To study the freeze-thaw durability of different types of recycled aggregate seawater sea-sand concrete (SWSSC) in freeze-thaw dominated environments of cold regions, a compressive strength degradation prediction model [GM(1,1)] was constructed based on grey theory in this paper, and the synergistic effects of the number of freeze-thaw cycles, recycled aggregate types, and replacement rates on compressive strength were analyzed. Experimental and model prediction results indicate that the compressive strength of concrete shows a nonlinear attenuation with the increase of freeze-thaw cycles. The deterioration of recycled brick aggregate concrete is the most significant; after 75 freeze-thaw cycles, its strength is 14.50 MPa, which decreases by 57.2% compared with unfrozen concrete; after 300 freeze-thaw cycles, the strength is only 1.43 MPa, with a decrease of 90%, and the high water absorption and low crushing index of recycled brick aggregate are the main reasons. For every 20% increase in the replacement rate of recycled aggregate, the strength loss of recycled brick aggregate concrete after 75 freeze-thaw cycles increases by 22.8%; therefore, it is recommended to control its replacement rate within 20%. The prediction accuracy of the GM(1,1) model is “excellent” (p = 1, C < 0.35), with a maximum residual of 1.84 MPa and a relative error of 9.79%, which verifies the reliability of grey theory under poor information conditions. This study provides a theoretical basis for the mix proportion optimization and service life assessment of recycled aggregate concrete in freeze-thaw dominated environments of cold regions and offers an engineering reference for the resource utilization of construction waste and the substitution of river sand.
In recent years, ship-bridge collisions have occurred frequently, significantly increasing the risk of damage to bridge substructures. To evaluate the safety performance of the damaged double-column pier and determine the optimal reinforcement scheme, the ship collision accident involving Xietang Bridge was used as the engineering case study. Several feasible reinforcement measures were proposed, and the impact resistance of each scheme was compared using finite element simulations. The results show that, among the two impact conditions with different loading states, the peak impact force under the fully loaded condition is 2.68 MN, and the residual displacement on the impacted side of the pile cap is approximately 291 mm, indicating that a collision with a fully loaded standard cargo vessel is the most likely cause of the actual accident. Under the same impact conditions, compared with the unreinforced pier, the pier strengthened using the section-enlargement scheme has a 47.7% higher peak impact force and provides the greatest improvement in the impact resistance of the bridge with double-column piers. The impact angle has a greater influence on the impact duration and the dynamic response of the bridge, thus increasing the risk of overall bridge collapse. This study provides a reference for ship-collision assessment and reinforcement design of bridges with double-column piers.
Based on the 2# pipe jacking project in the south line of Shiyan, Shenzhen, the construction influence and reinforcement scheme of super-large diameter double circular pipe jacking side-crossing dense building areas were studied by adopting Midas-GTS/NX finite element software and field monitoring data. The results show that the influence of pipe jacking construction on the displacement of the front pile is greater than that of the back pile, and the longitudinal displacement of the pile (the displacement along the excavation direction of pipe jacking) is most affected in the range of two times the diameter of the central axis of pipe jacking and 1.5 times the diameter of the buried depth of the pile, showing U-shaped distribution. The lateral displacement of the affected pile (horizontal displacement perpendicular to the direction of pipe jacking excavation) presents S-shaped distribution when the excavation is completed on the left and right lines. The lateral displacement of the pile in the deeper stratum is larger than that in the shallow stratum, and the extreme displacement occurs in the section where the pipe is excavated. The vertical displacement of the pile (the direction of the pile axis) is negative, and the closer distance to pipe jacking leads to greater influence, with the settlement value of the pile top smaller than that of the pile end. Without reinforcement measures, the maximum lateral horizontal displacement of the pile is 9.41 mm, which meets the requirements, but the maximum longitudinal horizontal displacement is 14.76 mm and the maximum vertical settlement is 13.03 mm, both of which are beyond the allowable value range. After taking the sleeve valve pipe grouting reinforcement measures, the maximum longitudinal displacement of the pile is 8.98 mm, the maximum lateral displacement is 5.64 mm, and the maximum vertical displacement is 8.86 mm, all of which meet the control requirements. The reinforcement achieves a remarkable effect, enabling the smooth side crossing of super-large diameter double circular pipes beneath the dense building areas.
The influence of phosphogypsum dosages on geopolymer performance was investigated to address the high drying shrinkage and slow later-stage strength development of all-solid-waste geopolymer materials. Combined with XRD, SEM, and MIP test results, the effects of phosphogypsum on the properties and microstructure of geopolymer materials were discussed. The results indicate that the incorporation of phosphogypsum reduces the early-stage compressive strength of the geopolymer. However, as the curing age increases, the strength continues to grow and stabilizes by 28 d. Meanwhile, phosphogypsum effectively inhibits early drying shrinkage of geopolymer and induces controlled micro-expansion in the later stage. The reaction of phosphogypsum exhibits significant delayed participation, and its dissolution is limited initially, with alkali-activated slag reaction dominating the system. In the later stage, phosphogypsum gradually participates in the reaction, promoting the formation of ettringite and thereby enhancing the strength. The formation of ettringite significantly optimizes the pore structure. As the phosphogypsum dosage increases from 0% to 15%, the total porosity decreases from 22.06% to 20.55%, the number of harmful pores reduces, and the material structure becomes denser. The proportion of fine capillary pores decreases from 40.79% to 23.91%, significantly improving the resistance to drying shrinkage.
Suspension bridges are characterized by low longitudinal stiffness and large deformation. To reduce the longitudinal displacement at the girder ends and the required movement capacity of the expansion joints, static and dynamic finite element analysis models of the main bridge were established based on the Labo Chongtian River Bridge. The effects of two longitudinal restraint systems, including a central buckle combined with longitudinal dampers and a static displacement-limiting and dynamic damping system, on the static and dynamic responses of key structural components were analyzed. The two systems were compared to identify an appropriate longitudinal restraint system, and a parametric analysis of the selected system was conducted. The results show that, without any longitudinal restraint measures, the required movement capacity of the expansion joints of the Labo Chongtian River Bridge is at least 2 320 mm. Both the central buckle combined with longitudinal dampers and the static displacement-limiting and dynamic damping system can substantially reduce the girder-end displacement, with reductions of approximately 34%. However, the latter is easier to implement, and its construction cost is only 50% of that of the former. Therefore, it is the more appropriate longitudinal restraint system. The analysis of the displacement-limiting parameters shows that, when the limiting gap is 0.7 m and the limiting stiffness is 200 MN/m, the required movement capacity of the expansion joints of the Labo Chongtian River Bridge can be reduced to 1 520 mm, representing a reduction of 34.5%.
To summarize the key technical experience in catwalk construction for rotating-cable suspension bridges under complex mountainous conditions, this paper took the Three Gorges Bridge on the Yellow River(a single-tower and single-span rotating-cable steel truss girder suspension bridge with a main span of 540 m) as the engineering background. A two-span continuous catwalk without wind-resistant cables was used as the superstructure construction platform, and three major technical countermeasures in catwalk design and construction were systematically elaborated. In the 146 m cable-girder intersection area on the north side, the catwalk and the steel girder collided, and setting up the looping anchorage system for a catwalk was difficult. To address these problems, brackets and anchor beams were set at the front end of the anchorage for anchoring catwalk cables. Following the schedule of girder erection, the profile-shifted steel frame on the north side was installed in two stages to realize the avoidance of the catwalk from the steel girder. The bridge site was in the Three Gorges Reservoir area of the Yellow River, and the construction condition of the catwalk was poor. The pilot cable of Dyneema rope was pulled across the river from cable tower to looping anchorage by using the unmanned aerial vehicle (UAV) + sag control method. The single hook hanging method was used to erect the portal support cable, while the double-suspension-ring method was used to erect the catwalk load-bearing cable. Construction practice shows that this method has the advantages of low traction requirements, convenient sag control, and high construction efficiency, and exhibits good adaptability to bridge erection construction in the steep valley environment in mountainous areas.
Cable force optimization is a key step in ensuring a rational force state of cable-stayed bridge structures. To address the repeated iterations, complicated adjustment procedures, and low computational efficiency associated with cable force optimization using traditional finite element software, this paper combined Python with the OpenSeesPy open-source library to establish a finite element model of a cable-stayed bridge that accounted for the construction process. A trust-region optimization algorithm was adopted to minimize structural bending energy, and a method was proposed for automatically optimizing cable forces during construction and in the completed bridge. The effectiveness and applicability of the proposed method were verified through a case study of the Wuxuan Qianjiang Grand Bridge, the largest-span cable-stayed bridge in Guangxi. The results indicate that the optimized cable force distribution is reasonable, and that the variations in deformation and internal forces during bridge construction remain within controllable limits, thus ensuring the structural safety and stability of the bridge at all construction stages. The research results provide a new optimization-based computational technique for the design and construction of cable-stayed bridges.
In the subway engineering of soft soil areas, the physical indicators and static-dynamic properties of soft clay are important factors influencing subway design, construction, and project cost. In particular, during subway operation, cyclic dynamic stress induced by running trains acts on the underlying soft soil foundation of the tunnels, thus greatly affecting the operational safety and maintenance of the subway. Based on the Wenzhou Metro M1 Line project, laboratory geotechnical tests and systematic research were carried out on the soft soil through shield tunnels to obtain the basic physical indicators of Wenzhou soft clay, with its consolidation, shear characteristics, and cyclic dynamic characteristics under traffic loads analyzed. The test results indicate that the soil surrounding the shield tunnel is typical soft soil, exhibiting unfavorable engineering properties such as high water content, high void ratio, high compressibility, high sensitivity, and low strength. The preconsolidation pressure presents regular variation, while shear strength indicators show great discreteness. The consolidated undrained triaxial shear tests reveal that most soil samples exhibit strain-softening behavior, with failure line slopes ranging from 1.39 to 1.52 and critical state line (CSL) slopes between 1.47 and 1.51. Comparison between the cyclic dynamic properties of undisturbed and remolded soil shows that the strain of remolded soil is generally greater than that of undisturbed soil. A cumulative strain prediction model was built under cyclic traffic loads for both undisturbed and remolded soil.
Machine learning and intelligent optimization algorithms have been increasingly applied to construction and health monitoring of long-span cable-stayed bridges. Based on the construction history of cable-stayed bridges both domestically and internationally, an overview of the origin and development process of cable-stayed bridges was provided. Firstly, from the perspective of the entire life cycle of bridges, bridge monitoring was divided into construction period monitoring and operation period monitoring. The applications of mainstream construction monitoring methods in large cable-stayed bridge projects were elaborated, and the specific composition of bridge health monitoring systems was clarified. Secondly, the basic principles of several machine learning models and intelligent optimization algorithms were introduced, and the application status of different machine learning models and intelligent optimization algorithms such as the support vector machine (SVM), neural networks, and Bayesian networks in the monitoring and calculation of large-span cable-stayed bridge construction was analyzed. The limitations and shortcomings of existing single machine learning strategies in monitoring and calculation research on bridges were summarized, and the development direction of monitoring and calculation models for large-span cable-stayed bridges that integrate machine learning and intelligent optimization algorithms was proposed. Finally, a summary was made of the noise reduction techniques and damage identification methods of existing bridge health monitoring systems. The research shows that traditional bridge structure optimization calculation methods have certain limitations, and multi-objective bridge structure optimization methods can effectively avoid this problem. Machine learning models and intelligent optimization algorithms have been widely applied to bridge monitoring calculations, but single models are more commonly employed than cross-fusion models. The structure of the bridge health monitoring system has been relatively mature. The research mainly focuses on signal noise reduction and structural damage identification. Currently, the commonly adopted structural damage identification methods are still based on convolutional neural networks and long short-term memory models. In the future, the accuracy and reliability of bridge monitoring can be further improved by integrating artificial intelligence and intelligent optimization algorithms.
To address the safety risk prevention requirements caused by right-of-way conflicts in the mixed traffic environment of motor and non-motorized vehicles at urban intersections, a collision risk prediction method for motor and non-motorized vehicles integrating trajectory clustering and deep learning was proposed in this paper to improve the accuracy of traffic safety assessment at intersections. First, multi-type vehicle trajectory data in drone videos were extracted based on the DataFromSky software to construct a high-precision spatiotemporal dataset containing vehicle coordinates, velocities, and accelerations, and high-risk scenario trajectories were screened through the feature analysis of risk scenarios. Second, the DBSCAN spatiotemporal trajectory clustering algorithm was adopted, and the spatial radius (REps) and minimum sample size (DMinPts) were optimized in combination with the silhouette coefficient method to divide the non-motorized vehicle trajectories into conservative and aggressive types. Then, an LSTM-based time series prediction model was designed to realize the multi-step prediction of future spatiotemporal trajectories of non-motorized vehicles, and a spatiotemporal collision risk quantification model based on Euclidean distance and TTC threshold was constructed to dynamically evaluate potential collision risks. The test results indicate that the DBSCAN clustering algorithm can effectively identify the driving behavior patterns of non-motorized vehicles (with a silhouette coefficient of 0.256 6), the LSTM model can accurately predict vehicle trajectories for the future three time steps, and the spatiotemporal collision risk quantification model can proactively identify high-risk interaction scenarios. The research results can provide a quantitative decision-making basis and effective technical support for real-time risk prevention and control in mixed traffic environments.
To address the key issue of mica minerals in manufactured sand limiting concrete performance, this study compared the synergistic and differential effects of biotite and granite powder and systematically investigated the effects of biotite and mica-containing granite powder on the rheological properties, evolution of mechanical properties, and microscopic mechanisms of cement paste using TOC, XRD, FTIR, TG-DTG, and SEM, thus providing a theoretical basis for controlling mica mineral content and optimizing manufactured-sand concrete performance. The results show that both biotite and mica-containing granite powder significantly increase the plastic viscosity of cement paste, with biotite having a more pronounced effect. At a biotite dosage of 6%, the final plastic viscosity of the paste reaches 1.655 1 Pa ⋅ s, which is 122% higher than that of the control group. At a granite powder dosage of 12%, the plastic viscosity increases to 1.105 9 Pa ⋅ s, representing an increase of 48%. Both biotite and mica-containing granite powder promote the early-age strength development of cement paste through the nucleation effect, but excessive incorporation reduces its long-term strength. When the biotite dosage increases from 2% to 6%, the 28 d compressive strength of the paste decreases by 10.69 MPa. When the granite powder dosage increases from 4% to 12%, the 28 d compressive strength of the paste decreases by 17.15 MPa. Biotite and mica-containing granite powder have little effect on early hydration but significantly inhibit the later hydration process. At 28 d, both markedly reduce the formation of Ca(OH)2, ettringite, and C-(A)-S-H gel, thus limiting long-term strength development.
Asphalt pavement containing salts can delay or suppress road icing by lowering the freezing point.To evaluate the applicability of such pavement in engineering,this study compared the road performance and snow-melting and anti-icing effects of asphalt mastic crushed stone(SMA-13 containing salts)mixed with two salt additives Lvxin Ⅱ(LX Ⅱ)and Mafilon(MFL)through laboratory and field tests.The snow-melting and anti-icing effects of the SMA13 mixture containing salts and the optimal amount of salt additives were analyzed through conductivity tests,ice-melting tests,and snow-melting tests.Then,the influence of additives on the road performance of the SMA-13 mixture was evaluated.Finally,the snow-melting and anti-icing effects of two different salt SMA-13 mixtures were validated based on the icing and snow conditions in icy and snowy weather.The results show that after long-term aging,the anti-icing components(chlorides)in LX Ⅱ and MFL of the SMA-13 mixture containing salts are more easily precipitated.The two types of salt additives have no significant effect on the water stability of the SMA-13 mixture,only slightly reducing its high-temperature stability and low-temperature crack resistance.In both laboratory and field tests,LX Ⅱ shows better snow-melting and anti-icing effects than MFL.
To investigate the stability problems frequently arising in the push-from-the-rear incremental launching construction of steel box girders of curved ramp bridges, this study took the steel box girder project of the Qingshui Bridge Hub ramp bridge as the engineering background. A finite element model of the curved ramp girder‒launching nose‒support system was first established using Midas Civil. The model’s validity was verified with monitoring data of incremental launching force, stress in the girder, and axis deviation from the actual incremental launching process. Subsequently, based on the validated model, the study analyzed the mechanical properties of the steel box girder of the curved ramp bridge under four typical incremental launching conditions, confirming the safety and feasibility of the push-from-the-rear incremental launching scheme. Furthermore, three potential risk factors—axis deviation, support uplift, and asynchronous incremental launching—were investigated, and corresponding integrated stability control measures were proposed. The results demonstrate that the stresses and deformations in the ramp girder and launching nose system and supports under the four typical incremental launching working conditions meet construction requirements. The overall stability coefficient of the incremental launching system of the ramp bridge exhibits negative correlations with both axis deviation and asynchronous incremental launching rates. Among the three risk factors, support uplift is the most critical, with edge support uplift having the most significant adverse impact on structural stability. Additionally, the coupling effect of vibrations and static deviations further reduces system stability. The proposed triple-factor stability control method effectively addresses the overall stability problem facing the steel box girder of the curved ramp bridge during the push-from-the-rear incremental launching process. This study provides a closed-loop risk early warning and control analysis methodology—integrating verification, warning, and control—for similar push-from-the-rear incremental launching projects of curved steel box girders.
Lane changing is generally prohibited and strict speed limits are imposed in expressway tunnels in China. To ensure that drivers can safely and comfortably complete lane changes and speed adjustments before entering a tunnel, horizontal curves should satisfy the tunnel entrance recognition sight distance requirement, and the radii of vertical curves in the longitudinal profile should also satisfy this requirement. If the vertical curve radius of the section before a tunnel entrance is improperly designed, drivers may be unable to recognize the tunnel entrance in time, resulting in rushed lane changes or delayed speed adjustments before entering the tunnel, which can easily lead to road traffic accidents caused by improper maneuvers in front of the tunnel entrance. For the purpose of determining the minimum radius of vertical curves required on the approach to a tunnel to satisfy the tunnel entrance recognition sight distance, the tunnel entrance recognition sight distance was first defined according to drivers’ operating characteristics and driving needs when selecting lanes and adjusting speeds before entering the tunnel. Second, a vehicle lane-changing model was established using the shifted negative exponential distribution model and the constant-speed offset cosine-curve lane-changing model, and a tunnel entrance recognition sight distance calculation model was constructed. Finally, limiting and normal values for the tunnel entrance recognition sight distance were proposed, and recommended minimum radii of crest and sag vertical curves before the tunnel entrance were proposed based on these values to satisfy the tunnel entrance recognition sight distance. The results show that, when drivers decelerate before the tunnel portal, the minimum radius of the crest vertical curve that satisfies the normal value requirement of the tunnel entrance recognition sight distance is larger than the limiting value of the crest vertical curve stipulated in the Specifications for Highway Geometric Design (JTG D20—2017). Similarly, the minimum radius of the sag vertical curve that satisfies the normal value requirement of the tunnel entrance recognition sight distance is larger than the normal value of the minimum radius of the sag vertical curve stipulated in the Specifications for Highway Geometric Design (JTG D20—2017). Therefore, for sections before the entrances of long tunnels, extra-long tunnels, and other tunnels where lane changing is prohibited, the minimum radius of the vertical curve that satisfies the normal value requirement of the tunnel entrance recognition sight distance should be adopted.
Rutting is a typical distress of asphalt pavement in high-temperature and heavy-load conditions. The addition of anti-rutting agents is key to improving the high-temperature stability of asphalt mixtures. The effectiveness and modification mechanisms of various anti-rutting agents, including rock asphalt, styrene-butadiene-styrene (SBS), crumb rubber (CR), plastic modifiers (PET, PE, etc.), and thermoplastic elastomer (TPE), were systematically reviewed. The pavement performance, modification mechanism, construction technology, and performance evaluation methods of various anti-rutting agents were compared, and their modification effectiveness and limitations were analyzed to address critical technical challenges and promote the upgrading of anti-rutting modification technologies. The research indicates that all kinds of anti-rutting agents improve the high-temperature performance of asphalt mainly through physical effects such as surface adsorption, swelling and absorption of light components, and formation of polymer network structures. However, single modifiers have certain limitations: rock asphalt tends to increase the low-temperature brittleness of mixtures, SBS and plastics show poor compatibility with asphalt, CR modified systems suffer insufficient long-term service stability, and TPE materials have high cost and unsatisfactory storage stability. Composite modification can synergistically optimize the high-temperature and low-temperature performance of asphalt, and effectively improve compatibility and storage stability. At the construction process level, the dry or wet processes should be reasonably selected based on the modifier characteristics. Future research should focus on multi-component synergistic composite modification, develop green low-carbon modification technologies such as high-value utilization of solid waste and microwave pretreatment, and establish a unified and standardized evaluation system for anti-rutting performance to continuously innovate asphalt pavement anti-rutting technology toward high efficiency, durability and environmental friendliness.
Heat transfer models were built for ordinary subgrade and phase change subgrade to reveal the temperature control and heat transfer laws of phase change subgrade in permafrost regions of the Qinghai‒Tibet Plateau. The variation characteristics of temperature and heat within the subgrade were analyzed by numerical simulation. The effects of phase change materials’ phase change temperature, phase change enthalpy, and dosage on the temperature and heat of the subgrade bottom and the surface at 3.0 m height were studied. Research indicates that compared with ordinary subgrade, the phase change subgrade reduces the high temperature of the subgrade by phase change heat storage in the warm season and increases the low temperature of the subgrade by phase change heat release in the cold season. In the warm season, the heat transfer from the atmospheric environment to the phase change layer of the subgrade increases, while the heat transfer from the phase change layer of the subgrade to the subgrade foundation decreases. In the cold season, the heat transfer from the subgrade foundation to the phase change layer of the subgrade decreases, while the heat transfer from the phase change layer of the subgrade to the atmospheric environment increases. Through the cyclic alternation of warm and cold seasons, the heat of the subgrade in the warm season is transferred to the cold season, achieving the spatiotemporal redistribution of heat within the subgrade. Under the phase change temperature of 1℃, phase change enthalpy of 300 J/g, and a dosage of 15%, the annual net heat release of the subgrade foundation is reduced by 29.13 MJ/m², and the annual net heat release of the surface at 3.0 m height of the subgrade is increased by 18.62 MJ/m². This indicates that the thermal barrier effect on the foundation is greater than the heat dissipation effect on the subgrade, thus effectively improving thermal insulation performance of the subgrade.
To address the challenges such as significant surrounding rock disturbance, complex construction procedures, and long construction periods in single-side widening during the reconstruction and expansion of highway tunnels in China, this study took a typical highway tunnel reconstruction and expansion project as an example to investigate the rapid assembly technology of corrugated steel plate lining. A complete technical system was proposed, encompassing lining structure design, rapid ring-by-ring assembly techniques, and construction monitoring and control. The technology utilized a box-type corrugated steel plate lining structure. Rapid and precise circumferential and longitudinal assembly was achieved through groove-protrusion connections. Combined with an optimized construction method of “pre-reinforcement + block-by-block excavation”, this technology significantly improved construction efficiency and effectively controlled surrounding rock deformation. The research results demonstrate that this technology offers advantages such as convenient construction, a short construction period, minimal disturbance to surrounding rock, and high structural stability. It can ensure construction safety and control surrounding rock deformation. This study provides valuable reference for the design and construction of similar tunnel reconstruction and expansion projects.
To address the limitations of traditional empirical interpretation methods for advanced ground penetrating radar (GPR) detection images of tunnels, including inconsistent standards, low efficiency, and high rates of misinterpretation and missed detection, this study proposed an intelligent inversion method for radar B-scan waveform images of adverse geology based on an improved generative adversarial network (GAN). A multi-condition synthetic dataset was constructed through electromagnetic numerical simulation combined with random generation constraints of medium parameters, incorporating three types of geological anomalies (irregular cavities, fracture zones, and cracks) and their combinations. The GAN generator was optimized by integrating Unet convolutional neural network architecture and dilated convolution modules, and structural similarity (SSIM) loss function was incorporated into the loss function to enhance the extraction capability of waveform image features and model inversion performance. Training evaluation results demonstrate that the improved GAN model achieves approximately 4% and 10% higher inversion accuracy than conventional GAN and standalone Unet models, respectively. An inversion experiment using actual engineering data from fracture zone prediction was carried out. Comparative analysis with digital drilling and excavation verification data confirms that the inversion prediction results of the proposed method are basically consistent with actual conditions, and it can provide reliable geological forecasting for tunnel excavation and support.
To ensure the construction safety of the short-line precast wide-width concrete beam section on a high platform before splicing, the concrete beam and beam shifting support on the Jiangling side of the Guanyinsi Yangtze River Bridge were taken as the research object. Midas FEA/Civil was adopted to establish the solid model of the beam section and the beam element model of the support, respectively. The transverse stress and deformation in each construction stage before splicing, and the influence of support deformation on the stress of the beam section during beam shifting were calculated and analyzed. Considering the actual construction process and the influence of concrete shrinkage and creep, a reasonable transverse prestressed fractional tensioning scheme for the precast beam section was determined. The calculation results indicate that the transverse prestress of the precast beam section, which is mainly subjected to transverse stress before splicing, must be tensioned fractionally; the timing and degree of fractional tensioning should be adapted to the timing of system conversion and the specific conditions of supports; the deformation of the beam shifting support has a minor effect on the uneven settlement of the four supporting points of the beam section, but its adverse effect on the stress of the beam section still needs to be considered.
To address the problem of decreasing disease detection accuracy due to shadow interference in complex road scenes, this study proposed a road shadow removal algorithm based on a weakly supervised generative adversarial network. By constructing a dynamic adaptive normalization strategy and an improved residual module, the algorithm optimized image feature representation under the condition of limited shadow pairing samples. The specific design was as follows: First, an auxiliary classifier with an attention mechanism was introduced to enhance the semantic perception ability of the network for road scenes. Second, the residual structure was improved by adopting cross-layer skip connections to effectively alleviate the problem of gradient vanishing in deep layers of the network. Finally, a hybrid loss function that combined the perceptual loss and the adversarial loss was designed to enhance the structure preservation ability of shadow removal. The experimental results show that the image quality evaluation metrics ERMSE, RPSNR, and SSSIM of the shadow removal algorithm are 1.083 4, 27.568 2, and 0.794 9. The images after shadow removal using the proposed algorithm were fed into the detection model. The recognition accuracy of six typical road diseases such as cracks and potholes are improved by 3.3%‒10.2%, which verifies the effectiveness of the method.
