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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>A study of stone arch bridge’s flood reliability through a surrogate model approach</title>
      <link>https://trid.trb.org/View/2663631</link>
      <description><![CDATA[Europe’s historic masonry arch bridges are culturally and economically significant, but their long-term safety must be ensured. Scour effects are the most common cause of collapse, so it is necessary to carry out structural assessments to mitigate the risk and prevent potential failures. In this study, a metamodel-based method was used to determine the probability of failure of an existing stone arch bridge in Portugal due to local and contraction scour on the abutments. Non-linear finite element analysis supported the calculation of the reliability index, which took into account the soil-structure interaction and the failure mechanism. The variables with the greatest influence on the load-carrying capacity of the structure were identified and a surrogate model was implemented. Fragility curves were then derived based on the surrogate model, using scour depth as a measure of intensity and load factor as an engineering requirement parameter. The results of the study indicate that the load capacity of the numerical model is compromised when the scour depth of 1.5 m reaches the base of the foundation. As a result, stability problems and settlements are observed in the model. At a depth of 2.5 m, the soil reaches its ultimate bearing capacity.]]></description>
      <pubDate>Fri, 27 Feb 2026 11:00:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663631</guid>
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    <item>
      <title>Out-of-Plane Buckling Mechanism and Enhancing Method of Stiff Skeleton Arch Bridge When Wrapping Surrounding Concrete</title>
      <link>https://trid.trb.org/View/2643347</link>
      <description><![CDATA[This study investigates the stability of skeleton-reinforced concrete arch bridges during the concrete encasement process, employing a homogeneous generalized yield functions for extreme buckling load determination in nonlinear finite element analysis. Through an analysis of the stability of a stiff skeleton arch bridge with a 600 m span during the concrete wrapping stage, this study delves into and elucidates the mechanism by which the transverse brace enhances the out-of-plane stability capacity of the skeleton arch ribs. Additionally, a method for improving stability by controlling the lateral rotation angle of arch ribs is proposed. The results indicate that the lateral deflection angle of arch ribs serves as a crucial metric for assessing the out-of-plane stability of arch bridges. Transverse braces effectively coordinate and constrain the lateral deflections of two isolated arch ribs through their bending stiffness along the tangential direction of the arch axis. Notably, transverse braces within the range of L/8 to 3L/8 make the most substantial contribution to the lateral stiffness of arch ribs. Consequently, wrapping surrounding concrete on transverse braces within the L/8 to 3L/8 range proves advantageous for enhancing the stability of a stiff skeleton arch bridge under construction. Specifically, it is recommended to pour surrounding concrete on transverse braces at L/4 before the closure of the bottom plate’s concrete ring. After the ring of bottom plate’s concrete is closed, a symmetrical pouring of surrounding concrete on transverse braces from L/4 to the arch spring and vault is proposed.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643347</guid>
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    <item>
      <title>A novel physics-informed deep learning method for predicting arch bridge temperature-induced responses</title>
      <link>https://trid.trb.org/View/2632531</link>
      <description><![CDATA[Long-span bridges are large-scale and high-order statically indeterminate structures, whose mechanical behaviors are sensitive to temperature. The uneven temperature distribution on such structures generates a large amount of secondary stress, which brings great challenges for the accurate identification of temperature-induced responses, thereby resulting in an erroneous assessment of the service state of bridges. To this end, this paper proposes a novel physics-informed deep learning framework for structural temperature-induced response predictions. Firstly, the Squeeze-and-Excitation Network (SENet) is integrated into the Temporal Convolutional Network (TCN) to develop the Squeeze-and-Excitation Temporal Convolutional Network (SETCN). This integration enables adaptive feature calibration across channels, effectively addressing the inherent channel-wise weighting imbalance in traditional TCN that hinders the accurate capture of complex thermal-load relationships. Secondly, residuals between the physical model and the real data are infused into SETCN, resulting in the physics-informed SETCN (Phy-SETCN). This integration effectively mitigates the limitation of generalization ability of the pure data-driven model, while also alleviating disturbances caused by the time-lag effect and non-uniform temperature distribution. A case study based on the measurements from a 1:10 scale arch structure reveals that Phy-SETCN has a superior performance. Phy-SETCN achieves the highest accuracy with a 10.04 % reduction in MAE and 10.44 % in RMSE compared to SETCN, demonstrating its strong potential for accurate service-state assessment of bridges under thermal effects.]]></description>
      <pubDate>Tue, 27 Jan 2026 09:19:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2632531</guid>
    </item>
    <item>
      <title>Research on the stress and cracking characteristics of high-speed railway U-shaped steel box–concrete deck composite girders</title>
      <link>https://trid.trb.org/View/2632179</link>
      <description><![CDATA[To study the stress distribution and cracking characteristics of a composite girder combining a U-shaped steel box with a concrete deck in high-speed railways, the composite girder above the You Shui Grand Bridge arch was used as the research background. An experiment involving a 1:2.5 scaled full-section segment model was conducted, coupled with a nonlinear finite element analysis. Formulas for the cracking moment and crack width of the concrete deck in the negative bending moment area were derived. A parametric study on the cracking moment and crack width of the composite girder was performed. The results show that the stress unevenness coefficients of the concrete deck range from 0.47 to 1.54 for the positive moment and 0.78–1.15 for the negative moment, highlighting the stress shear lag and transverse unevenness. The strain distribution across the girder height deviated from the plane-section hypothesis, indicating the complex force transmission between the concrete and steel. The insignificant measured slips with a maximum value of 0.507 mm and variations with loads indicate good force transmission between the steel and concrete. The uniformly fine measured and numerical cracks of concrete deck indicate characteristics of a suitably reinforced girder cracking. The derived formulas for the crack width control bending moment of the composite girder, crack width and crack spacing in the negative bending moment area, considering the force transmission of the upper flange plate and studs, show good agreement with the experimental results. The crack width in the concrete deck decreased significantly with increasing reinforcement ratios and diameters. The influence of the upper flange plate area and the spacing between the studs were evident. The proposed formulas provide a reference for the design of similar high-speed railway composite girders.]]></description>
      <pubDate>Thu, 22 Jan 2026 09:24:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2632179</guid>
    </item>
    <item>
      <title>Damage detection of a steel arch bridge model utilizing natural frequencies and rotation angles</title>
      <link>https://trid.trb.org/View/2640591</link>
      <description><![CDATA[Utilizing bridge vibrations for health monitoring is an effective approach to managing ageing infrastructure. However, accurately identifying multiple damage locations and assessing their severity have traditionally depended on the number of sensors deployed. In this study, the finite element method was applied to a Langer arch bridge model, and the effect of damage on the frequency of the natural vibration mode and rotation angle was investigated. The objective was to enhance damage detection accuracy in multiple damage scenarios. The findings revealed that damaged components affect distinct natural vibration modes. Specifically, damage in stiffening girders significantly alters the second- and third-order bending modes, damage in hanger members predominantly affects the first-order bending mode, and damage in cross girders causes considerable changes in the first- and second-order transverse modes. The frequency shifts in multiple damage scenarios can be understood as the superposition of effects from individual damages. These findings suggest that, in a Langer arch bridge, it is possible to classify damage by utilizing the natural frequencies of multiple vibration modes, as dominant modes vary significantly depending on the damaged component. Furthermore, incorporating rotational angles as an additional parameter enhances the accuracy of damage location estimation.]]></description>
      <pubDate>Thu, 22 Jan 2026 09:10:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640591</guid>
    </item>
    <item>
      <title>Process-Based Carbon Emission Assessment of the Cable-Stayed Anchored Cantilever Construction Method: A Case Study of a 600-Meter-Scale Arch Bridge</title>
      <link>https://trid.trb.org/View/2650623</link>
      <description><![CDATA[There is a growing need to quantify carbon emissions from bridge construction, while the field lacks systematic modeling approaches tailored to specific construction methods, especially in arch bridge engineering. This study addresses this gap by focusing on a concrete-filled steel tube (CFST) arch bridge with a main span 600 meters, constructed using the cable-stayed anchored cantilever method. A comprehensive research framework is established, integrating sub-project decomposition, carbon emission factor methodology, machine learning prediction, SHAP (SHapley Additive exPlanations)-based mechanism interpretation. A dynamic carbon emission quantification model is developed, while a predictive model is constructed using machine learning algorithms. The results reveal that the construction of arch foundations and arch ribs are the two most carbon-intensive stages, with concrete pouring and steel hoisting operations playing a dominant role in emission generation. A multi-dimensional emission reduction strategy is further proposed, including structural design optimization, low-carbon material substitution, and construction process improvements. The study confirms the low-carbon advantage of the cable-stayed anchored cantilever method, which minimizes temporary material usage, with the Cable Hoisting and Cantilever systems contributing only 8% to the total construction emissions. This study offers theoretical support and critical evidence for low-carbon decision-making that aligns with safety requirements of the cable-stayed anchored cantilever method in long-span arch bridges.]]></description>
      <pubDate>Tue, 20 Jan 2026 10:13:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2650623</guid>
    </item>
    <item>
      <title>Development of a Simplified Methodology to Assess the Internal Redundancy of Bolted-Built-Up Tied Arch Members</title>
      <link>https://trid.trb.org/View/2643096</link>
      <description><![CDATA[Tied arch bridges represent a vital component of the nation's infrastructure, valued for their structural efficiency and aesthetic qualities. These bridges rely on arch ribs to transfer vertical loads into horizontal thrusts, which are counteracted by the tie beams (TBs) acting in axial tension. In addition to this axial tension, TBs are also subjected to strong axis bending mainly due to live loads from vehicular traffic. The TB, therefore, is a critical structural component, maintaining the internal equilibrium of the system by resisting the spreading forces generated by the arch and bending caused by the moving vehicular loads. These TBs are often constructed as built-up steel members, a design that inherently possesses a degree of internal redundancy, allowing them to redistribute loads among their components following a localized fracture. Under current American Association of State Highway and Transportation Officials (AASHTO) standards, these members are often classified as non-redundant steel tension members (NSTMs), resulting in additional inspection rigor. The existing AASHTO Guide Specifications for Internal Redundancy of Mechanically Fastened Built-up Steel Members (IRM Guide Spec.) provides limited information for assessing members under the combined axial tension and bending loads characteristic of TBs. This knowledge gap has led to a conservative approach, subjecting these bridges to more resource-intensive inspections, even when their actual risk profile may be comparable to typical bridges. This project was initiated to develop simplified methodologies that accurately assess the internal redundancy of bolted-built-up tie beams. The goal is to provide a reliable framework for engineers to evaluate these members, ensuring safety while reducing the need for regular hands-on inspection, ultimately contributing to more efficient bridge management practices.]]></description>
      <pubDate>Mon, 12 Jan 2026 09:13:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643096</guid>
    </item>
    <item>
      <title>Infrared vision-based in-tube concrete pumping level monitoring for CFST arch bridge construction: Experimental and field evaluation on impacting factors</title>
      <link>https://trid.trb.org/View/2610883</link>
      <description><![CDATA[Concrete-filled steel tubular structures are widely used in large-span arch bridges due to their superior mechanical properties. However, blockage issues during the construction can significantly reduce the arch bridge's load-bearing capacity and stiffness, making monitoring of the steel tube concrete pumping process crucial. Recent developments in infrared vision technology show great potential for real-time monitoring of the concrete pumping level. However, the factors impacting monitoring accuracy in complex on-site conditions are underexplored. This paper investigates the impact of environmental temperature differences (ΔT), shooting angles (θ), and the temperature difference above and below the pumping level (δT) on monitoring accuracy. The influence of various factors was evaluated through indoor simulation experiments, and suitable monitoring parameters were determined. Finally, the on-site application was conducted to verify the experimental results obtained indoors. Limitations and future work in terms of practical applications are also discussed.]]></description>
      <pubDate>Tue, 02 Dec 2025 09:56:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2610883</guid>
    </item>
    <item>
      <title>Monitoring During the Unbraced Network Tied-Arch Bridge Construction Using ABC Techniques</title>
      <link>https://trid.trb.org/View/2630563</link>
      <description><![CDATA[A unique network tied-arch bridge with free-standing arches was designed to carry the 2nd Avenue traffic over the Interstate (I) 94 in Detroit, Michigan. This 245-ft-long, 96.5-ft-wide, and 18° skew bridge is the first skewed unbraced network arch bridge in the United States. The skeleton of the superstructure was erected off-site at a bridge staging area and moved and placed over the I-94 freeway using self-propelled modular transporters to complete construction. Based on the observations from the analysis models and the communications with the Michigan Department of Transportation, the Engineer of Records, and the peer review engineer, an instrumentation system was designed and installed in the bridge to: (i) monitor and record strains in major components during construction to determine the state of stress after construction; (ii) monitor and record the change in strains during service life to support bridge maintenance and load rating decisions; and (iii) collect adequate data to verify design assumptions. This paper discusses instrumentation system planning, design, and implementation, including sensor locations, data acquisition systems, cable and power management, data collection, and observations. The instrumentation system functions as expected. The monitoring data confirm that the structural component strains are within the design limits and the structure functions as expected.]]></description>
      <pubDate>Wed, 26 Nov 2025 10:13:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630563</guid>
    </item>
    <item>
      <title>Experimental study on the effect of initial crack damage on the capacity degradation of RC eccentric columns</title>
      <link>https://trid.trb.org/View/2625449</link>
      <description><![CDATA[This study investigates the degradation of bearing capacity in cantilever-casting arch bridges due to construction-induced cracking. An equivalent conversion method is proposed to model the arch ring segment as an eccentric compression column. Reinforced concrete (RC) columns with constant cross-sections are designed to simulate eccentric column specimens, with crack width serving as the damage quantification index. Various initial crack widths (0 mm, 0.05 mm, 0.10 mm, and 0.15 mm) are introduced through different loading methods, and load-bearing capacity tests are performed for various damage states. The results show that initial cracks on the tensile side significantly reduce the load-bearing capacity of the eccentric columns, with the largest reductions being 18.91% and 8.33% for large and small eccentric columns, respectively. A negative correlation is observed between crack width and bearing capacity, while cracks on the compressive side have a minimal effect on the load-bearing capacity. Cracks in large eccentric columns result in reduced elastic stiffness, early yielding of reinforcement, and a deterioration in ductility, while small eccentric columns fail in a brittle manner due to concrete crushing. The strain distribution in the damaged section still approximately follows the plane-section assumption, with crack propagation controlled by the initial crack face. Finally, a damage reduction factor model is developed, linking crack width to bearing capacity degradation, and the calculated results align well with experimental findings. This research provides experimental evidence and theoretical tools for assessing the load-bearing capacity of cracked arch bridges.]]></description>
      <pubDate>Tue, 25 Nov 2025 16:57:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625449</guid>
    </item>
    <item>
      <title>Optimization of the ring-segment division scheme for the arch ribs outsourcing concrete in rigid skeleton reinforced arch bridges</title>
      <link>https://trid.trb.org/View/2626350</link>
      <description><![CDATA[This study presents the first comprehensive multi-objective optimization framework for rigid-skeleton reinforced (RSR) arch bridge construction, addressing critical gaps in existing empirical and single-objective approaches. We develop an integrated methodology that combines NSGA-II optimization with a novel Structural Stability Index (SSI) for quantitative Pareto solution selection, validated through systematic testing across seven construction configurations. Using the Tian'e Longtan Bridge as a case study, both 1:10-scale model experiment and finite element analysis were conducted to validate the proposed approach. The optimization method employs working platform lengths as design variables, constrained by segment dimensions. Sensitivity analysis identified optimal NSGA-II parameters: a crossover probability of 0.92 and a mutation probability of 0.02, which achieved superior convergence and solution diversity. Across seven construction configurations (2-4 rings, 6-10 working platforms, 5-7 segments), the method consistently improved structural performance, achieving maximum reductions of 8.56% in compressive stress, 57.41% in tensile stress, and 22.56% in crown deformation. The Structural Stability Index was developed for Pareto solution selection identified the three-ring, eight-working-platform, five-segment scheme as optimal (index value: 5.9196). Validation through moving-load experiments and influence-line superposition confirmed result accuracy, with a maximum relative error of 4.08%. These findings provide valuable references for optimizing construction schemes for similar arch bridges projects.]]></description>
      <pubDate>Fri, 21 Nov 2025 08:46:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2626350</guid>
    </item>
    <item>
      <title>Intelligent Forming of Large-Span Arch Bridges: Methodology and Engineering Applications</title>
      <link>https://trid.trb.org/View/2622313</link>
      <description><![CDATA[Arch bridges are well-suited to mountainous regions because their force characteristics align with local site conditions. However, construction in such areas faces challenges including large temperature differentials, complex canyon wind fields, and rugged terrain. Arch-forming also entails extensive work at height, high construction risk, and difficulties in achieving precise alignment after forming. To overcome these issues, this study presents an intelligent arch-forming method for large-span arch bridges. First, an optimization model for the entire arch-forming process is established to compute cable forces that meet objectives during construction. Second, a digital preassembly-based manufacturing control scheme is developed, allowing high-precision virtual assembly of arch rib segments in a digital environment. Finally, an automatic installation attitude adjustment strategy is proposed, based on restoring the structure to its designed shape, enabling high-precision, automated adjustment of the three-dimensional installation attitude of arch rib segments. The proposed method has been successfully applied to the Deyu Expressway Wujiang Bridge (with a main span of 504 m) located in Guizhou Province, China, demonstrating its reliability and practicality. This approach offers guidance for low-labor, resource-efficient, rapid, and automated construction of large-span arch bridges.]]></description>
      <pubDate>Fri, 21 Nov 2025 08:44:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2622313</guid>
    </item>
    <item>
      <title>Seismic risk assessment methodology for large-span CFST arch bridges in near-fault areas based on fragility analysis</title>
      <link>https://trid.trb.org/View/2602583</link>
      <description><![CDATA[Large-span concrete-filled steel tube (CFST) arch bridges are widely built in high-seismicity mountainous areas in China due to their low maintenance costs and high adaptability to the challenging construction environments. The dynamic response of such bridges under seismic loading is highly complex, and their seismic performance is a major concern for multiple stakeholders. This study proposes a seismic risk assessment method for large-span CFST arch bridges from a risk perspective, based on seismic fragility analysis. The method begins with seismic hazard analysis of the bridge site, followed by seismic risk scenario identification of the bridge through fragility analysis, then quantifies the seismic risk scenarios from the perspective of economic losses, and finally evaluates the quantified results of discrete risk scenarios based on tolerance theory. A CFST arch bridge located in a near-fault area is analyzed as a case study, with two design schemes and five annual earthquake frequencies considered to validate the feasibility of the proposed method. The research results show that the seismic risk assessment method effectively identifies risk scenarios and their characteristics across different design schemes and seismic frequencies. Additionally, as the method presents results through macro risk tolerance zone divisions, it offers more intuitive and stakeholder-friendly outputs compared to traditional engineering-technology-based assessments (e.g., seismic fragility curves). Overall, the proposed method serves as a robust decision-making tool for the design, operation, and maintenance of large-span CFST arch bridges and similar structures with complex seismic responses.]]></description>
      <pubDate>Mon, 13 Oct 2025 16:31:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2602583</guid>
    </item>
    <item>
      <title>Seismic fragility, loss, and resiliency of old railway masonry arch bridges under near-field ground motion</title>
      <link>https://trid.trb.org/View/2582040</link>
      <description><![CDATA[Iran’s historic railway arch bridges, many over a century old, face seismic risks due to their original design neglecting lateral loads. As they are often situated in seismically active zones near fault lines, understanding their seismic vulnerability is crucial. The goal of this study is to assess the seismic fragility and loss estimation of such bridges under various seismic events. To this end, the seismic performance of two masonry arch bridges, specifically a bridge with two long spans, named 2LS20, and a bridge featuring five small spans, named 5SS06, along the old Tehran-Qom railway line, is assessed under a set of 28 near-field and 22 far-fault earthquake records. Throughout the nonlinear incremental dynamic analysis, seismic fragility analyses were performed to ascertain the likelihood of damage across distinct limit states for each bridge model under the action of near and far-fault ground motions. Subsequently, throughout the resiliency analysis, the recovery process was simulated to assess the progress of bridge functionality with time. Moreover, seismic loss analyses were conducted to assess the comparative economic viability of the studied models. The results indicate the 5SS06 bridge for lower vulnerability and repair costs with near-fault motions posing higher risks, particularly for extreme damage conditions. Resilience varies significantly based on recovery models, with the 5SS06 bridge showing more effortless recovery under far-fault motions and higher resilience factors under near-fault records. Additionally, predictive equations were proposed for managing seismic risks in similar bridge infrastructures, particularly in Iran’s railway network, aiding resilience and risk mitigation planning.]]></description>
      <pubDate>Fri, 26 Sep 2025 13:39:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2582040</guid>
    </item>
    <item>
      <title>Automated finite element modeling method for steel bridges integrating 3D point clouds and intelligent drawing recognition technology</title>
      <link>https://trid.trb.org/View/2589361</link>
      <description><![CDATA[Laser scanning is widely recognized for capturing bridge geometry, yet automation of information extraction and finite element model (FEM) generation remains limited by manual intervention. Therefore, an automated FEM framework for bridges is proposed by integrating point cloud with intelligent recognition techniques. This paper presents three key contributions: (1) A high-precision external dimension extraction algorithm is developed based on bridge-specific features and secondary segmentation, combining projection density, adaptive thresholding, and region-growing RANSAC; (2) An internal drawing extraction framework is established using deep learning-based search, optical character recognition (OCR), and large language models for automated retrieval of structural information; (3) A FEM generation process is implemented by aligning internal and external data through component naming conventions, using a three-step algorithm involving segmentation, element creation, boundary and load assignment. Validations on arch bridge model and pedestrian bridge are conducted. This paper provides an initial exploration toward automated digital modeling in bridge engineering.]]></description>
      <pubDate>Thu, 25 Sep 2025 14:53:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2589361</guid>
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