Hasil untuk "Bridge engineering"

Xiaodong Zhang, Jun Yang, Ming Sun et al.

This study presents a novel sludge ash and limestone cementitious (SSLC) composite tailored for construction, addressing the critical needs for durability, sustainability, and resilience in harsh environments. The experimental work systematically evaluates the flowability, mechanical properties, and chloride ion resistance of the SSLC paste under varying mix proportions. Through advanced techniques such as SEM, XRD, and thermodynamic simulations, the hydration mechanisms and microstructural evolution are comprehensively explained. The findings reveal that the synergistic incorporation of sludge ash and limestone optimizes pore structures, enhances the formation of carbonate-based hydration products, and significantly improves long-term properties, including a 34 % reduction in chloride ion concentration and a 5.98 % increase in flexural strength after 365 days. Additionally, the SSLC paste demonstrates a 23.43 % reduction in carbon emissions and a 22.22 % decrease in production costs, offering a low-carbon, cost-effective solution for infrastructure. These results underscore the SSLC paste’s potential as a sustainable construction material for applications, providing enhanced durability, reduced environmental impact, and economic viability to meet the challenges of modern engineering.

ZHANG Xiyin, YU Shengsheng, WANG Wanping et al.

In cold and high-seismic regions, such as the Qinghai‒Xizang Plateau in China, the deterioration of material properties caused by freeze-thaw cycles and permafrost degradation due to climate change have become increasingly severe, posing significant challenges for the seismic performance assessment of bridge pile foundations. To systematically investigate the impact of permafrost degradation and material freeze-thaw deterioration on the seismic performance of bridge pile foundations and ensure proper seismic design, a finite element model was established, considering the dual effects of permafrost degradation and material freeze-thaw deterioration. A comparative analysis was conducted to evaluate the influence mechanisms of various factors on the seismic performance of bridge pile foundations in permafrost regions. The results indicate that as the bridge service life increases, the horizontal bearing capacity, equivalent stiffness, and energy dissipation capacity of the pile‑permafrost system all show a decreasing trend. Notably, the combined effect of permafrost degradation and material freeze-thaw deterioration has a more significant impact on the seismic performance of the bridge pile foundations. Specifically, after 100 years of bridge service, the horizontal bearing capacity of the pile‑permafrost system reduces to approximately 55% of its initial value, whereas when only permafrost degradation is considered, the horizontal bearing capacity drops to around 89% of its initial value. Therefore, neglecting the effect of material freeze-thaw deterioration will lead to an unsafe seismic performance assessment of the bridge pile foundation. In the seismic performance analysis of bridge pile foundations in permafrost regions, it is essential to consider not only the effect of permafrost degradation but also the impact of material freeze-thaw deterioration.

Zhuo Song, Xiaojun Li, Yushi Wang et al.

The multi-strip method is often used to establish a demand model for fragility analysis. Using the multi-strip method to scale the ground motion record may cause uncertainty and bias in structural response calculation and fragility assessment. It is necessary to analyze the effect of differences in the amplitude scaling range in different strips on structural seismic response calculation and seismic fragility assessment. In this paper, the multi-strip method was used to analyze the seismic demand bias based on four multi-story reinforced concrete frame structures subjected to eight ground motion record sets. The bias, variance, and coefficient of variation in different strips in each group of ground motion records were obtained. The effect of different strips on the demand bias was investigated by analysis of variance (ANOVA). Uncertainty quantification of structural demand and fragility curves was carried out using the bootstrap sampling method. The results for structures in different ground motion record sets verify that the differences between the demand bias for different strips by amplitude scaling are statistically insignificant for a 95% confidence level. These findings will contribute to the use of scaling methods for ground motion record sets in a probabilistic seismic demand assessment, allowing for a more reliable prediction of structural seismic fragility.

Ilakeya Subbiah Arivuthilagam, Raghisa Shahid, Md. Mahbubur Rahman et al.

Single‐atom catalysts (SACs) have rapidly progressed from early proof‐of‐concept studies to high‐performance sensing platforms. Their atomically dispersed active sites and tunable coordination environments, offer superior catalytic activity and selectivity compared with conventional nanocatalysts. Recent advances in support engineering, spanning carbon nanomaterials, metal oxides, and metal organic frameworks have enabled precise control over SAC composition, electronic structure, and stability under complex operating conditions. This review summarizes the current state of SAC research from three complementary perspectives. First, it compare top‐down and bottom‐up synthesis strategies, emphasizing scalable approaches that preserve single‐atom dispersion. Second, it outlines the characterization techniques, highlighting how advanced spectroscopy, microscopy, and theoretical calculations are integrated to correlate coordination environments with catalytic performance. Third, it discusses emerging sensing applications including biosensing, environmental monitoring, gas and electrochemiluminescence detection, and photoelectrochemical analysis where SAC‐based materials achieve record‐low detection limits. Despite significant advancements, key challenges remain: (i) preventing atom aggregation under harsh electrochemical conditions, (ii) integrating SACs into miniaturized devices, and (iii) establishing standardized metrics that bridge theoretical predictions and practical performance. This review concludes that addressing these issues will advance SACs toward real‐time sensing, with multi‐atom cooperative sites and AI‐assisted catalyst design as promising strategies to unlock their full potential in next‐generation analytical platforms.

Yijun Chen, Wenqi Wu, Qingzhao Li et al.

Traditional damage detection methods of prestressed concrete box girder bridges have low efficiency and cannot quantify the structure’s internal damage. We used an inversion method and a falling weight deflectometer to estimate the mechanical parameters of prestressed box girder bridges. A finite element model of the bridge dynamics under impact loading was established. A perturbation-based update was conducted, and a multi-parameter inversion algorithm was constructed. The measured data were used for the efficient identification of the bridge’s elasticity modulus and the prestressing tensile force. The theoretical validation indicated a high modeling accuracy and inversion efficiency, with a convergence accuracy within 1%. The initial value had a minimal influence on the inversion results. The engineering application showed that the maximum error of the elastic modulus between the inversion and the rebound methods was 1.55%. The loss rates of the deck slab’s elastic modulus and the prestressing force obtained from the inversion were 4.39% and 7.64%, respectively. The proposed method provides a new strategy for evaluating damage to prestressed box girder bridges.

ZHANG Dongying, LI Ning, LIU Xincheng et al.

To address the poor performance of plant-produced hot recycled asphalt mixtures with high recycled asphalt pavement (RAP) content, this study employed a refined separation technology to treat RAP materials. The effectiveness of this technology in enhancing the durability of high-RAP-content recycled asphalt mixtures was verified through trial pavement construction and performance testing. In addition, the carbon reduction potential as well as the economic and social benefits of the refined separation technology were analyzed. The results demonstrate that the refined-separation recycled asphalt mixture performs significantly better than conventional crushed-and-screened recycled asphalt mixtures in terms of water-temperature cycling resistance, long-term aging resistance, high-temperature and moisture damage resistance, and fatigue resistance, while exhibiting comparable durability to virgin asphalt mixtures. From an economic and social perspective, the total cost of refined-separation recycled asphalt pavement decreases by 33% and 50% compared to conventional crushed-and-screened recycled asphalt pavement and virgin asphalt pavement, respectively. Furthermore, its energy consumption and carbon emissions decrease by 25% and 32% compared to virgin asphalt pavement, and by 25% and 24% compared to conventional crushed-and-screened recycled asphalt pavement. This technology not only achieves significant energy conservation and emission reduction but also substantially enhances the durability of high-RAP-content recycled asphalt pavements.

Linda Davies, Dominik Jánošík

In geotechnical engineering, the CBR test is an essential evaluation tool that can be used in laboratory and field settings. It is essential for figuring out the resistance properties of subgrade soil, whether it is used as the foundation for retaining wall fills, highway embankments, bridge abutments, or earth dams. CBR values provide a valuable metric for assessing the strength of the soil. This paper presents a novel approach to the accurate prediction of CBR values. Using the DT algorithm, the method creates complex and incredibly accurate predictive models. These models include a wide range of intrinsic soil characteristics, including particle distribution, plasticity, linear shrinkage, and the kind and number of stabilizing additives. The dataset of this study consisted of several variables, including LL, PI, PL, MDD, OMC, OPC, SDA, and QD. The DT algorithm improves forecasting accuracy by establishing significant correlations between these soil properties and CBR values. The study incorporates two state-of-the-art meta-heuristic algorithms, the NGO and the EOS, to further improve the predictive model's accuracy. Three unique models are produced by this framework: DTEO, DTNG, and a hybrid DT model. Out of all of them, the DTEO model performs exceptionally well, exhibiting excellent prediction abilities and remarkable generalization. Its performance is rigorously assessed using a range of soil types derived from earlier stabilization tests' outcomes. The DTEO model's remarkable R2 values of 0.996 during the training phase highlight its remarkable accuracy and dependability. Additionally, it achieves an ideal RMSE of 0.732, confirming its accuracy and consistency.

Gangnian Xu, Weimin Xu, Zhanhong Wang et al.

To improve the accuracy of deflection prediction for prestressed concrete (PSC) box-girder bridges with a stay cable system (SCS) during tensioning, this study employs the Latin hypercube sampling (LHS) technique to sample random variables affecting long-term deflection of the main girder. A long-term deflection randomness analysis model is established, and the shear stiffness degradation factor is included to quantify the contribution of diagonal web cracking to the main girder deflection. Uncertainty and sensitivity analysis are conducted for the Dongming Huanghe River Highway Bridge. An objective function is applied to select the optimal combination of random variables, and a modified model is established and verified for accuracy. Results show that diagonal web-cracking accounts for 8.8% of total deflection and cannot be ignored, and the prestressed tension control stress, creep uncertainty coefficient, and concrete density significantly impact long-term deflection. The modified model predicts deflection with greater accuracy than the mean value model.

Zheng Zeng, Xuefeng Yan, Weigang Xiang et al.

The formed-in-place pipe (FIPP) is a trenchless technology used for pipeline rehabilitation. It is a folded PVC pipe that expands through thermoforming to fit tightly inside the host pipe. However, the deficiencies during the construction of FIPP liners such as insufficient inflation, pipe misalignment and initial deformation will lead to elliptical deformation of the FIPP liner, which affects the load-bearing performance of the liner and makes it susceptible to buckling failure. In this paper, the buckling behavior of loosely fitted FIPP liners under uniform external pressure was investigated by the external pressure resistance test and finite element model. The pre- and post-buckling equilibrium paths verified the finite element model. The results indicated that the value of the dimension ratio will significantly reduce the critical buckling pressure. With the increasing value of liner major axis ratio to host pipe, the reduction effect on the critical buckling pressure caused by the increase in the ovality will diminish. Different values of liner major axis ratio to host pipe and ovality changed the range of the detached portion, which affected the critical buckling pressure. The parametric studies modified the design model from ASTM F1216, which was established to predict the critical buckling pressure of a loosely fitted FIPP liner and reduced the average difference rate from 23.43% to 5.52%.

Hongyan Guo, Hongyan Guo, Yu Yan et al.

The reliability of the immersed tunnel element joint is the key to determine whether the immersed tunnel can operate safely. At present, the immersed tunnel monitoring mostly pays attention to the joint opening and closing amount and neglects the differential deformation of the joint. Based on the immersed tunnel of Hong Kong-Zhuhai-Macao Bridge, combined with the operating environment and structural characteristics of the immersed tunnel, this paper introduces a close-range photogrammetry method to monitor the differential deformation of the immersed tunnel element joint. Through theoretical analysis, software and hardware development, laboratory test and field test, the paper puts forward puts forward a comprehensive multi-parameter evaluation and screening algorithm of boundary fitting ellipse based on fitting rate, ellipticity and area difference and a micro-displacement correction algorithm for camera based on three-dimensional calibration object, and develops an automatic monitoring system equipment for differential deformation of immersed tunnel element joint. Upon tests in tunnels, the monitoring equipment is proven in automatic monitoring on differential deformation of immersed tunnel element joints. This equipment has been successfully applied to the E31~E32 element joint of Hong Kong-Zhuhai-Macao Bridge immersed tunnel, which verifies the effectiveness of the equipment from the perspective of practical engineering application.

D. Marijan, Sagar Sen

Increasing the impact of software engineering research in the software industry and the society at large has long been a concern of high priority for the software engineering community. The problem of two cultures, research conducted in a vacuum (disconnected from the real world), or misaligned time horizons are just some of the many complex challenges standing in the way of successful industry–academia collaborations. This article reports on the experience of research collaboration and knowledge co-creation between industry and academia in software engineering as a way to bridge the research–practice collaboration gap. Our experience spans 14 years of collaboration between researchers in software engineering and the European and Norwegian software and IT industry. Using the participant observation and interview methods, we have collected and afterwards analyzed an extensive record of qualitative data. Drawing upon the findings made and the experience gained, we provide a set of 14 patterns and 14 anti-patterns for industry–academia collaborations, aimed to support other researchers and practitioners in establishing and running research collaboration projects in software engineering.

Gang Li, Qiangwei Liu, Shanmeng Zhao et al.

Regular inspections of bridge substructures are very important for evaluating bridge health, since early detection and assessment offer the best chances of bridge repair. However, the traditional inspection methods of checking defects with visual features cannot meet engineering needs sufficiently. Although deep-learning methods have recently demonstrated a remarkable improvement in image classification and recognition, there are still difficulties, such as the countless parameters and large model training sets needed by these methods. In this paper, we propose a novel crack extraction algorithm for automatic segmentation of cracks and noise using multi-layer features extracted from a fully convolutional network and a naive Bayes data fusion (NB-FCN) model. The bridge images in both the training and testing datasets are taken using an in-house designed high-precision image acquisition device, called Bridge Substructure Detection 10 (BSD-10). BSD-10 is applied to collect 7200 images from ten existing bridges under different illuminants and distances. After gathering the crack datasets, the crack and noise models of the NB-FCN are trained, respectively, with multiple iterations. Next, the skeleton and continuous boundary of a crack are recognized. Then the crack length and width are calculated using electronic distance measurement to verify the error rate of the proposed method. Compared to up-to-date machine-learning-based algorithms, i.e. the crack tree algorithm, the random structured forests algorithm, the relatively competitive convolutional neural networks algorithm, and the fusion convolutional neural network algorithm, the significant superiority of the NB-FCN algorithm in terms of recognition accuracy, computation time, and error rates is illustrated based on different types of crack images of handwriting, peel off, water stains and repair traces. The NB-FCN algorithm is verified with 7200 datasets of bridge substructures collected from 20 in-service bridges under various circumstances. In general, the recognition results show that the proposed algorithm demonstrates a remarkable performance compared to other recent algorithms.

Yongjian Chen, Honglie Sun, Zhenfa Feng

In order to improve the seismic performance of long-span double deck steel truss continuous girder bridge, taking Dao Qing Chau Bridge in Fuzhou as an engineering background, the isolation scheme of friction pendulum bearing (FPB) and friction pendulum bearing combined with viscous dampers is applied to study seismic performance. A three-dimensional dynamic model of the bridge is established using SAP2000. Taking three artificial seismic waves as seismic excitation, the seismic response of the seismic structure is calculated by nonlinear time history integration, and is then compared with the seismic response of the seismic reduction and isolation structure. The results show that the friction pendulum bearing (FPB) scheme and combined seismic dissipation and isolation (CSDI) scheme show a good seismic dissipation and isolation effect and ensure the safety of the bridge structure. However, for whole-bridge isolation, friction pendulum bearing (FPB) will produce certain residual deformations and additional stress of the bearing under the conditions of temperature and external load. For the purpose of protecting the bearing, it is recommended to use the combined seismic dissipation and isolation (CSDI) scheme.

Boming Shang, Feng Jin, Xuewen Rong et al.

In this paper, dry-mixed recycled cement concrete gravel (CCG) piles and dry-mixed cement macadam gravel (CMG) piles were analyzed. CCG and CMG were prepared by using recycled concrete aggregate (RCA) with different substitution rates, recycled macadam aggregate (RMA) from waste bricks and tiles, and fly ash, respectively. Mechanical properties, hydration heat release performance, and frost resistance were used as evaluation factors. The compressive strength, hydration heat, relative dynamic elastic modulus, and mass loss rate were tested. Based on the requirements of subgrade reinforcement on the material strength, hydration heat release, and frost resistance of dry-mixed CRA piles, TOPSIS analysis method was used to conduct a comprehensive evaluation. The results show that the mechanical properties and frost resistance of CCG and CMG gradually deteriorate with the increase of RCA and RMA replacement rates. At the same time, the hydration heat release of CCG and CMG increases with the increase of the replacement rate. The fly ash instead of cement can improve the compressive strength and frost resistance of CCG and CMG and reduce the hydration heat and material cost. When the CCG replacement rate reaches 20%, the CCG composite score of 20% fly ash is higher than that of traditional dry-mixed cement gravel pile and has better comprehensive performance.

Dan Li, Yang Luo, Xiao Lei Jiao et al.

Molecular dynamics was used in this study to understand the self-healing behavior and mechanism of asphalt. Density, solubility, and mean square displacement parameters were analyzed to confirm the validity of the matrix asphalt model. Molecular simulation software was used to develop a microscopic matrix asphalt self-healing model at the nanoscale. Cracking width of asphalt microcracks was represented by setting different vacuum layer thicknesses as the asphalt self-healing model. Density and diffusion coefficient of the self-healing model were obtained by running the molecular software to understand the entire process of asphalt healing. The self-healing mechanism of the matrix asphalt was analyzed. Results showed that the entire self-healing process of asphalt could be clearly divided into four stages, namely, external environment energy endowment, model end healing, asphalt microcrack healing, and self-healing model self-diffusion stages. Molecules of each component in the asphalt self-healing process diffuse and move mutually under constant temperature conditions. The diffusion coefficient of saturated components and polar aromatic was higher than that of asphaltenes and aromatic components.

Huihui Li, Lifeng Li, Guojie Zhou et al.

Lianxu Zhou, Xiaowei Wang, A. Ye

Abstract In current transverse seismic design of long span cable-stayed bridges, the conventional transverse fixed system (TFS) is usually adopted. This strategy inevitably increases seismic demands of substructures and towers, leading to high seismic-induced damage risks to the bridges. To address this issue, the authors recently developed a novel Transverse Steel Damper (TSD) and correspondingly proposed an innovative TSD seismic system (TSDSS), in which the TSDs were placed at deck-tower and/or deck-bent connections. To further verify the reliability and seismic isolation efficiency of TSDSS for long span cable-stayed bridges under near- and far-fault ground motions, a series of experiments on a 1/35-scale model of a kilometer-span cable-stayed bridge were conducted on a four-shake-table testing system. Experimental results indicate that (1) compared with the conventional TFS, the TSDSS can reduce transverse displacement and curvature demands along bent/tower columns, meanwhile limiting displacements at deck-bent/tower connections to an acceptable level in engineering practice. (2) The sensitivity of TSDSS to ground motions is obviously lower than that of the conventional TFS. The isolation efficiency of TSDSS is robust regardless under near- or far-fault ground motions; (3) Increasing the yield strength of TSDs can decrease the relative displacements at deck-bent/tower connections. In general, the TSDSS is experimentally validated to be a capable and reliable strategy for the seismic design of long span cable-stayed bridges. Additionally, the shake-table test is simulated using a finite element model, which provides good agreements with the test results.

Emma Aspland, D. Gartner, P. Harper

ABSTRACT Hospital information systems are increasingly used as part of decision support tools for planning at strategic, tactical and operational decision levels. Clinical pathways are an effective and efficient approach in standardising the progression of treatment, to support patient care and facilitate clinical decision making. This literature review proposes a taxonomy of problems related to clinical pathways and explores the intersection between Information Systems (IS), Operational Research (OR) and industrial engineering. A structured search identified 175 papers included in the taxonomy and analysed in this review. The findings suggest that future work should consider industrial engineering integrated with OR techniques, with an aim to improving the handling of multiple scopes within one model, while encouraging interaction between the disjoint care levels and with a more direct focus on patient outcomes. Achieving this would continue to bridge the gap between OR, IS and industrial engineering, for clinical pathways to aid decision support.

R. Jiang, Qi-ming Wu, Y. Xiao et al.

Abstract The composite box girder bridge with corrugated steel webs and trusses is a recently proposed enhanced composite box girder bridge structure. The shear-lag effect of this kind of structure is studied in detail in this research. Two 8.744 m-long test beams with and without concrete filled in the bottom steel tubes were constructed and tested. The non-uniform distribution of cross-sectional stress in the top concrete slab was captured. The filling of concrete inside the bottom steel tubes is shown not to have a great influence on the shear-lag effect. Numerical parametric studies were carried out to study the influence of various factors on the shear-lag effect of this kind of structure. The numerical results indicate that the magnitude of the shear-lag effect increases with the width-to-span ratio and the suspension ratio. Analytical equations were derived to calculate the shear-lag coefficient for composite box girders with corrugated steel webs and trusses based on the energy variational principle. The experimental and numerical validation indicates that the proposed equations can be well applied in engineering practice.

D. Elmo, D. Donati, D. Stead

Abstract Intact rock bridges have been recognised as of critical importance in the stability of rock slopes but still remain a poorly understood and challenging engineering problem both in respect to their measurement and their incorporation into design analyses. The objective of this paper is not to provide conclusive answers as to the definition and measurement of rock bridges, and the manner that they can be accounted for in rock slope stability analysis. Rather, we highlight important and as yet unanswered questions to allow review of fundamental rock bridge concepts and then proceed to provide new insight into how rock bridges may be incorporated into slope stability analysis. Early definitions of what constitute a rock bridge are somewhat limited, and the authors suggest that they could be improved by including important constraints such as “block forming potential” and “block kinematics”. In this context, this paper introduces an improved terminology (RBij) commonly used by the discrete fracture network (DFN) community to define rock bridge intensity relative to the sampling region. In rock engineering, the measurement of rock bridges is exacerbated by the fact that rock bridges are not visible unless the rock mass is exposed by human activities or by natural events such as rockfalls. This constitutes a major problem for engineering design scenarios, since it would not be possible to validate any assumption made with respect to extent of rock bridges without performing some form of field testing or back-analysis. The results of a of the Finite-Discrete numerical analysis are presented to support our conclusions with respect to the limitations current methods used to characterise rock bridge strength. The role of scale effects, block theory, kinematics and what we term “negative rock bridges” in stability analysis is discussed.