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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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    <language>en-us</language>
    <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 simplified nonlinear longitudinal seismic model of high-speed railway simply supported bridge based on time-history response updating</title>
      <link>https://trid.trb.org/View/2642853</link>
      <description><![CDATA[As high-speed railway lines expand into regions prone to earthquakes, the seismic safety of High-Speed Railway Bridges (HSRBs) has become an increasing concern. While traditional seismic analysis models can accurately capture the seismic response of HSRBs, their complexity and low computational efficiency limit their use in engineering applications. To address this issue, this study develops a simplified nonlinear longitudinal seismic model based on the principle of Track Constraint Equivalent (TCE) and proposes a finite element model structural parameter updating method based on seismic response time-history. Additionally, an improved genetic algorithm combined with a filtering strategy was developed to accelerate the iterative process. Three nonlinear test cases are used to validate the feasibility and accuracy of the proposed method. Numerical analyses show that Simplified Track-Bridge Model (STBM) reduces the number of elements and nodes by more than 95 % and nearly doubles computational efficiency in seismic analysis. The STBM demonstrates high fidelity in reproducing both static peak characteristics and dynamic seismic responses of bridge structures, with errors maintained within 10 %. These findings confirm the effectiveness of STBM for seismic analysis and provide an efficient and practical alternative for the seismic design and assessment of HSRBs.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642853</guid>
    </item>
    <item>
      <title>Revised modality-driven approach for enhanced analytical solutions to complex multi-mode coupled flutter: Influence of suspension bridge configurations</title>
      <link>https://trid.trb.org/View/2642842</link>
      <description><![CDATA[Future island-linking suspension bridges with spans exceeding 2000 m face significant challenges related to flutter instability. The suspension system configuration largely determines the baseline flutter resistance and plays a pivotal role in wind-resistant design. Given the inherent complexity of suspension systems, typically characterized by strong multi-mode coupling, accurately capturing the underlying modal interactions is essential for their reliable flutter evaluation. However, conventional mechanism analysis methods, such as the modality-driven approach, often rely on simplified assumptions and thus fall short in providing high-fidelity explanations of complex coupling effects. To overcome this limitation, this study refines the theoretical foundation of the modality-driven approach by enhancing the excitation-feedback interactions between modes, yielding an accurate analytical solution for three-dimensional flutter and enabling detailed mechanism analysis of multi-mode coupling, particularly inter-modal deep coupling. The necessity and effectiveness of this refinement are validated through comparative analyses of three suspension bridges with similar span layouts and mass distributions but different suspension configurations: single-span, three-span, and cable-stayed suspension systems. Furthermore, the influence of suspension system configuration on flutter behavior is examined from the perspective of multi-mode coupling using the proposed approach. Results indicate that flutter behavior is highly sensitive to suspension system complexity. The three-span system is primarily governed by first-order symmetric torsional (positive damping) and vertical (negative damping) modes. In the single-span system, the second-order vertical mode additionally participates due to modal shape differences compared to the three-span system, introducing further negative damping and resulting in the lowest critical flutter wind speed. In contrast, the cable-stayed system demonstrates the highest flutter resistance owing to its elevated torsional frequency and the favorable contribution of the second-order vertical mode. However, this system also involves a higher-order torsional mode, resulting in significant deep coupling with the fundamental vertical mode that partially offsets the anticipated performance gains.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642842</guid>
    </item>
    <item>
      <title>System reliability-based design optimization of energy dissipation devices for long-span cable-stayed bridge under near-fault seismic excitation</title>
      <link>https://trid.trb.org/View/2642838</link>
      <description><![CDATA[To obtain optimal parameters of energy dissipation devices for long-span cable-stayed bridge exposed to near-fault stochastic ground motions as nonstationary random excitation, a novel framework for system reliability-based design optimization (SRBDO) is developed via direct probability integral method (DPIM). Based on the probability density function of global limit state function, the formulation of dynamic system reliability is established first, and solved via DPIM. New formulas for system reliability sensitivity and mean value sensitivity to distribution parameters of random variables are then deduced from probability density integral equation. Moreover, the stochastic synthesis model of response spectrum compatible near-fault ground motions is advanced, and SRBDO of energy dissipation devices is performed. Finally, four cases are investigated, including deterministic optimization, SRBDO under forward directivity, fling-step pulse-like ground motions, and non-pulse motions. Results demonstrate that the automatic and digital designs of energy dissipation devices of cable-stayed bridge are accurately and efficiently fulfilled, avoiding numerous calls for structural analyses. SRBDO can enhance the bridge system reliability and resilience more effectively than deterministic design. Pulse-like ground motions impose higher seismic demands for cable-stayed bridge, resulting in 36.49 % and 20.27 % cost increases for fling-step and forward directivity scenarios than non-pulse motions. It is essential to evaluate the velocity pulse effect on seismic performance and optimal design of cable-stayed bridge in near-fault region via nonlinear and nonstationary random vibration analysis.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642838</guid>
    </item>
    <item>
      <title>Automated standardization of bridge inspection data using generative AI</title>
      <link>https://trid.trb.org/View/2642800</link>
      <description><![CDATA[This paper presents a method leveraging generative AI and natural language processing to standardize bridge inspection data, transforming it into a ready-to-use format for direct use in condition assessment, predictive modeling, and informed decision-making. This entails capturing and evaluating severity levels of reinforced concrete bridge defects from textual inspection data, such as comments provided by inspection personnel regarding type, location, and intensity of these defects. This paper employs three models: (1) a baseline generative pre-trained transformer model, which leverages OpenAI’s large language models to process textual inspection data through an optimized prompt engineering procedure; (2) a fine-tuned generative pre-trained transformer model, which builds upon the baseline by incorporating domain-specific training before being deployed to improve its performance; and (3) a newly developed natural language processing model, which employs conventional natural language processing techniques, providing a benchmark for comparison with the generative AI models. These models are implemented and validated to standardize vast amounts of inspection data extracted from 2255 inspection reports spanning five years (2018–2022) for a set of bridges in Québec, Canada. The fine-tuned model is found to outperform other models in terms of performance, stability, and reliability in detecting and standardizing the severity of different types of concrete defects in bridge decks. It achieves accuracy rates of 98.79 % for corrosion of reinforcing bars, 99.09 % for concrete delamination, and 98.64 % for cracking, scaling, and spalling of concrete. This paper demonstrates the potential for integrating generative AI into infrastructure asset management, an application that has yet to be realized.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642800</guid>
    </item>
    <item>
      <title>Mechanism and application of obstacle-grid tuned particle impact dampers for railway track vibration and noise mitigation</title>
      <link>https://trid.trb.org/View/2642791</link>
      <description><![CDATA[This study introduces a novel obstacle grid tuned particle impact damper (OG-TPID) for vibration and noise mitigation in rail transit systems. A hybrid numerical framework, combining multibody dynamics and the discrete element method, was developed to simulate particle dynamics and energy dissipation under sweep-frequency excitation. The results demonstrate that the internal obstacle grid facilitates multidirectional energy transfer, significantly enhancing damping performance in the mid-to-high frequency range. A full-scale vibration test conducted on a nine-meter-long ballastless track validated the numerical model, with modal frequency errors within five percent. Frequency-domain admittance and attenuation rate analyses reveal that traditional tuned mass dampers (TMDs) suppress the primary resonance near 1080 Hz within a narrow frequency range (960–1380 Hz). In contrast, the OG-TPID provides superior broadband vibration control from 1300 Hz to 3000 Hz, with peak decay rates of 11.1 dB/m for OG-TPID-II (with inclined obstacle grids) and 9.8 dB/m for OG-TPID-I (with vertically aligned grids), surpassing conventional tuned particle impact dampers (TPIDs) by 8.1 dB/m. Acoustic measurements further confirm the OG-TPID enhanced noise reduction capabilities. OG-TPID-I achieved a total sound power reduction of 4.7 dB in the 1250–2250 Hz range, while OG-TPID-II resulted in a 1.1 dB reduction in the 2250–3000 Hz range, outperforming both TMDs and traditional TPIDs. These findings highlight the OG-TPID as an effective broadband solution for vibration attenuation and noise mitigation in complex rail structures.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642791</guid>
    </item>
    <item>
      <title>Vibration serviceability assessment of footbridges: Extending the application range of current design guides</title>
      <link>https://trid.trb.org/View/2642789</link>
      <description><![CDATA[Vibration serviceability assessment of footbridges under walking excitation is a critical component in their design. Current deterministic methodologies, such as those outlined in the Sétra and HiVoSS guidelines, are widely adopted but are in principle limited in terms of application range. This work proposes a generalization of the same methodology that is applicable for (1) different rates of inter-person variability with standard deviations on the step frequency ranging from 0.02 to 0.30 Hz, (2) extended range of damping ratios from 0.1 to 50%, and (3) a span range covering both short and long footbridges. These generalizations in particular allow to account for additional damping resulting from human-structure interaction or tuned mass dampers, using the effective modal parameters. Moreover, the extended range of standard deviations of step frequencies allows implementation of human-human interaction for different occupation rates. The solution is underpinned by numerical simulations, from which conservative, yet, accurate deterministic equations are derived which can be integrated seamlessly in the existing design methodology of Sétra and HiVoSS. Validation against both a theoretical example and two real-world structures shows that the proposed solution consistently outperforms the one of Sétra and HiVoSS across nearly the complete application range.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642789</guid>
    </item>
    <item>
      <title>A hierarchical enhanced text matching model for semantic alignment and importance determination of bridge defect records</title>
      <link>https://trid.trb.org/View/2640082</link>
      <description><![CDATA[With the rapid development of large language models (LLM) and other artificial intelligence (AI) technologies, digitalization in bridge information management has become essential for advancing intelligent bridge maintenance, particularly as the growing number of inspection data caused by increasing bridge degradation and damage. New technologies are needed to improve the processing capabilities and efficiency of new data and historical inspection reports in printed form. This paper introduced a hierarchy-enhanced text-matching model that employed a refined Sentence-BERT to align the defect records in inspection reports with a pre-established standardized library of defect nomenclature. In this way, the model could predict the importance of individual defect entries. The proposed model enhanced matching performance by incorporating the hierarchical information of bridge structures from defect records and standardized defect names into sentence order information. Real-world inspection data were utilized to evaluate the effectiveness and interpretability of the proposed method, including ablation experiments and comparison studies with state-of-the-art sentence-matching and generative language models. The results revealed that the proposed model demonstrated a 6 % enhancement in the F1 score relative to the baseline model, and when compared to state-of-the-art methods, it has competitive performance in low-resource consumption scenarios.]]></description>
      <pubDate>Tue, 17 Feb 2026 13:12:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640082</guid>
    </item>
    <item>
      <title>Research on wheel-rail impact monitoring and identifying method based on combined Variational Modal Decomposition-Envelop Spectrum (VMD-ES) and Transformers framework</title>
      <link>https://trid.trb.org/View/2639839</link>
      <description><![CDATA[During high-speed train operation, wheel flats are common wheel wear that cause wheel-rail impacts. Thus, studying impact transmission and wheel-flat monitoring is crucial. This study focuses on wayside wheel-rail impact monitoring and proposes identifying wheel flats via rail-seat forces. A vehicle-track coupling model is built and verified via wheel-drop tests to analyze rail-seat force variations under impacts. Variational Modal Decomposition (VMD) and Envelop Spectrum (ES) are used to extract characteristic frequencies for different wheel-flat conditions. A VMD-ES-Transformers-based classification framework for wheel-flat length is proposed and trained/validated with simulated rail-seat force data. Performance under varying rail-seat points, data structures, and cascade models is discussed. Key findings include: indoor tests and simulations confirm the feasibility of monitoring wheel-rail impacts using rail-seat force and propose a wayside monitoring method via the fastener system's iron plate strain; Signal decomposition by VMD extracts components containing wheel-rail impact information, and ES analysis quantifies the degree of wheel-rail impact; The degree of wheel-rail impact from wheel flat scars depends on the impact location (nearer to the rail seat, the greater the impact amplitude), but the sum of VMD-ES amplitudes of rail-seat force signals for each wheel-rail impact fluctuates within a certain range, offering characteristic values for recognizing different length wheel flat scars via rail-seat force (10–50 mm flat corresponds to 0.095 ± 0.024 kN, 0.212 ± 0.028 kN, 0.54 ± 0.038 kN, 1.10 ± 0.058 kN, and 1.86 ± 0.077 kN, respectively); The VMD-ES-Transformers model outperforms the Transformers model in error indicators (RMSE, MSE, MAE close to 0), has a better data fitting degree (R² closes to 1), and higher classification performance metrics (precision, recall, F1-score close to 1), especially in identifying small flat scar grades, demonstrating high robustness and efficiency in classification performance to meet real-time online monitoring requirements for wheel flat scars. This method offers a complementary way for real-time wheel flat length monitoring, with engineering significance.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:54:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2639839</guid>
    </item>
    <item>
      <title>Investigation of the effects of crosswinds on the aerodynamics of high-sided road vehicles on open terrain highways</title>
      <link>https://trid.trb.org/View/2639785</link>
      <description><![CDATA[This study investigates the aerodynamic effects of crosswinds on high-sided road vehicles, using the commonly driven Freightliner Cascadia semi-truck and Jeep Grand Cherokee SUV, under realistic open-terrain highway conditions. Conducted in the Aerodynamic and Atmospheric Boundary Layer (AABL) Wind and Gust Tunnel at Iowa State University, the research employs high-fidelity 1:16 scale models to measure aerodynamic forces and pressure distributions at various yaw angles ranging from 0° to 90°. Results reveal that crosswinds significantly impact vehicle stability, with drag, lift, and side force coefficients varying significantly with yaw angle. The semi-truck exhibits peak drag at 60° yaw, while the SUV shows increasing lift and side forces up to 90° yaw on highways compared to flat surfaces. Pressure distributions highlight localized high-load regions, particularly on windward surfaces, contributing to roll and yaw moments. The study validates findings against literature, demonstrating strong agreement. Key implications include the vulnerability of high-sided vehicles to crosswind-induced instability, emphasizing the need for aerodynamic design optimizations and safety measures in highway infrastructure. This work provides critical insights for enhancing vehicle safety and efficiency in adverse wind conditions, bridging gaps between academic research and practical applications in freight transportation.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:54:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2639785</guid>
    </item>
    <item>
      <title>Bond investigation of iron-based shape memory alloy bars embedded in UHPFRC – Comparison between testing methods</title>
      <link>https://trid.trb.org/View/2635419</link>
      <description><![CDATA[Roughly 50 % of the existing bridges in Switzerland are now over 50 years old. Following a common trend, in most industrialised countries, many bridges are approaching or have reached their design lifespan. Thus, awareness towards retrofitting demands of existing bridges is increasing. In this context, a new prestressed strengthening technique is pro-posed, where a layer of Ultra-High Performance Fibre Reinforced Concrete (UHPFRC) reinforced with Iron-based Shape Memory Alloy (Fe-SMA) bars is cast on top of an existing bridge deck. Besides increasing the deck bending resistance under hogging moments, the innovative method can reduce transverse bending moments in the bridge webs and significantly improve the structure's serviceability thanks to the Fe-SMA prestressing capabilities. As part of the study of the proposed system, and to address the existing gap in knowledge on the bond behaviour between UHPFRC and Fe-SMA, two series of tests were conducted: (i) short pull-out tests (adapted RILEM tests) instrumented with Digital Image Correlation (DIC), and (ii) pull-out tests with longer embedment lengths instrumented with Fibre-Optical (FO) sensors and DIC. For comparison, two types of steel reinforcing bars (B500B and Fe-SMA) were tested. The main results from both pull-out test campaigns are discussed, highlighting the advantages and drawbacks of each of these approaches. The FO sensors used in the long pull-out tests provided new insights into the bond behaviour between UHPFRC and reinforcement steel. Post-processing of the long pull-out tests results revealed average peak bond shear stresses of 28 MPa and 23 MPa for B500B and Fe-SMA steel reinforcing bars, respectively. Conversely, the short pull-out tests yielded unrealistically high bond shear strength values, in some cases overestimating the maximum bond capacity by more than a factor of two. While the bond strengths observed in the long pull-out test align well with the fib Model Code predictions, they remained significantly lower than recommended in existing standards, such as the Swiss technical specification SIA 2052.]]></description>
      <pubDate>Wed, 04 Feb 2026 16:28:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635419</guid>
    </item>
    <item>
      <title>Thermo-mechanical behavior of height-adjustable short-sleeper ballastless tracks under severe thermal conditions</title>
      <link>https://trid.trb.org/View/2635537</link>
      <description><![CDATA[High-speed railway ballastless track structures are prone to deformation and damage due to temperature fluctuations. This study investigates the thermo-mechanical behavior of a Height-adjustable Ballastless Track with Short Sleepers (HBTS) using a three-dimensional transient thermo-mechanical finite element model. The model incorporates solid conduction, solar radiation, convective and radiative heat exchange, a bilinear cohesive-zone interface model, and a concrete plastic-damage law. Parameters are calibrated with 24-hour temperature field monitoring data from a reference track slab. Two configurations are compared: Mode A (slabs with free expansion joints) and Mode B (slabs with restraint connectors). Pre- and post-elevation states, achieved by increasing isolation pad thickness from 5 mm to 8.15 mm, are analyzed under severe temperatures of −25 ℃ and + 40 ℃. Results show Mode B enhances stiffness and continuity at high temperatures, reducing peak tensile stress from 3.2 MPa (exceeding concrete’s tensile strength) in Mode A to below the threshold, limiting HBTS-roadbed interlayer stiffness degradation to 0.404 (versus 0.565 in Mode A), and decreasing mid-span uplift and lateral rail displacement. Mode A offers greater flexibility, suitable for cold climates and differential settlements. These findings provide the design and maintenance guidance for height-adjustable ballastless tracks operating under thermal environments.]]></description>
      <pubDate>Wed, 04 Feb 2026 16:28:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635537</guid>
    </item>
    <item>
      <title>Performance of a novel piezoelectric energy harvester in railway wind barriers under coupling of train-induced wind and crosswinds</title>
      <link>https://trid.trb.org/View/2635532</link>
      <description><![CDATA[Harvesting energy directly from railway wind barriers to power bridge monitoring systems is an ideal approach. In this study, a novel galloping piezoelectric energy harvester with a square-cut isosceles triangular prism (GPEH-SCT) is proposed for use on a railway bridge wind barrier. Its performance is examined under the combined effects of train-induced wind and crosswinds. A theoretical model for the GPEH-SCT is established. Additionally, wind tunnel tests and comprehensive computational fluid dynamics (CFD) analyses are conducted on the harvester to thoroughly evaluate its performance. The influence of varying structural parameters of the GPEH-SCT and its arrangement position on the output characteristics of the harvester has been theoretically analyzed. The results reveal that the GPEH-SCT-90 demonstrates remarkable energy-harvesting efficiency, with an output power of 1.83 mW at a wind speed of 7 m/s, which is 50.3 % higher than that of square prism GPEHs. Further analysis indicates that the windward-side wind barrier is more suitable for energy harvesting. Increases in train speed and variations in the position of the GPEH-SCT relative to the wind barrier inlet have minimal impact on its electrical output performance. Conversely, higher crosswind speeds and lower installation heights of the harvester enhance its energy-harvesting efficiency. This work provides valuable insights for the installation and performance evaluation of the GPEH-SCT in the practical application of the railway bridge wind barriers.]]></description>
      <pubDate>Wed, 04 Feb 2026 16:28:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635532</guid>
    </item>
    <item>
      <title>Integrated camera array and AIS approach for ship trajectory monitoring and bridge collision prevention</title>
      <link>https://trid.trb.org/View/2635452</link>
      <description><![CDATA[Single-camera surveillance in wide waterways has significant blind spots, posing high risks for ship-bridge collisions. Traditional monitoring relies on multiple uncoordinated camera feeds, requiring supervisors to interpret split-screen images, complicating real-time awareness. Additionally, the Automatic Identification System (AIS) has low data acquisition frequency, leading to trajectory gaps that hinder accurate ship movement prediction and increase safety risks. This paper proposes a multi-source data fusion scheme for real-time ship localization and trajectory tracking. A camera array serves as the core sensing device, playing a dominant role in short-range high-precision monitoring and real-time trajectory recognition. During system deployment, an unmanned aerial vehicle (UAV)-based laser scanning system is introduced for one-time spatial modeling and coordinate calibration, providing technical support for the construction of a unified spatial reference framework. Meanwhile, the Automatic Identification System is utilized for long-range global positioning beyond the visual coverage and serves as a key auxiliary data source to supplement trajectory information when video-based sensing is weak or unavailable. By integrating multiple data sources, the system achieves precise ship localization in waterway areas, effectively reduces monitoring blind spots, enhances ship recognition capabilities, and ensures high-accuracy spatial positioning. For high-risk ship-bridge collision areas, a trajectory recognition method combining video surveillance and AIS data is developed. By analyzing trajectory variations at the camera array’s edges and compensating for missing AIS data, a multi-source trajectory fusion approach is established. Furthermore, video-based monitoring is integrated to address AIS trajectory gaps and offline states, enabling comprehensive yaw tracking and early warnings for ships in near- and far-waterway regions.]]></description>
      <pubDate>Wed, 04 Feb 2026 16:28:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635452</guid>
    </item>
    <item>
      <title>Fatigue behavior and cracking performance of novel toothed-shape SFRC joints in precast deck systems for accelerated bridge construction</title>
      <link>https://trid.trb.org/View/2635418</link>
      <description><![CDATA[The wet joints between adjacent decks have been identified as the weakest points of the full-depth precast deck systems in prefabricated bridges, with traditional flat joints made of normal concrete typically exhibiting suboptimal fatigue behavior and crack control. To address these challenges, this study introduces a novel toothed-shape precast deck joint reinforced with milled-cut steel fibers, aimed at enhancing both fatigue and cracking performance for accelerated bridge construction (ABC). Full-scale fatigue tests were conducted under variable-amplitude progressive loading to compare the performance of toothed-shape and flat joints. Additionally, advanced Extended Finite Element Method models, integrated with the Virtual Crack Closure Technique (XFEM-VCCT), were developed and calibrated against the experimental results to reveal interfacial cracking mechanisms. The results demonstrate that incorporating milled-cut steel fibers effectively controlled crack propagation. The toothed-shape joints significantly enhanced cracking resistance, with a 40 % increase in interfacial cracking load compared to flat joints. This joint design also improved fatigue performance including increased stiffness, lower residual deflection, and reduced stress ranges, thereby delaying rebar fracture and extending the fatigue life of the joints. The well-calibrated XFEM-VCCT models accurately reproduced interfacial fatigue crack propagation, further validating the effectiveness of the joint design. Moreover, a preliminary analytical model was proposed to give reasonable prediction of the cracking resistance for proposed joint, incorporating key factors such as tooth geometry and interfacial cohesion strength. The findings highlight the potential of the toothed-shape SFRC joints for improving the durability and longevity of precast deck systems, offering a promising solution for ABC practices.]]></description>
      <pubDate>Thu, 29 Jan 2026 08:52:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635418</guid>
    </item>
    <item>
      <title>A physics and data co-driven initial temperature field reconstruction approach for real-time thermal analysis of concrete bridges</title>
      <link>https://trid.trb.org/View/2632535</link>
      <description><![CDATA[Substantial non-uniform temperature fields, induced by the combined effects of solar radiation, ambient air temperature, and convective heat transfer, can generate thermal loads exceeding the operational limits of concrete bridges, causing structural deformation or damage. Accurate temperature field prediction is crucial for assessing service conditions and providing early warnings of thermal-induced failures. However, conventional numerical simulations face significant challenges, including reliance on approximate boundary conditions, high computational costs, and limited accuracy due to the sparsity of measured data. Existing interpolation methods rarely incorporate physical constraints and are, therefore, less applicable to bridge engineering. To address these issues, a physics and data co-driven approach is proposed, coupling the ray-tracing algorithm with physics-informed neural networks to enhance both computational efficiency and prediction accuracy. Low-fidelity numerical pre-analysis and sparse high-fidelity measurements are integrated via transfer learning to reconstruct initial temperature fields with high precision, even under minimal data conditions. The reconstructed field subsequently serves as the initial condition for temperature prediction. Additionally, a level-of-detail multi-scale model based on the ray-tracing priority principle is introduced to enhance shadow effect analysis, significantly improving the efficiency of external heat flux calculation. Validation on the Huinan Bridge in Shanghai demonstrates a mean absolute error of 1.05°C, satisfying precision requirements for thermal load calculations. Compared to numerical simulations and data-driven simulations, substantially lower short-term prediction errors are achieved with only 18 initial-value inputs, while heat flux updating efficiency is accelerated by 26.3 %. This work provides an effective tool for real-time assessment of bridge service conditions.]]></description>
      <pubDate>Tue, 27 Jan 2026 09:19:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2632535</guid>
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