently， advanced robotics， computer vision， and deep learning techniques have provided innovative solutions. This study proposed a generalized vision-based intelligent agent navigation for structural damage inspection， and established an interactive experimental environment for visual navigation agent integrating structural damage. A multi-modal information fusion network of optical image and depth information was designed， and a deep reinforcement learning network was developed based on the A3C algorithm with auxiliary tasks of collision prediction and reward prediction， in which a long-term memory module was embedded before the output layers of policy network and value network， and a decoupling module of value network was introduced based on universal successor representation. The model performance， effectiveness， and generalization ability were validated under various structural damage scenarios， and the results showed that it could achieve accurate mapping from observed images to navigation strategies and address conventional navigation limitations of lacking long-term memory and poor generalization ability in open environments.
2025, 55(7): 11-20.
doi: 10.3724/j.gyjzG25062002
Abstract:
Surface defects of stay-cable sheaths directly jeopardize the structural redundancy and service life of cable-supported bridges. However， large depth-of-field imaging， cluttered backgrounds， and considerable cable length fragment visual information still impairs the accuracy of automated inspection accuracy. To remedy the inadequate data preprocessing and absence of holistic analysis in the existing work， an intelligent three-stage inspection pipeline that integrates instance-segmentation-based background removal， image mosaicking， and YOLO-based validation was developed. First， a fine-tuned U2-Net performed pixel-level cropping on images captured by a cable-climbing robot， suppressing background noise while preserving sheath details. Next， an enhanced regional SIFT matcher conducted longitudinal unfolding and transversed stitching to generate a seamless panoramic view of the cable surface. Finally， a task-oriented， improved YOLOv5 detector—augmented with lightweight attention and loss-function refinements—verified the effectiveness of the workflow for sheath-defect recognition. Experiments on a self-built data set of 1500 original images showed that the proposed model raised the mAP@0.5 by 2.8% comparing to the baseline YOLOv5 and maintained real-time inference. The three-stage pipeline markedly enhanced stay-cable sheath defect detection precision and supplied high-quality data for subsequent three-dimensional localization and service-life evaluation.
Surface defects of stay-cable sheaths directly jeopardize the structural redundancy and service life of cable-supported bridges. However， large depth-of-field imaging， cluttered backgrounds， and considerable cable length fragment visual information still impairs the accuracy of automated inspection accuracy. To remedy the inadequate data preprocessing and absence of holistic analysis in the existing work， an intelligent three-stage inspection pipeline that integrates instance-segmentation-based background removal， image mosaicking， and YOLO-based validation was developed. First， a fine-tuned U2-Net performed pixel-level cropping on images captured by a cable-climbing robot， suppressing background noise while preserving sheath details. Next， an enhanced regional SIFT matcher conducted longitudinal unfolding and transversed stitching to generate a seamless panoramic view of the cable surface. Finally， a task-oriented， improved YOLOv5 detector—augmented with lightweight attention and loss-function refinements—verified the effectiveness of the workflow for sheath-defect recognition. Experiments on a self-built data set of 1500 original images showed that the proposed model raised the mAP@0.5 by 2.8% comparing to the baseline YOLOv5 and maintained real-time inference. The three-stage pipeline markedly enhanced stay-cable sheath defect detection precision and supplied high-quality data for subsequent three-dimensional localization and service-life evaluation.
2025, 55(7): 21-29.
doi: 10.3724/j.gyjzG25020802
Abstract:
Latent defects， such as poorly compacted concrete and voids， are increasingly detected in existing structures due to advances in structural inspection technology. These defects are formed during concrete pouring because of inadequate vibration， blockage by coarse aggregates， or obstruction by reinforcement. They exhibit high randomness. In this study， the defect detection in reinforced concrete structures was analyzed， and the random distribution of poorly compacted areas was characterized. Finite element models with random defects were developed using ABAQUS and Python. The effects of different modeling methods and defect rates on seismic performance were investigated， and the finite element modeling method was validated through experiments. The results showed that both the random element method and the random sphere method could effectively simulate random defects in shear walls while meeting computational requirements， with the random element method exhibiting higher computational efficiency. The influence of defect rates on the seismic performance of shear walls was primarily reflected in the degradation of initial stiffness and bearing capacity. Additionally， the presence of defects significantly affected the cracking and failure patterns in concrete.
Latent defects， such as poorly compacted concrete and voids， are increasingly detected in existing structures due to advances in structural inspection technology. These defects are formed during concrete pouring because of inadequate vibration， blockage by coarse aggregates， or obstruction by reinforcement. They exhibit high randomness. In this study， the defect detection in reinforced concrete structures was analyzed， and the random distribution of poorly compacted areas was characterized. Finite element models with random defects were developed using ABAQUS and Python. The effects of different modeling methods and defect rates on seismic performance were investigated， and the finite element modeling method was validated through experiments. The results showed that both the random element method and the random sphere method could effectively simulate random defects in shear walls while meeting computational requirements， with the random element method exhibiting higher computational efficiency. The influence of defect rates on the seismic performance of shear walls was primarily reflected in the degradation of initial stiffness and bearing capacity. Additionally， the presence of defects significantly affected the cracking and failure patterns in concrete.
2025, 55(7): 30-38.
doi: 10.3724/j.gyjzG24083103
Abstract:
Given the structural complexity of back-bolted stone curtain wall panels — with four cantilevered edges and four-point localized back-anchor constraints — no theoretical natural frequency solution is available to validate numerical simulations or guide experimental test analysis. Considering the actual constraint characteristics of back-bolted stone curtain wall panels， the actual constraint was first simplified as linear constrains along one panel direction， then modeled as a simply-supported beam with overhanging ends， and finally solved for natural frequencies using continuous system vibration theory to obtain the theoretical solution for a double-overhang beam. The modal test results for the back-bolted stone curtain wall panel showed that the experimental frequencies closely matched the theoretical solutions， which were further verified by numerical simulations. In the case where a crack was present inside the panel， the corresponding natural frequencies of the simplified model for the back-bolted stone curtain wall panel were also validated to match well with the theoretical solution for the cracked panel as a whole. The theoretical natural frequencies obtained for the back-bolted stone curtain wall panels （including those with partial cracks） can be used to varify the numerical simulation and experimental test results.
Given the structural complexity of back-bolted stone curtain wall panels — with four cantilevered edges and four-point localized back-anchor constraints — no theoretical natural frequency solution is available to validate numerical simulations or guide experimental test analysis. Considering the actual constraint characteristics of back-bolted stone curtain wall panels， the actual constraint was first simplified as linear constrains along one panel direction， then modeled as a simply-supported beam with overhanging ends， and finally solved for natural frequencies using continuous system vibration theory to obtain the theoretical solution for a double-overhang beam. The modal test results for the back-bolted stone curtain wall panel showed that the experimental frequencies closely matched the theoretical solutions， which were further verified by numerical simulations. In the case where a crack was present inside the panel， the corresponding natural frequencies of the simplified model for the back-bolted stone curtain wall panel were also validated to match well with the theoretical solution for the cracked panel as a whole. The theoretical natural frequencies obtained for the back-bolted stone curtain wall panels （including those with partial cracks） can be used to varify the numerical simulation and experimental test results.
2025, 55(7): 39-50.
doi: 10.3724/j.gyjzG25050703
Abstract:
Modular integrated construction （MIC） shear walls are composed of multiple connecting components， such as grouting sleeves， non-contact grouted rebar lapping connections， bedding mortar layer at the base， prefabricated wall molds， and cast-in-place concrete cores. They fully embody the modular characteristics of industrialized production， prefabricated construction， and full life-cycle maintainability.However， due to factors such as concrete shrinkage and creep， complex local detailing， inadequate vibration compaction and other construction issues， these connection components are prone to hidden damage， including insufficient grouting， interface debonding， and internal voids. With the development of non-destructive testing （NDT） hardware and software in recent years， various NDT techniques have become important technical means for damage identification in MIC shear wall structures. This paper systematically reviewed the research progress of existing NDT techniques in damage identification of MIC shear wall structures. A review study was conducted on damage identification techniques for the following aspects： the insufficient grouting in rebar grouting sleeves and non-contact grouted rebar lapping connections， interface debonding between prefabricated wall molds and cast-in-place concrete， internal voids in cast-in-place concrete， and insufficient grouting in the bedding mortar layer at the base. Finally， the regulations and recommended methods outlined in relevant domestic standards were systematically reviewed. Additionally， the development prospects for damage detection in prefabricated shear walls using the MIC method were forecasted. This research provides an effective solution for identifying potential hidden damage in MIC shear wall structures and offers guiding significance for engineering applications.
Modular integrated construction （MIC） shear walls are composed of multiple connecting components， such as grouting sleeves， non-contact grouted rebar lapping connections， bedding mortar layer at the base， prefabricated wall molds， and cast-in-place concrete cores. They fully embody the modular characteristics of industrialized production， prefabricated construction， and full life-cycle maintainability.However， due to factors such as concrete shrinkage and creep， complex local detailing， inadequate vibration compaction and other construction issues， these connection components are prone to hidden damage， including insufficient grouting， interface debonding， and internal voids. With the development of non-destructive testing （NDT） hardware and software in recent years， various NDT techniques have become important technical means for damage identification in MIC shear wall structures. This paper systematically reviewed the research progress of existing NDT techniques in damage identification of MIC shear wall structures. A review study was conducted on damage identification techniques for the following aspects： the insufficient grouting in rebar grouting sleeves and non-contact grouted rebar lapping connections， interface debonding between prefabricated wall molds and cast-in-place concrete， internal voids in cast-in-place concrete， and insufficient grouting in the bedding mortar layer at the base. Finally， the regulations and recommended methods outlined in relevant domestic standards were systematically reviewed. Additionally， the development prospects for damage detection in prefabricated shear walls using the MIC method were forecasted. This research provides an effective solution for identifying potential hidden damage in MIC shear wall structures and offers guiding significance for engineering applications.
2025, 55(7): 51-59.
doi: 10.3724/j.gyjzG25010305
Abstract:
Ultrasonic testing has been widely used in the quality inspection of pile foundations due to its non-destructiveness and high accuracy. Traditional ultrasonic transmission method relies on two-dimensional waveform diagrams （e.g.， sound velocity， amplitude， and PSD） for defect judgment， and the readability and intuitiveness of the detection results are relatively poor. Based on a modified residual convolutional neural network algorithm （M-ResNet）， an original ultrasonic dataset using the ray-tracing method was constructed. Deep learning technology was employed to train the network model， and MATLAB was used to develop code for displaying 3D pile foundation defect images and detection results. Evaluation indicators （ICC and CCC） for defect images and algorithm noise immunity tests demonstrated that the algorithm operated rapidly with high detection accuracy， could directly display the defect range and size， and showed more advantages in imaging compared to traditional methods. The proposed method can directly use existing instruments and test data from conventional ultrasonic methods to achieve 3D visualization and defect detection， with research results applicable to similar engineering inspections.
Ultrasonic testing has been widely used in the quality inspection of pile foundations due to its non-destructiveness and high accuracy. Traditional ultrasonic transmission method relies on two-dimensional waveform diagrams （e.g.， sound velocity， amplitude， and PSD） for defect judgment， and the readability and intuitiveness of the detection results are relatively poor. Based on a modified residual convolutional neural network algorithm （M-ResNet）， an original ultrasonic dataset using the ray-tracing method was constructed. Deep learning technology was employed to train the network model， and MATLAB was used to develop code for displaying 3D pile foundation defect images and detection results. Evaluation indicators （ICC and CCC） for defect images and algorithm noise immunity tests demonstrated that the algorithm operated rapidly with high detection accuracy， could directly display the defect range and size， and showed more advantages in imaging compared to traditional methods. The proposed method can directly use existing instruments and test data from conventional ultrasonic methods to achieve 3D visualization and defect detection， with research results applicable to similar engineering inspections.
2025, 55(7): 60-69.
doi: 10.3724/j.gyjzG25051006
Abstract:
Nowadays， the shoulder-beams of heavy industrial plants in China are widely cracked under repeated crane loads， seriously threatening the production safety of the plants. To investigate the fatigue cracking mechanism and fatigue life of the double-web shoulder-beams in four-limb concrete-filled steel tubular （CFST） columns， this paper analyzed the key factors affecting the fatigue strength of the ortho-welded zone of the crane limb of shoulder-beams by field inspection. Finite element models were used to simulate the pseudo-static fatigue crack propagation of double-web shoulder-beams in four-limb CFST columns under eight different working conditions. Based on the structural principal stress distribution， the effects of the longitudinal eccentricity of the crane beam， the local suspension of the shoulder-beam support on the stress damage of the crane limb were analyzed. Finally， based on the linear elastic fracture mechanics， it was found that the shear fatigue life of the vertical joint seam of the web and column was reduced by 52.2%， when the longitudinal eccentricity of the crane beam was 42.5%. The shear fatigue life of the vertical joint seam between the web and stiffener was reduced to less than 300000 times， when the shoulder-beam support was 50% suspended. To address the issue of the crane limb of the shoulder beam being prone to cracking under eccentric loading， a reinforcement method using welded vertical steel plates was proposed. This method significantly improves the mechanical performance of the shoulder beam. Currently， this method has been successfully applied in several domestic heavy metallurgical industrial buildings.
Nowadays， the shoulder-beams of heavy industrial plants in China are widely cracked under repeated crane loads， seriously threatening the production safety of the plants. To investigate the fatigue cracking mechanism and fatigue life of the double-web shoulder-beams in four-limb concrete-filled steel tubular （CFST） columns， this paper analyzed the key factors affecting the fatigue strength of the ortho-welded zone of the crane limb of shoulder-beams by field inspection. Finite element models were used to simulate the pseudo-static fatigue crack propagation of double-web shoulder-beams in four-limb CFST columns under eight different working conditions. Based on the structural principal stress distribution， the effects of the longitudinal eccentricity of the crane beam， the local suspension of the shoulder-beam support on the stress damage of the crane limb were analyzed. Finally， based on the linear elastic fracture mechanics， it was found that the shear fatigue life of the vertical joint seam of the web and column was reduced by 52.2%， when the longitudinal eccentricity of the crane beam was 42.5%. The shear fatigue life of the vertical joint seam between the web and stiffener was reduced to less than 300000 times， when the shoulder-beam support was 50% suspended. To address the issue of the crane limb of the shoulder beam being prone to cracking under eccentric loading， a reinforcement method using welded vertical steel plates was proposed. This method significantly improves the mechanical performance of the shoulder beam. Currently， this method has been successfully applied in several domestic heavy metallurgical industrial buildings.
2025, 55(7): 70-78.
doi: 10.3724/j.gyjzG25052601
Abstract:
The damages such as cracking and bending deformation in the timber beam-column joints in traditional vernacular dwellings in the Xianshui River Basin of Garzê Tibetan Autonomous Prefecture， Sichuan Province， the normal use of the house is affected， posing safety risks such as fracture of the main joint. Based on the survey data of Diqingyi Village in the upper Xianshui River Basin， this study takes the typical beam-column joint of a timber-framed house in the village as the research object. A steel reinforcement component was designed to address these issues. Finite element analysis software was used to establish models of the joint and the steel component， analyzing the failure conditions of the joint before and after reinforcement. Three performance indicators of the joint—hysteresis curve， skeleton curve， and stiffness degradation curve—were compared to evaluate the effectiveness of the reinforcement. The results indicated a 69.19% reduction in maximum von Mises stress （from 6.127 MPa to 1.888 MPa） following reinforcement. The bearing capacity increased by 35.52% to -25.45 kN at -120 mm displacement and by 25.60% to 28.89 kN at +150 mm displacement. The reinforced joint demonstrated improved stability， enhanced energy dissipation capacity， and greater deformation resistance under cyclic loading， confirming the system's effectiveness in seismic risk mitigation.
The damages such as cracking and bending deformation in the timber beam-column joints in traditional vernacular dwellings in the Xianshui River Basin of Garzê Tibetan Autonomous Prefecture， Sichuan Province， the normal use of the house is affected， posing safety risks such as fracture of the main joint. Based on the survey data of Diqingyi Village in the upper Xianshui River Basin， this study takes the typical beam-column joint of a timber-framed house in the village as the research object. A steel reinforcement component was designed to address these issues. Finite element analysis software was used to establish models of the joint and the steel component， analyzing the failure conditions of the joint before and after reinforcement. Three performance indicators of the joint—hysteresis curve， skeleton curve， and stiffness degradation curve—were compared to evaluate the effectiveness of the reinforcement. The results indicated a 69.19% reduction in maximum von Mises stress （from 6.127 MPa to 1.888 MPa） following reinforcement. The bearing capacity increased by 35.52% to -25.45 kN at -120 mm displacement and by 25.60% to 28.89 kN at +150 mm displacement. The reinforced joint demonstrated improved stability， enhanced energy dissipation capacity， and greater deformation resistance under cyclic loading， confirming the system's effectiveness in seismic risk mitigation.
2025, 55(7): 79-86.
doi: 10.3724/j.gyjzG25031704
Abstract:
Glass curtain walls are widely used in modern buildings， but they are prone to safety hazards such as structural adhesive aging and debonding due to long-term exposure to wind loads and temperature changes. To this end， the representative results of domestic and foreign hidden frame glass curtain wall safety testing technology and analysis methods and evaluation system are systematically sorted out. For detection， vibration analysis identifies adhesive damage through changes in natural frequency， ultrasonic testing evaluates damage severity using nonlinear coefficients， and infrared inspection detects thermal anomalies in adhesives despite its sensitivity to environmental interference. In analysis， test data can be used to assess the safety of glass curtain walls， while finite element models can locate debonding damage through modal curvature. For evaluation， a fuzzy comprehensive method integrates multiple indicators， and neural networks classify safety levels based on dynamic parameters. Aiming to address the existing problems of insufficient detection accuracy and poor model adaptability， future research should focus on integrating vibration， ultrasonic， and infrared technologies， investigating adhesive aging in relation to environmental factors for long-term performance prediction， and creating intelligent real-time monitoring systems to improve early-warning capabilities for potential hazards.
Glass curtain walls are widely used in modern buildings， but they are prone to safety hazards such as structural adhesive aging and debonding due to long-term exposure to wind loads and temperature changes. To this end， the representative results of domestic and foreign hidden frame glass curtain wall safety testing technology and analysis methods and evaluation system are systematically sorted out. For detection， vibration analysis identifies adhesive damage through changes in natural frequency， ultrasonic testing evaluates damage severity using nonlinear coefficients， and infrared inspection detects thermal anomalies in adhesives despite its sensitivity to environmental interference. In analysis， test data can be used to assess the safety of glass curtain walls， while finite element models can locate debonding damage through modal curvature. For evaluation， a fuzzy comprehensive method integrates multiple indicators， and neural networks classify safety levels based on dynamic parameters. Aiming to address the existing problems of insufficient detection accuracy and poor model adaptability， future research should focus on integrating vibration， ultrasonic， and infrared technologies， investigating adhesive aging in relation to environmental factors for long-term performance prediction， and creating intelligent real-time monitoring systems to improve early-warning capabilities for potential hazards.
2025, 55(7): 87-95.
doi: 10.3724/j.gyjzG25052401
Abstract:
The Shanghai Huangpu District 160 Neighborhood Reconstruction Project involved the development of underground space beneath a historical building. It innovatively used the first support of the foundation pit as a translation platform for the historical building， with reciprocating lateral movement synchronized to the foundation pit excavation. It successfully realized the completion of foundation pit excavation while preserving the historical building directly above it. A complex three-dimensional finite element model was established， considering the interaction among the soil， foundation pit supporting structure， and the building. The HS-Small advanced constitutive model considering the small strain characteristics of soil was adopted， and reasonable calculation parameters were determined. A full-process simulation of foundation pit excavation beneath the historical building was carried out. The rationality of the analytical method was verified by comparing the calculated and measured values of foundation pit deformation. On this basis， the impact of foundation pit excavation on the overlying historical building was analyzed. The results showed that the deformation and stress of the building were controllable， ensuring its safety. It also demonstrated that a three-dimensional analysis based on the small-strain constitutive model could effectively evaluate the impact of deep excavation on the overlying building.
The Shanghai Huangpu District 160 Neighborhood Reconstruction Project involved the development of underground space beneath a historical building. It innovatively used the first support of the foundation pit as a translation platform for the historical building， with reciprocating lateral movement synchronized to the foundation pit excavation. It successfully realized the completion of foundation pit excavation while preserving the historical building directly above it. A complex three-dimensional finite element model was established， considering the interaction among the soil， foundation pit supporting structure， and the building. The HS-Small advanced constitutive model considering the small strain characteristics of soil was adopted， and reasonable calculation parameters were determined. A full-process simulation of foundation pit excavation beneath the historical building was carried out. The rationality of the analytical method was verified by comparing the calculated and measured values of foundation pit deformation. On this basis， the impact of foundation pit excavation on the overlying historical building was analyzed. The results showed that the deformation and stress of the building were controllable， ensuring its safety. It also demonstrated that a three-dimensional analysis based on the small-strain constitutive model could effectively evaluate the impact of deep excavation on the overlying building.
2025, 55(7): 96-102.
doi: 10.3724/j.gyjzG25051304
Abstract:
To investigate the cooling performance of thermosyphon-ventilated plate composite subgrade in permafrost regions， field experiments were conducted on a highway section between the 109 Junction at Erdaogou Military Station and Zhiduo along the S224 Line in Qinghai Province. The research reveals that the composite structure achieves three-dimensional optimization of the subgrade temperature field by establishing a tri-integrated regulation mode of "active cooling guidance - passive heat dissipation - cooling energy reserve". Based on the field-monitored temperature data and ground temperature measurements， this study analyzed the cooling performance of both the thermosyphon-ventilated plate composite subgrade and the ventilated plate subgrade. The research findings indicated that the composite subgrade， through a synergistic mechanism of "thermosyphon phase-change cooling + ventilated plate-enhanced heat dissipation"， extended the heat transfer influence depth to -6 m during the cold season， forming a core cooling reserve layer spanning 2 to 6 meters in depth with a cooling energy reserve of 5220 J/kg， representing a 35.5% increase compared to the ventilated plate subgrade alone. Moreover， monitoring data revealed that the composite subgrade stabilized the permafrost table at a distance of 2.0 to 2.5 meters from the road surface， representing a 0.5 m uplift compared to the ventilated plate subgrade alone. The thermosyphon system maintained continuous operation for 215 days during the cold season. This study proposes a novel technical solution utilizing the synergistic effect of "thermosyphon phase-change cooling + ventilated plate-enhanced heat dissipation" for highway construction in discontinuous and continuous permafrost regions （particularly ice-rich and ice-saturated frozen soil areas） where the annual average ground temperature on the Qinghai-Tibet Plateau is ≤ -1 ℃.
To investigate the cooling performance of thermosyphon-ventilated plate composite subgrade in permafrost regions， field experiments were conducted on a highway section between the 109 Junction at Erdaogou Military Station and Zhiduo along the S224 Line in Qinghai Province. The research reveals that the composite structure achieves three-dimensional optimization of the subgrade temperature field by establishing a tri-integrated regulation mode of "active cooling guidance - passive heat dissipation - cooling energy reserve". Based on the field-monitored temperature data and ground temperature measurements， this study analyzed the cooling performance of both the thermosyphon-ventilated plate composite subgrade and the ventilated plate subgrade. The research findings indicated that the composite subgrade， through a synergistic mechanism of "thermosyphon phase-change cooling + ventilated plate-enhanced heat dissipation"， extended the heat transfer influence depth to -6 m during the cold season， forming a core cooling reserve layer spanning 2 to 6 meters in depth with a cooling energy reserve of 5220 J/kg， representing a 35.5% increase compared to the ventilated plate subgrade alone. Moreover， monitoring data revealed that the composite subgrade stabilized the permafrost table at a distance of 2.0 to 2.5 meters from the road surface， representing a 0.5 m uplift compared to the ventilated plate subgrade alone. The thermosyphon system maintained continuous operation for 215 days during the cold season. This study proposes a novel technical solution utilizing the synergistic effect of "thermosyphon phase-change cooling + ventilated plate-enhanced heat dissipation" for highway construction in discontinuous and continuous permafrost regions （particularly ice-rich and ice-saturated frozen soil areas） where the annual average ground temperature on the Qinghai-Tibet Plateau is ≤ -1 ℃.
2025, 55(7): 103-108.
doi: 10.3724/j.gyjzG23052503
Abstract:
The service state of the steel deck system is closely related to load， temperature， structural response and other factors. In order to accurately analyze the long-term performance of the steel deck pavement， the study conducted long-term monitoring on an orthotropic steel deck system with cast + epoxy asphalt pavement and steel box girder， using a specific bridge as the engineering case. Based on a large number of real bridge monitoring data， the data analysis was carried out on service conditions and structural responses， such as temperature， vehicle speed， load， and characteristic values of structural response. The relations between different factors and the strain of steel deck-U-rib welds were studied and analyzed， and the multi-dimensional correlation rule of structural dynamic responses was established. The research showed that the strain amplitude of the weld seams in the cast+epoxy pavement structural steel deck-U-rib was linearly related to the axle load， and the strain magnitude increased as the axle load increased. For the same axle load， when the speed increased from 40 km/h to 70 km/h， the evaluated strain decreased by 28%。 When the temperature rose from 5 ℃ to 50 ℃， the average strain increased by 24%. Based on the real bridge monitoring data， a multi-factor regression model was established to quantify the relationship between weld strain and factors such as axle load， vehicle speed， and temperature. The model was then applied to predict strain variations in the weld seams.
The service state of the steel deck system is closely related to load， temperature， structural response and other factors. In order to accurately analyze the long-term performance of the steel deck pavement， the study conducted long-term monitoring on an orthotropic steel deck system with cast + epoxy asphalt pavement and steel box girder， using a specific bridge as the engineering case. Based on a large number of real bridge monitoring data， the data analysis was carried out on service conditions and structural responses， such as temperature， vehicle speed， load， and characteristic values of structural response. The relations between different factors and the strain of steel deck-U-rib welds were studied and analyzed， and the multi-dimensional correlation rule of structural dynamic responses was established. The research showed that the strain amplitude of the weld seams in the cast+epoxy pavement structural steel deck-U-rib was linearly related to the axle load， and the strain magnitude increased as the axle load increased. For the same axle load， when the speed increased from 40 km/h to 70 km/h， the evaluated strain decreased by 28%。 When the temperature rose from 5 ℃ to 50 ℃， the average strain increased by 24%. Based on the real bridge monitoring data， a multi-factor regression model was established to quantify the relationship between weld strain and factors such as axle load， vehicle speed， and temperature. The model was then applied to predict strain variations in the weld seams.
2025, 55(7): 109-118.
doi: 10.3724/j.gyjzG24060304
Abstract:
Orthotropic steel decks are prone to fatigue damage under repeated traffic loads， which poses a serious threat to the safe and healthy operation of bridges. By using large-scale bridge health monitoring data， the fatigue damage of orthotropic steel bridge decks can be predicted. In this paper， a fatigue damage prognosis method for steel bridge decks based on long short-term memory （LSTM） neural network is proposed. This method enables long-term fatigue damage prognosis of steel bridge decks， allowing early assessment of bridge health status and providing an effective reference for fatigue evaluation of steel bridges. First， the characteristics of LSTM neural networks and fatigue damage sequences were studied and analyzed. Fatigue damage sequences are essentially a type of time series， making them highly suitable for modeling and prediction using LSTM neural networks. The stress characteristics and damage sequence characteristics of four measuring points were analyzed for two types of fatigue details： roof and longitudinal rib welding details， and transverse partition and longitudinal rib cross structural details. The hourly damage sequence was selected as the dataset for training. The effects of the number of hidden layers of the model， the number of neurons in the hidden layer， the output step-size of the prediction， the size of the dataset， the model prediction method and the model update method on the prediction accuracy of the model were explored. A neural network with LSTM and long term memory was established to realize the accurate prediction of the fatigue damage after one month of the two fatigue details.
Orthotropic steel decks are prone to fatigue damage under repeated traffic loads， which poses a serious threat to the safe and healthy operation of bridges. By using large-scale bridge health monitoring data， the fatigue damage of orthotropic steel bridge decks can be predicted. In this paper， a fatigue damage prognosis method for steel bridge decks based on long short-term memory （LSTM） neural network is proposed. This method enables long-term fatigue damage prognosis of steel bridge decks， allowing early assessment of bridge health status and providing an effective reference for fatigue evaluation of steel bridges. First， the characteristics of LSTM neural networks and fatigue damage sequences were studied and analyzed. Fatigue damage sequences are essentially a type of time series， making them highly suitable for modeling and prediction using LSTM neural networks. The stress characteristics and damage sequence characteristics of four measuring points were analyzed for two types of fatigue details： roof and longitudinal rib welding details， and transverse partition and longitudinal rib cross structural details. The hourly damage sequence was selected as the dataset for training. The effects of the number of hidden layers of the model， the number of neurons in the hidden layer， the output step-size of the prediction， the size of the dataset， the model prediction method and the model update method on the prediction accuracy of the model were explored. A neural network with LSTM and long term memory was established to realize the accurate prediction of the fatigue damage after one month of the two fatigue details.
2025, 55(7): 119-130.
doi: 10.3724/j.gyjzG25051801
Abstract:
This paper is aimed to study the applicability of digital image correlation （DIC） technology in the protection of wooden cultural relics and the complex damage characteristics of the Dou-Gong under compression due to wood anisotropy. Firstly， new woods were used to verify the applicability of DIC in the mechanical properties testing of wood， and then DIC technology was applied to the replaced original components of the Dou-Gong of Chongshan Temple to obtain its compressive elastic constants， and its surface strain field evolution and crack extension process were analyzed based on DIC. The results showed that： 1） DIC had better reliability and robustness in wood testing， the average value of the deviation of the elastic modulus from the results by the traditional method was 8.29%， and the average value of the variation coefficient of each parameter was 8.07%； 2） the compressive elastic parameters of the arch timber were measured by DIC， and the proportional limiting strengths and elastic modulus ratios of the longitudinal and tangential directions were 9.51 and 24.56， respectively； 3） the compressed specimen surfaces of the Dou-Gong timbers in the longitudinal direction produced transverse and oblique vertical composite splits and diagonal splits， the radial direction produced out-of-face compression bending and shear diagonal cracks， and overall compression bending occurred in the tangential direction； 4） crack evolution showed a three-stage characteristic， with a growth rate of the maximum crack length of longitudinal direction specimens appearing in the crack macroscopic stage of 1.35 mm/s， and the growth rates of the maximum crack length in the radial direction and the tangential direction appearing in the crack expansion stage， of 2.08 mm/s and 0.94 mm/s， respectively.
This paper is aimed to study the applicability of digital image correlation （DIC） technology in the protection of wooden cultural relics and the complex damage characteristics of the Dou-Gong under compression due to wood anisotropy. Firstly， new woods were used to verify the applicability of DIC in the mechanical properties testing of wood， and then DIC technology was applied to the replaced original components of the Dou-Gong of Chongshan Temple to obtain its compressive elastic constants， and its surface strain field evolution and crack extension process were analyzed based on DIC. The results showed that： 1） DIC had better reliability and robustness in wood testing， the average value of the deviation of the elastic modulus from the results by the traditional method was 8.29%， and the average value of the variation coefficient of each parameter was 8.07%； 2） the compressive elastic parameters of the arch timber were measured by DIC， and the proportional limiting strengths and elastic modulus ratios of the longitudinal and tangential directions were 9.51 and 24.56， respectively； 3） the compressed specimen surfaces of the Dou-Gong timbers in the longitudinal direction produced transverse and oblique vertical composite splits and diagonal splits， the radial direction produced out-of-face compression bending and shear diagonal cracks， and overall compression bending occurred in the tangential direction； 4） crack evolution showed a three-stage characteristic， with a growth rate of the maximum crack length of longitudinal direction specimens appearing in the crack macroscopic stage of 1.35 mm/s， and the growth rates of the maximum crack length in the radial direction and the tangential direction appearing in the crack expansion stage， of 2.08 mm/s and 0.94 mm/s， respectively.
2025, 55(7): 131-142.
doi: 10.3724/j.gyjzG25031702
Abstract:
This paper systematically reviews advancements in bolt loosening and loss detection， weld defect identification， local deformation monitoring， and corrosion localization and severity assessment. To address the limitations of traditional manual-feature-based methods—such as poor environmental adaptability—deep learning and 3D reconstruction techniques have been employed to enable automatic feature extraction， multi-scale detection， and spatial deformation quantification， greatly enhancing detection accuracy and intelligence. To overcome challenges such as complex background interference and small-target omission， researchers have introduced attention mechanisms， feature pyramid networks， multimodal data fusion， and semi-supervised transfer learning to improve model robustness and generalization. Nevertheless， current technologies still face challenges including insufficient dataset diversity， limited algorithm robustness， and difficulties in real-time deployment. Future development directions will include strengthening multimodal collaborative sensing and 3D reconstruction integration， building continuously adaptive learning models， enabling real-time cloud-edge collaborative analysis， and advancing intelligent inspection systems integrated with digital twin frameworks. These advancements will drive the maintenance of steel structures towards full automation， intelligence， and systematization.
This paper systematically reviews advancements in bolt loosening and loss detection， weld defect identification， local deformation monitoring， and corrosion localization and severity assessment. To address the limitations of traditional manual-feature-based methods—such as poor environmental adaptability—deep learning and 3D reconstruction techniques have been employed to enable automatic feature extraction， multi-scale detection， and spatial deformation quantification， greatly enhancing detection accuracy and intelligence. To overcome challenges such as complex background interference and small-target omission， researchers have introduced attention mechanisms， feature pyramid networks， multimodal data fusion， and semi-supervised transfer learning to improve model robustness and generalization. Nevertheless， current technologies still face challenges including insufficient dataset diversity， limited algorithm robustness， and difficulties in real-time deployment. Future development directions will include strengthening multimodal collaborative sensing and 3D reconstruction integration， building continuously adaptive learning models， enabling real-time cloud-edge collaborative analysis， and advancing intelligent inspection systems integrated with digital twin frameworks. These advancements will drive the maintenance of steel structures towards full automation， intelligence， and systematization.
2025, 55(7): 143-151.
doi: 10.3724/j.gyjzG25071002
Abstract:
In this paper， seismic tests of reinforced concrete （RC） column were conducted， based on which the post-earthquake damage dataset of RC member was established considering the additional data obtained externally. A lightweight model， i.e. FG-YOLOv5， was then proposed by replacing the backbone of YOLOv5 model with the FasterNet network and introducing the C3Ghost module and GhostConv in the neck of YOLOv5 model. Based on the dataset， the FG-YOLOv5 model was trained and tested and the ablation test was also carried out. Finally， the model was deployed on a smartphone to achieve rapid post-earthquake damage detection of RC members. The results showed that， compared to the conventional convolution， the partial convolution and GhostConv can greatly reduce the computational cost. By introducing the FasterNet， C3Ghost module and Ghostconv into the YOLO v5 model， greatly smaller model size and computation with a bit higher detection accuracy can be achieved. The FG-YOLOv5 model proposed in this paper can be conveniently deployed on mobile phones for rapid post-earthquake damage detection of RC members.
In this paper， seismic tests of reinforced concrete （RC） column were conducted， based on which the post-earthquake damage dataset of RC member was established considering the additional data obtained externally. A lightweight model， i.e. FG-YOLOv5， was then proposed by replacing the backbone of YOLOv5 model with the FasterNet network and introducing the C3Ghost module and GhostConv in the neck of YOLOv5 model. Based on the dataset， the FG-YOLOv5 model was trained and tested and the ablation test was also carried out. Finally， the model was deployed on a smartphone to achieve rapid post-earthquake damage detection of RC members. The results showed that， compared to the conventional convolution， the partial convolution and GhostConv can greatly reduce the computational cost. By introducing the FasterNet， C3Ghost module and Ghostconv into the YOLO v5 model， greatly smaller model size and computation with a bit higher detection accuracy can be achieved. The FG-YOLOv5 model proposed in this paper can be conveniently deployed on mobile phones for rapid post-earthquake damage detection of RC members.
2025, 55(7): 152-161.
doi: 10.3724/j.gyjzG25051205
Abstract:
The formation and development of cracks in brick walls is a gradual process. If the management unit ignores dynamic changes during daily inspections， it is highly likely to pose a threat to the safety of people's lives and property. To address the problems of high risk， low efficiency， and high cost existing in traditional manual detection methods， this paper proposes an improved SSG-YOLOv8n model. Based on the basic architecture of YOLOv8n， this model significantly enhances the recognition and detection accuracy of the crack patterns of brick walls by introducing the SPD Conv convolution module， adding a small target detection head， and embedding the SAFM attention mechanism module. The experimental data showed that the mAP@50 index of the improved model was 4.3% higher than that of the original YOLOv8n model. To balance detection accuracy improvement and model complexity control， the GhostNet lightweight module was further integrated. While maintaining the accuracy advantage， it significantly reduced floating-point operations， parameter count， and model size. The experimental results indicated that the improved model achieved both high detection accuracy and computational efficiency， providing important technical support for automated crack pattern detection in brick walls.
The formation and development of cracks in brick walls is a gradual process. If the management unit ignores dynamic changes during daily inspections， it is highly likely to pose a threat to the safety of people's lives and property. To address the problems of high risk， low efficiency， and high cost existing in traditional manual detection methods， this paper proposes an improved SSG-YOLOv8n model. Based on the basic architecture of YOLOv8n， this model significantly enhances the recognition and detection accuracy of the crack patterns of brick walls by introducing the SPD Conv convolution module， adding a small target detection head， and embedding the SAFM attention mechanism module. The experimental data showed that the mAP@50 index of the improved model was 4.3% higher than that of the original YOLOv8n model. To balance detection accuracy improvement and model complexity control， the GhostNet lightweight module was further integrated. While maintaining the accuracy advantage， it significantly reduced floating-point operations， parameter count， and model size. The experimental results indicated that the improved model achieved both high detection accuracy and computational efficiency， providing important technical support for automated crack pattern detection in brick walls.
2025, 55(7): 162-170.
doi: 10.3724/j.gyjzG24110806
Abstract:
The horizontal hidden-frame glass curtain wall is a common form of building envelope. The absence of lower-edge brackets directly affects the structural safety of the curtain wall during the operation and maintenance phase. This paper focuses on the brackets of the horizontal hidden-frame glass curtain wall and proposes a non-destructive detection method for missing brackets. Unmanned aerial vehicles （UAVs） equipped with visible-light sensors and infrared thermal imaging cameras are employed to collect data on these brackets， enabling the 3D modeling of building facades for analysis. The deep learning target detection algorithm YOLOv8 is used to detect the bracket targets in infrared thermograms of the glass curtain wall. A dataset is formed for the screened missing results of the glass curtain wall brackets， allowing defects to be visually positioned in the three-dimensional model and retrieved at any time. An application report for detecting missing brackets can be generated to document their locations and quantities， forming a complete inspection workflow—from data collection and processing to visualization—through a visualization software platform. This system helps assess the health status of the curtain wall structure， supports its operation and maintenance， and extends its service life.
The horizontal hidden-frame glass curtain wall is a common form of building envelope. The absence of lower-edge brackets directly affects the structural safety of the curtain wall during the operation and maintenance phase. This paper focuses on the brackets of the horizontal hidden-frame glass curtain wall and proposes a non-destructive detection method for missing brackets. Unmanned aerial vehicles （UAVs） equipped with visible-light sensors and infrared thermal imaging cameras are employed to collect data on these brackets， enabling the 3D modeling of building facades for analysis. The deep learning target detection algorithm YOLOv8 is used to detect the bracket targets in infrared thermograms of the glass curtain wall. A dataset is formed for the screened missing results of the glass curtain wall brackets， allowing defects to be visually positioned in the three-dimensional model and retrieved at any time. An application report for detecting missing brackets can be generated to document their locations and quantities， forming a complete inspection workflow—from data collection and processing to visualization—through a visualization software platform. This system helps assess the health status of the curtain wall structure， supports its operation and maintenance， and extends its service life.
2025, 55(7): 171-181.
doi: 10.3724/j.gyjzG24061308
Abstract:
Research on water adaptability in traditional settlements can help understand the fundamental principles of their spatial morphological evolution， providing a historical basis for the sustainable development of settlements. Over the past 40 years， despite research in this field has received extensive and continuous attention， there has been a lack of universal understanding of its concepts and systematic construction of its framework. This study aims to resolve the above deficiencies by collecting， analyzing， and summarizing relevant domestic and international literature： using the CiteSpace visualization tool to analyze the historical evolution and research hotspots； identifying the relevant concepts of water adaptability； constructing a content framework for spatial morphological water adaptability research； analyzing key research topics； reviewing current challenges； and conducting a research trend analysis.
Research on water adaptability in traditional settlements can help understand the fundamental principles of their spatial morphological evolution， providing a historical basis for the sustainable development of settlements. Over the past 40 years， despite research in this field has received extensive and continuous attention， there has been a lack of universal understanding of its concepts and systematic construction of its framework. This study aims to resolve the above deficiencies by collecting， analyzing， and summarizing relevant domestic and international literature： using the CiteSpace visualization tool to analyze the historical evolution and research hotspots； identifying the relevant concepts of water adaptability； constructing a content framework for spatial morphological water adaptability research； analyzing key research topics； reviewing current challenges； and conducting a research trend analysis.
2025, 55(7): 182-193.
doi: 10.3724/j.gyjzG24101903
Abstract:
Addressing the issues of low sensitivity to scale and weak applicability in research on urban spatial quality， defining update areas based on spatial quality characteristics at the optimal analysis granularity has become an effective way for urban quality to guide urban renewal. The article selects the historical urban area of Hohhot as the research object， explores the optimal spatial granularity of spatial quality in the historical urban area based on spatial autocorrelation measurement indicators， and identifies the distribution characteristics of spatial quality； guiding the delineation of urban renewal areas based on the spatial differentiation characteristics， differences， and internal influencing mechanisms of the subjective and objective qualities of historical urban areas. The results show that： 1）350~400 m is the optimal spatial granularity for studying the spatial quality of the old city in Hohhot. 2）Based on the objective spatial quality characteristics， the update areas are defined as key renovation， encouraged renovation， general renovation， and reserved areas. Then， the update timing is determined based on the subjective and objective spatial quality matching index， namely the short-term， medium-term， and long-term improvement areas. 3）Identify the type of update area and corresponding update approach based on the impact mechanism of objective built environment indicators on subjective quality. The construction of research technology logic has theoretical and practical significance for delineating update areas， clarifying update timing， and identifying update pathways in the process of spatial planning practice.
Addressing the issues of low sensitivity to scale and weak applicability in research on urban spatial quality， defining update areas based on spatial quality characteristics at the optimal analysis granularity has become an effective way for urban quality to guide urban renewal. The article selects the historical urban area of Hohhot as the research object， explores the optimal spatial granularity of spatial quality in the historical urban area based on spatial autocorrelation measurement indicators， and identifies the distribution characteristics of spatial quality； guiding the delineation of urban renewal areas based on the spatial differentiation characteristics， differences， and internal influencing mechanisms of the subjective and objective qualities of historical urban areas. The results show that： 1）350~400 m is the optimal spatial granularity for studying the spatial quality of the old city in Hohhot. 2）Based on the objective spatial quality characteristics， the update areas are defined as key renovation， encouraged renovation， general renovation， and reserved areas. Then， the update timing is determined based on the subjective and objective spatial quality matching index， namely the short-term， medium-term， and long-term improvement areas. 3）Identify the type of update area and corresponding update approach based on the impact mechanism of objective built environment indicators on subjective quality. The construction of research technology logic has theoretical and practical significance for delineating update areas， clarifying update timing， and identifying update pathways in the process of spatial planning practice.
2025, 55(7): 194-203.
doi: 10.3724/j.gyjzG24020603
Abstract:
Parameters such as the hollow ratio and reinforcement ratio can significantly influence the behavior of reinforced hollow square high-strength concrete-filled steel tubular columns （RHSCFSTs）. However， current material constitutive models and finite element modeling methods fail to account for these effects. Besides， the data used for the modelling of concrete-filled steel tubes with high strength concrete is relatively small. The data adopted in existing models differs from each other. Therefore， this paper investigated the finite element modelling procedures for RHSCFST and the corresponding material constitutive models. Based on all collected test data from 57 groups of specimens， the reliable constitutive models for both concrete and steel were established through a combined approach of theoretical derivation and regression analysis. After then， the predicted results from the proposed models were compared with all the test data. The results showed that the proposed models could reasonably predict the axial load-deformation curve of RHSCFST members. The mean ratios of predicted-to-measured values for axial compressive capacity， peak strain， and post-peak residual capacity were 0.975， 0.981， and 1.034， respectively， with corresponding coefficients of variation of 0.088， 0.205， and 0.179.
Parameters such as the hollow ratio and reinforcement ratio can significantly influence the behavior of reinforced hollow square high-strength concrete-filled steel tubular columns （RHSCFSTs）. However， current material constitutive models and finite element modeling methods fail to account for these effects. Besides， the data used for the modelling of concrete-filled steel tubes with high strength concrete is relatively small. The data adopted in existing models differs from each other. Therefore， this paper investigated the finite element modelling procedures for RHSCFST and the corresponding material constitutive models. Based on all collected test data from 57 groups of specimens， the reliable constitutive models for both concrete and steel were established through a combined approach of theoretical derivation and regression analysis. After then， the predicted results from the proposed models were compared with all the test data. The results showed that the proposed models could reasonably predict the axial load-deformation curve of RHSCFST members. The mean ratios of predicted-to-measured values for axial compressive capacity， peak strain， and post-peak residual capacity were 0.975， 0.981， and 1.034， respectively， with corresponding coefficients of variation of 0.088， 0.205， and 0.179.
2025, 55(7): 204-215.
doi: 10.3724/j.gyjzG22122506
Abstract:
A novel prefabricated frame structure system was proposed， featuring "prefabricated beams and columns， prefabricated joints， and post-cast UHPC connections". A prefabricated frame and a cast-in-place frame were designed， and quasi-static tests were sequentially conducted to investigate their seismic performance. The test results showed that the overall seismic performance of the new prefabricated frame was equivalent to that of the cast-in-place one. Subsequently， a prefabricated frame model was established using finite element software. The numerical simulation results exhibited good agreement with the test results： the concrete damage patterns were similar， the yield load and maximum bearing capacity showed minor deviations， the energy dissipation capacity was comparable， and the hysteresis curves as well as the skeleton curves demonstrated high consistency. On this basis， the effects of beam longitudinal reinforcement ratio， column axial compression ratio， and concrete strength on the seismic performance of the novel prefabricated frame were investigated individually.The parametric analysis results showed that with the increase of longitudinal reinforcement rate of the beam， the bearing capacity increased significantly， while the energy dissipation capacity decreased。 The displacement ductility showed a trend of increasing first and then decreasing， the displacement ductility reached the maximum when the reinforcement ratio was 1.3%. The column axial compression ratio was varied within 0.75， with the increase of axial compression ratio， the bearing capacity of the prefabricated frame showed minimal change and remained at a high level， but its ductility and energy dissipation capacity decreased. With the increase of concrete strength， the bearing capacity of the prefabricated frame increased， while the structural ductility decreased. However， when the concrete grade exceeded C50， the bearing capacity of the prefabricated frame could not be improved further.
A novel prefabricated frame structure system was proposed， featuring "prefabricated beams and columns， prefabricated joints， and post-cast UHPC connections". A prefabricated frame and a cast-in-place frame were designed， and quasi-static tests were sequentially conducted to investigate their seismic performance. The test results showed that the overall seismic performance of the new prefabricated frame was equivalent to that of the cast-in-place one. Subsequently， a prefabricated frame model was established using finite element software. The numerical simulation results exhibited good agreement with the test results： the concrete damage patterns were similar， the yield load and maximum bearing capacity showed minor deviations， the energy dissipation capacity was comparable， and the hysteresis curves as well as the skeleton curves demonstrated high consistency. On this basis， the effects of beam longitudinal reinforcement ratio， column axial compression ratio， and concrete strength on the seismic performance of the novel prefabricated frame were investigated individually.The parametric analysis results showed that with the increase of longitudinal reinforcement rate of the beam， the bearing capacity increased significantly， while the energy dissipation capacity decreased。 The displacement ductility showed a trend of increasing first and then decreasing， the displacement ductility reached the maximum when the reinforcement ratio was 1.3%. The column axial compression ratio was varied within 0.75， with the increase of axial compression ratio， the bearing capacity of the prefabricated frame showed minimal change and remained at a high level， but its ductility and energy dissipation capacity decreased. With the increase of concrete strength， the bearing capacity of the prefabricated frame increased， while the structural ductility decreased. However， when the concrete grade exceeded C50， the bearing capacity of the prefabricated frame could not be improved further.
2025, 55(7): 216-226.
doi: 10.3724/j.gyjzG23102413
Abstract:
In order to study the buckling performance and the bearing capacity design method of cold-formed thin-walled equal-legged lipped angle columns， axial compression tests were conducted on 32 LQ550 equal-legged lipped angle columns with different cross-sections and slenderness ratios. The results showed that long columns with small width-to-thickness ratios exhibited global flexural-torsional buckling， while short columns with larger width-to-thickness ratios experienced local buckling. Other specimens demonstrated the interactive buckling with local buckling and flexural-torsional buckling， and the specimens with torsional buckling all showed the post-torsional buckling strength. ABAQUS finite element software was then used to simulate the specimens. The simulation results were in good agreement with the test results， indicating that the established finite element analysis model was both reasonable and feasible. Therefore， the effects of the slenderness ratio， width-thickness ratio， and leg-lip ratio on the buckling performance of cold-formed thin-walled equal-legged lipped angle steel under axial compression were analyzed using finite element software. The analysis showed that the ultimate bearing capacity of the angle steel decreased greatly with the increase of slenderness ratio. When the angle steel had the same length， the ultimate bearing capacity increased with the increase of width-to-thickness ratio. Increasing the width of the lips enhanced the ultimate bearing capacity； however， when local buckling occurred at the lips， the rate of increase in the ultimate capacity slowed down. Finally， based on the test results， the effective width method and the direct strength method were proposed to calculate the bearing capacity of cold-formed thin-walled equal-legged lipped angle steel members under axial compression. The results of comparison with test and finite element analysis showed that the proposed methods were accurate and feasible.
In order to study the buckling performance and the bearing capacity design method of cold-formed thin-walled equal-legged lipped angle columns， axial compression tests were conducted on 32 LQ550 equal-legged lipped angle columns with different cross-sections and slenderness ratios. The results showed that long columns with small width-to-thickness ratios exhibited global flexural-torsional buckling， while short columns with larger width-to-thickness ratios experienced local buckling. Other specimens demonstrated the interactive buckling with local buckling and flexural-torsional buckling， and the specimens with torsional buckling all showed the post-torsional buckling strength. ABAQUS finite element software was then used to simulate the specimens. The simulation results were in good agreement with the test results， indicating that the established finite element analysis model was both reasonable and feasible. Therefore， the effects of the slenderness ratio， width-thickness ratio， and leg-lip ratio on the buckling performance of cold-formed thin-walled equal-legged lipped angle steel under axial compression were analyzed using finite element software. The analysis showed that the ultimate bearing capacity of the angle steel decreased greatly with the increase of slenderness ratio. When the angle steel had the same length， the ultimate bearing capacity increased with the increase of width-to-thickness ratio. Increasing the width of the lips enhanced the ultimate bearing capacity； however， when local buckling occurred at the lips， the rate of increase in the ultimate capacity slowed down. Finally， based on the test results， the effective width method and the direct strength method were proposed to calculate the bearing capacity of cold-formed thin-walled equal-legged lipped angle steel members under axial compression. The results of comparison with test and finite element analysis showed that the proposed methods were accurate and feasible.
2025, 55(7): 227-236.
doi: 10.3724/j.gyjzG25052207
Abstract:
In practical engineering structures， bolts often operate under tensile-shear combined stress states， whereas current design codes only provide calculation methods for bolt fatigue life under pure tension or pure shear loads. Therefore， this study conducted tensile-shear fatigue tests on bolts using a specially designed testing device. Fatigue tests were performed at five different loading angles （0° pure tension， 30° tensile-shear， 45° tensile-shear， 60° tensile-shear， and 90° pure shear） to analyze the influence of tensile-shear angles on bolt fatigue life. The S-N curves under different angles were unified based on Mises stress， and the effects of bolt material and diameter on fatigue life were discussed. The results showed that under the same loading force， bolts in tensile-shear combined states were more prone to fatigue failure compared to pure tension or shear load. At different tensile-shear angles， the fatigue life of bolts increased with the increase of material strength. Material influence coefficients for different angles were proposed： compared with 8.8-grade high-strength bolts， the fatigue strength of 4.8-grade and 6.8-grade bolts decreased by approximately 5% and 2%， respectively， while that of 10.9-grade high-strength bolts increased by approximately 21%. Under the same stress， the fatigue life of bolts first increased and then decreased with the increase of bolt diameter. Compared with M8 bolts， the diameter amplification factors for M16， M30， and M42 bolts were approximately 1.24， 1.37， and 1.07， respectively.
In practical engineering structures， bolts often operate under tensile-shear combined stress states， whereas current design codes only provide calculation methods for bolt fatigue life under pure tension or pure shear loads. Therefore， this study conducted tensile-shear fatigue tests on bolts using a specially designed testing device. Fatigue tests were performed at five different loading angles （0° pure tension， 30° tensile-shear， 45° tensile-shear， 60° tensile-shear， and 90° pure shear） to analyze the influence of tensile-shear angles on bolt fatigue life. The S-N curves under different angles were unified based on Mises stress， and the effects of bolt material and diameter on fatigue life were discussed. The results showed that under the same loading force， bolts in tensile-shear combined states were more prone to fatigue failure compared to pure tension or shear load. At different tensile-shear angles， the fatigue life of bolts increased with the increase of material strength. Material influence coefficients for different angles were proposed： compared with 8.8-grade high-strength bolts， the fatigue strength of 4.8-grade and 6.8-grade bolts decreased by approximately 5% and 2%， respectively， while that of 10.9-grade high-strength bolts increased by approximately 21%. Under the same stress， the fatigue life of bolts first increased and then decreased with the increase of bolt diameter. Compared with M8 bolts， the diameter amplification factors for M16， M30， and M42 bolts were approximately 1.24， 1.37， and 1.07， respectively.
2025, 55(7): 237-244.
doi: 10.3724/j.gyjzG22090902
Abstract:
The law of preload loss is an important basis for determining tightening technology and quality inspection in high-strength bolt connections. The bolt preload of 10 groups of stainless steel high-strength bolted standard specimens was tracked for a long time under six kinds of faying surface treatments， such as the grit blasting， heavy brushing， mechanical scoring， anti-slip coating， hot rolling， and mirror surface. The results showed that the preload decreased rapidly after final tightening， with the loss rate gradually slowing over time. The preload loss within the first hour after the tightening accounted for 50% of the total loss， and the loss stabilized after 24 hours. Larger slip resistance coefficients of the friction surfaces resulted in greater bolt preload loss. The laws of bolt preload loss for all specimens in the test were statistically analyzed and fitted. The results showed that for the specimens in the test， the final loss of preload with a 95% assurance rate was about 7.2%， which was similar to that of high-strength bolted connections in steel structures under the same conditions. Based on the results of this study， it is suggested that the preload inspection of stainless steel high-strength bolt connections should be conducted within 6 to 24 hours after final tightening.
The law of preload loss is an important basis for determining tightening technology and quality inspection in high-strength bolt connections. The bolt preload of 10 groups of stainless steel high-strength bolted standard specimens was tracked for a long time under six kinds of faying surface treatments， such as the grit blasting， heavy brushing， mechanical scoring， anti-slip coating， hot rolling， and mirror surface. The results showed that the preload decreased rapidly after final tightening， with the loss rate gradually slowing over time. The preload loss within the first hour after the tightening accounted for 50% of the total loss， and the loss stabilized after 24 hours. Larger slip resistance coefficients of the friction surfaces resulted in greater bolt preload loss. The laws of bolt preload loss for all specimens in the test were statistically analyzed and fitted. The results showed that for the specimens in the test， the final loss of preload with a 95% assurance rate was about 7.2%， which was similar to that of high-strength bolted connections in steel structures under the same conditions. Based on the results of this study， it is suggested that the preload inspection of stainless steel high-strength bolt connections should be conducted within 6 to 24 hours after final tightening.
2025, 55(7): 245-253.
doi: 10.3724/j.gyjzG24080205
Abstract:
A series of tests， including corrosion resistance， compressive strength， and microscopic analysis， were conducted on foam concrete under the combined action of chloride-sulfate composite salt solution. The study investigated the influence of the composite salt environment on the durability of foam concrete， focusing on mass change， compressive strength， and microstructure.The results indicate that under the erosion effect of the composite salt solution， a large number of white crystals formed on the surface of the specimens in the early stages. Additionally， damage to the specimens initially appeared at the edges and corners. The higher the density of foam concrete， the smaller the surface damage would be. The mass change rate of the foam concrete specimens was closely related to their density under the corrosion of the composite salt solution， and the overall mass change trend of the specimens first increased and then decreased. The resistance of foam concrete to compound salt attack increased with the increase of density， which was mainly reflected in the apparent damage， mass change， and strength change of the specimens. There was an interaction between the two salts， and the presence of chloride ions could inhibit sulfate corrosion to some extent.
A series of tests， including corrosion resistance， compressive strength， and microscopic analysis， were conducted on foam concrete under the combined action of chloride-sulfate composite salt solution. The study investigated the influence of the composite salt environment on the durability of foam concrete， focusing on mass change， compressive strength， and microstructure.The results indicate that under the erosion effect of the composite salt solution， a large number of white crystals formed on the surface of the specimens in the early stages. Additionally， damage to the specimens initially appeared at the edges and corners. The higher the density of foam concrete， the smaller the surface damage would be. The mass change rate of the foam concrete specimens was closely related to their density under the corrosion of the composite salt solution， and the overall mass change trend of the specimens first increased and then decreased. The resistance of foam concrete to compound salt attack increased with the increase of density， which was mainly reflected in the apparent damage， mass change， and strength change of the specimens. There was an interaction between the two salts， and the presence of chloride ions could inhibit sulfate corrosion to some extent.
