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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>Topology optimization using the Material Field Series Expansion method and the Covariance Matrix Adaptation-Evolution Strategy: A potential tool for crashworthiness applications</title>
      <link>https://trid.trb.org/View/2681745</link>
      <description><![CDATA[Topology optimization represents a cutting-edge optimization method that facilitates the design of structures beyond the capabilities of conventional human design approaches. Topology Optimization (TO) identifies highly efficient structures capable of carrying significant loads with minimal material usage. However, most TO studies do not account for impact problems or non-linear plastic constitutive material relationships. This paper introduces the application of the Material Field Series Expansion method in conjunction with the Covariance Matrix Adaptation Evolution Strategy with the potential to optimize structures subject to crash loadings and permanent deformation. Although the results of this work are still preliminary using low impact velocities, the method shows great possibilities to address the crashworthiness problem considerably reducing the computational cost.]]></description>
      <pubDate>Thu, 18 Jun 2026 16:35:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681745</guid>
    </item>
    <item>
      <title>Explainable machine learning for predicting the load-carrying capacity of damaged steel girders after over-height vehicle strikes</title>
      <link>https://trid.trb.org/View/2681619</link>
      <description><![CDATA[Steel bridge girders are often subjected to strikes by over-height vehicles that exceed the allowable vertical clearance underneath a bridge. Such strikes may affect the serviceability of a bridge structure and can significantly reduce the load-carrying capacity of damaged girders. Although finite element analyses are commonly used to estimate the residual capacity of damaged girders, developing and analyzing such models for every strike incident is computationally intensive and time-consuming. To address these limitations, this paper presents a new explainable machine learning methodology that can accurately and efficiently predict the residual load-carrying capacity of damaged steel I-girders. The methodology is conducted in five main stages: (1) data collection, (2) data analysis and preprocessing, (3) model training, (4) model validation, and (5) model interpretation. Five machine learning models were developed and trained to predict the residual capacity of damaged girders. Results show that the eXtreme Gradient Boosting (XGBoost) algorithm outperformed all other models, achieving R2 and MAPE scores of 95.4% and 3.21%, respectively, on the unseen test set. Moreover, the SHapley Additive exPlanations framework (SHAP) was used to explain the global performance of the XGBoost model and interpret its individual predictions. SHAP values revealed that predicted residual capacity is reduced by increases in girder span length and observed horizontal and vertical damage deflections. The proposed machine learning models are expected to provide bridge engineering researchers and practitioners with an efficient and explainable method for assessing the residual capacity of damaged steel I-girders without relying on time-consuming and computationally intensive simulations.]]></description>
      <pubDate>Thu, 18 Jun 2026 08:54:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681619</guid>
    </item>
    <item>
      <title>Evaluation of Dynamic Response for Freeze–Thaw Damaged RC Beams Subjected to Impact Loading</title>
      <link>https://trid.trb.org/View/2616167</link>
      <description><![CDATA[The impact resistance of in-service freeze-thaw damaged reinforced concrete (RC) bridges is a hot issue in the engineering field. Drop weight impact tests were conducted on RC beams after freeze-thaw cycles (FTCs), and the failure modes and dynamic impact responses were investigated. As the number of FTCs improved, RC beams transitioned from flexural to flexural-shear failure, tending to transition toward shear failure after 125 cycles. With the increase in the degree of freeze-thaw damage, the peak impact force and impact response duration of the RC beams decreased, and the impact energy dissipation was also significantly reduced. Conversely, the peak midspan deflection initially decreased and subsequently increased. Considering the uneven distribution of freeze-thaw damage from the surface to the interior of the concrete, a two-degree-of-freedom model for RC beams subjected to FTCs under impact loading was established. The proposed model can reflect the impact dynamic response process of the beams and shows good agreement with the experimental data.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2616167</guid>
    </item>
    <item>
      <title>Damage assessment of CFST columns internally strengthened with I-shaped CFRP under combined collision and explosion loads</title>
      <link>https://trid.trb.org/View/2680250</link>
      <description><![CDATA[Concrete-filled steel tubes internally reinforced with I-shaped CFRP (SCFST-CFRP) columns demonstrate significant potential for critical building structures due to their superior static performance and enhanced resistance to both collision and explosion forces. Critical facilities may be susceptible to vehicular bomb attacks during operation, resulting in combined collision and explosion loading scenarios. This study conducts a damage assessment of SCFST-CFRP columns under such combined loads. The damage mechanism of these composite columns initiates with concrete crushing, followed by plastic yielding of the steel tube at critical zones. This ultimately causes the CFRP profile to fracture, leading to a loss of the load-bearing capacity derived from the composite action of the steel tube, concrete, and CFRP profiles within the column. The coupling effect of these two loads induces more substantial cumulative damage, altering the failure mode under post-event axial compression. Therefore, a damage assessment criterion is developed incorporating residual axial capacity and critical lateral displacement at the failure section. A predictive model for lateral displacement under combined loads is also developed, enabling simplified anti-collision/blast design of the column and rapid post-disaster assessment.]]></description>
      <pubDate>Wed, 17 Jun 2026 12:23:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680250</guid>
    </item>
    <item>
      <title>Scaling effect of large size RC columns under rockfall impact loading: Influence of gravity and axial load</title>
      <link>https://trid.trb.org/View/2680202</link>
      <description><![CDATA[To address the safety of large-size reinforced concrete (RC) columns in mountainous bridges subjected to rockfall impact, this study develops three-dimensional finite element (FE) models to investigate the scaling effect on the impact response of RC columns under the combined action of gravity and axial load. A series of numerical models with different scale factors (λ) and axial compression ratios (n) are established. Comparative analyses are conducted in terms of displacement, impact force, reaction force, and internal force evolution, thereby clarifying how the impact response evolves with scale factors under combined gravity-axial loading. The results show that including gravity significantly reduces the peak displacement of large-size RC columns (with a maximum reduction of approximately 12.8%) and weakens the displacement scaling effect. A pronounced coupling between axial load and scale factor is observed: at low axial compression ratios, axial pre-compression provides a beneficial preloading effect, whereas the large size combined with the high axial compression ratios tends to trigger P-δ instability, which amplifies the displacement scaling effect and reduces the system stability margin. Compared with the evident scaling effects on the secondary peak impact force and the reaction force, the peak impact force exhibits relatively low sensitivity to scale factor and axial load within the investigated parameter range. Mechanistic analyses indicate that the increased proportion of additional bending moments is a key contributor to the intensified displacement scaling effect in large-size columns. Moreover, the increase in impact kinetic energy with size is not synchronized with that in quasi-static energy absorption capacity, leading to more stringent dynamic demands for large-size columns. On this basis, predictive formulas for the scaling effects of peak displacement and impact force are established.]]></description>
      <pubDate>Wed, 17 Jun 2026 12:23:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680202</guid>
    </item>
    <item>
      <title>Impact-force identification using deep learning and Bayesian inference with application on pipeline structures</title>
      <link>https://trid.trb.org/View/2672038</link>
      <description><![CDATA[Structures like bridges and pipelines are vulnerable to impacts from various sources, such as falling debris, over-height vehicles, or floating objects, which can compromise their integrity. Traditional inspection methods are costly and complex and can lead to economic losses due to shutdowns. This research introduces a probabilistic and more efficient approach by combining deep learning and Bayesian inference techniques to accurately measure and analyze these impacts, aiming to enhance the longevity and safety of these structures while mitigating potential critical failures. In this methodology, a novel two-stage approach is implemented to resolve the inverse problem of identifying impact forces on structures. Initially, a convolutional neural network (CNN) classifier for each of the four sensors is employed to determine the impacting material (aluminum, rubber, plastic). This classification stage utilizes ground truth data to identify the nature of the impact accurately. Following this, the preclassified data, categorized by the actual impacting materials, is directed into one of three 5-layer artificial neural networks (ANNs), each designated for a different impacting material. The ANNs act as surrogate models for Bayesian inference to determine impact force and position, resulting in 12 specialized models, each corresponding to a specific combination of sensor and tip type. The ANNs were evaluated using mean squared error, showing precise predictions of the pipeline’s acceleration frequency signals, while the CNN classifier achieved over 99% F1 scores. Using ANN and CNN results, the approximate Bayesian computation with subset simulation technique showed over 90% precision with 7% uncertainty in inferring impact force and 92% precision with 2% uncertainty in determining the impact position along the pipe. Data fusion, combining sensor responses, further improved precision and reduced uncertainty, achieving over 92% precision with 8% uncertainty for impact force and over 98% precision with 1.8% uncertainty for depth. These results demonstrate the method’s reliability and effectiveness in accurately identifying impact forces and locations, even with a single distant sensor.]]></description>
      <pubDate>Mon, 18 May 2026 16:36:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672038</guid>
    </item>
    <item>
      <title>Floating debris impact on historical masonry arch bridges: Model updating and fluid-structure interaction simulation</title>
      <link>https://trid.trb.org/View/2672342</link>
      <description><![CDATA[Historical masonry arch bridges represent critical transportation infrastructure and irreplaceable cultural heritage, yet they face severe threats from floating debris impact during extreme hydrological events. Existing research primarily focuses on ship impact on modern bridges, paying insufficient attention to the material degradation caused by long-term weathering and water erosion. Moreover, current simulation methods often lack adequate bidirectional fluid-structure interaction (FSI) simulation for woody debris impact, leading to inaccurate safety evaluations. This study takes the Nanjing Putang Bridge—a nine-span historical masonry arch bridge constructed in 1512 and a Chinese key national cultural heritage site—as a case study. Two key contributions are presented: first, the development of a two-stage finite element model updating approach based on operational modal analysis to map material degradation; and second, the integration of the updated model with bidirectional FSI simulation to systematically investigate the bridge’s mechanical response under woody debris impact. Results show that under combined water flow and debris impact, tensile stress concentrates on the side wall of Pier No. 5 and joints between Arch No. 3 to No. 6 and their respective arch shoulder walls, without causing structural collapse. Additionally, existing ship collision codes overestimate the impact force of floating woody debris, while the current simulation impact values are only 13–41 % of code-derived ones. This overestimation is corrected by introducing a regression-derived dynamic correction coefficient. This study provides a reliable numerical framework for the safety assessment of historical masonry arch bridges against floating debris impact.]]></description>
      <pubDate>Thu, 14 May 2026 14:00:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672342</guid>
    </item>
    <item>
      <title>A coupled rockfall-bridge damage assessment method integrating trajectory simulation and intrusion detection</title>
      <link>https://trid.trb.org/View/2668769</link>
      <description><![CDATA[Rockfall impacting bridge accidents are characterized by strong randomness, complex dynamic processes, and severe disaster consequences. Taking actual accident of bridge damaged by rockfall impact as research prototype, an intrusion detection algorithm of fallen rocks intruding into bridge clearance limits is developed. Additionally, a coupled rockfall-bridge damage assessment method integrating trajectory simulation and intrusion detection algorithm is proposed. The irrationality of traditional rockfall impact on bridge analysis has been addressed by establishing an integrated analysis framework which includes rockfall motion simulation, intrusion detection algorithm and bridge dynamic analysis. The major work is as follows: (1) The three-dimensional rockfall trajectory simulation determines the range and stagnation point of fallen rocks, effectively revealing distribution of threats to bridge structure and accurately locating high-risk impact zones; (2) The detection algorithm of fallen rocks intruding into bridge clearance limits enables the determination of collisions risk, the localization of impact locations and the extraction of impact parameters; (3) A high-fidelity finite element model is established to replicate bridge plastic damage and conduct residual performance assessment. The rationality and accuracy of the proposed framework are validated by comparing with actual accident. The proposed analysis framework can provide a scientific tool for transportation route selection, bridge structural protection, as well as disaster risk assessment.]]></description>
      <pubDate>Mon, 11 May 2026 08:50:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2668769</guid>
    </item>
    <item>
      <title>Investigation of dynamic characteristics of a vibration isolation system for impact resistance of the marine container</title>
      <link>https://trid.trb.org/View/2643488</link>
      <description><![CDATA[To achieve impact load resistance for the marine container, the paper designs a novel vibration isolation system. The dynamic characteristics of the system are experimentally investigated to verify the mathematical model. Based on the model, the vibration isolation rate is predicted under different conditions and its sensitivity to different influencing factors is investigated. The system is optimally designed for multiple parameters using adaptive particle swarm optimization (APSO). The results show that the vibration isolation system temporarily enters the pressure building displacement stage which does not affect the properties of the system. The model calculations coincide with the test results by more than 97%, except for the pressure building displacement stage. The predictions of vibration isolation rate are more than 80% and the sensitivity to excitation direction, load mass, system frequency and damping ratio is significant. The optimal system can meet the design requirements of engineering applications.]]></description>
      <pubDate>Thu, 30 Apr 2026 09:11:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643488</guid>
    </item>
    <item>
      <title>Validation of Load-Deflection Linearity in Pavements Using Deflection Bowl Parameters</title>
      <link>https://trid.trb.org/View/2685704</link>
      <description><![CDATA[The present study evaluated the load–deflection linearity of pavements incorporating emulsion treated base layers using field deflection data. Seven pavement test sections constructed with different base layer compositions, including conventional granular base and emulsion treated base layers with varying emulsion content and reclaimed asphalt pavement incorporation, were investigated. Surface deflections were measured using a falling weight deflectometer under five impact load levels ranging from 30 kN to 70 kN. Deflection bowl parameters were used to estimate the contributions of the base, subbase and subgrade. Linear regression analysis showed strong linear relationships between load and deflection parameters, with coefficients of determination greater than 0.90 for all sections. Layer elastic moduli were estimated using back calculation and were observed to remain approximately constant within the investigated load range, with standard deviations less than 10% of the mean values. The results indicated that the pavement layers behaved elastically under the applied loading conditions. Deflections measured in sections with emulsion treated base layers were lower than those in the conventional base section, indicating improved stiffness. The findings confirm that linear normalization of deflection data can be reliably applied for structural evaluation within the load range of 30 kN to 70 kN.]]></description>
      <pubDate>Wed, 29 Apr 2026 17:05:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685704</guid>
    </item>
    <item>
      <title>Ice-Load Time-Domain Modeling for Arctic Navigation Using an Enhanced Popov Method</title>
      <link>https://trid.trb.org/View/2628328</link>
      <description><![CDATA[This study presents a newly revised icebreaker external dynamics model, in which friction force and restitution coefficient are accounted for. The unification of classical elastic-plastic mechanics and the pressure–area relationship was demonstrated successfully, and a new nonlinear constitutive relationship for ice was obtained in the general theory of plasticity. Moreover, an explicit formula for the restitution coefficient of ship–ice collision was derived using the analytical methods of elastic-plastic mechanics. The external dynamics and internal mechanics were combined using the restitution coefficient, and a new coupling model was established for time-domain simulation of the ship–ice collision process. This study further developed an established Popov method for collision modeling, and a Likhomanov and Kheisin model for contact pressures. Relevant experimental investigations are discussed, because they can be combined with the proposed numerical model. The presented model is able to assess failure modes, related to penetration depth, dissipated energy, ice force, and motion of the ship–ice system in the accidental limit-state condition.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:20:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628328</guid>
    </item>
    <item>
      <title>Evolutionary patterns of vertical wave-impact forces on the superstructure of box girders: An experimental study</title>
      <link>https://trid.trb.org/View/2631535</link>
      <description><![CDATA[Box girders are a standard configuration in superstructures of coastal bridges, and wave impacts compromise their safety. In this study, a hydrodynamic experiment was conducted on a single-cell box girder at a scale of 1:25 to investigate the characteristics and mechanisms of wave forces acting on the superstructure. The vertical wave force evolution patterns were classified into five distinct categories. The mechanisms underlying these patterns were further examined using particle image velocimetry (PIV) and bubble image velocimetry (BIV) results. Two non-dimensional parameters were proposed to identify wave impact patterns on the box girder, providing insights into the causes and potential failure modes of bridge superstructures. Meanwhile, the influence of the wave height and period on the vertical wave force was also investigated. This study offers valuable insights into the understanding and mitigation of wave-induced impacts on box girder bridges under various wave scenarios and supports the design of resilient nearshore bridge structures.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2631535</guid>
    </item>
    <item>
      <title>Slam-induced loads on a three-dimensional stern model entering into water considering the bottom propeller shaft</title>
      <link>https://trid.trb.org/View/2607030</link>
      <description><![CDATA[The slamming load characteristics of stern structures under severe sea conditions are a research topic that deserves special attention. However, owing to the complex geometric characteristics of the stern, the current understanding of its slamming load characteristics is still insufficient. This study uses the computational fluid dynamics (CFD) method to conduct a numerical simulation study on the water impact problem of the stern structure of a container ship. Unlike previous studies, this calculation specifically considers the influence of the actual propeller shaft on the slamming process. The numerical calculation results were first compared with the existing experimental data for impact load verification, with errors within 10 %. Through numerical simulation, the details of the three-dimensional (3D) free surface flow that was difficult to observe in the experiment were successfully reproduced, and the flow separation and air bubble entrapment phenomena induced by the bottom propeller shaft were captured for the first time. The pressure distribution and slamming force characteristics of the stern surface for falling heights ranging from 250 mm to 900 mm were systematically analyzed, and the impact load‒time history curves of typical measurement points were discussed in detail. The findings reveal that fluid disturbances caused by the bottom propeller shaft weaken the correlation between the impact pressure and initial deadrise angle. Finally, the influences of parameters such as the impact velocity, model scale, shaft size, and model dimensions on the load characteristics were explored. These conclusions can help to improve our understanding of the slamming load characteristics of stern structures.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2607030</guid>
    </item>
    <item>
      <title>Effects of static air gap and pontoon height on breaking wave impact loads on a fixed surface-piercing square column structure</title>
      <link>https://trid.trb.org/View/2661537</link>
      <description><![CDATA[Breaking wave impacts are of particular concern in the field of coastal and marine engineering, due to their potential threat to structural safety. A good understanding of the characteristics and influencing factors of breaking wave impact loads is essential for designing cost-effective structures with the ability to withstand extreme marine environments. This study focuses on the effects of static air gaps and pontoon heights on the impact pressure, pressure impulse, and total impact force generated by various types of breakers on a square column with an overhanging deck. Breaking wave impact tests were carried out on the column with four static air gaps and six pontoon heights under six focused waves. The wavelet-based method was used to analyze the time–frequency characteristics of the breaking wave impact pressure, as well as the vertical variations in peak impact pressures and pressure impulses. The influences of static air gaps and pontoon heights on the breaking wave behavior and the impact forces by four types of breaking waves were discussed. It was found that the presence of columns and pontoons increases the local wave steepness of focused waves, and the pontoons alter the maximum wave height, acting in a similar way to the shoaling effect. The results showed that the increase in static air gaps reduces both the magnitude and position of maximum impact pressure, as well as the maximum pressure impulse and horizontal impact forces. A higher pontoon can cause the maximum wave crest to exceed the deck, directly producing intense impacts. Regardless of the type of breaking waves, pontoon heights close to the wave trough are adverse to decreasing horizontal impact forces of the column structure. In conclusion, the appropriate increase of the static air gap and the rational design of the pontoon height can effectively reduce breaking wave impact loads, lowering the risk of local structural damage.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:57:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2661537</guid>
    </item>
    <item>
      <title>Revolutionizing Coastal Infrastructure Durability with Pervious Concrete: A Cost-Effective, High-Performance Seawall</title>
      <link>https://trid.trb.org/View/2696019</link>
      <description><![CDATA[This project develops and validates a pervious concrete seawall system to reduce wave loads and mitigate scour-related degradation at lower cost and maintenance demand. The work integrates (i) high-fidelity finite element analysis for preliminary design, (ii) fabrication of pervious concrete with tuned porosity (15–35%) using durability-enhancing binders and engineered biochar, (iii) controlled wave flume experiments with instrumented specimens and backfill monitoring, and (iv) seawall design optimization accelerated by surrogate model and genetic algorithm.
To achieve the above mentioned integration, the research will proceed through a series of coordinated actions. First, the research team will build a high-fidelity finite element model, analyze the wave load in seawall, and achieve a preliminary design. Next, pervious concrete specimens with controlled porosity will be fabricated using the preliminary design and tested in a wave flume, which simulates real coastal conditions by generating programmable waves and measuring forces, displacements, and backfill scour behind the seawall. Finally, the team will apply a HyperNetwork, a neural architecture that dynamically generates predictive models, to estimate performance metrics such as energy dissipation and structural stability across different design configurations. The research team has rich experience in developing surrogate models for engineering applications and will complete building this HyperNetwork-based surrogate model in six months. This HyperNetwork will be used together with a genetic algorithm to search for Pareto-optimal designs that balance durability, hydraulic efficiency, and cost. This integrated approach ties together physical testing and advanced modeling to deliver practical, field-ready guidance with the objective of reducing wave-driven degradation and improving structural resilience in simple, cost-effective terms.
]]></description>
      <pubDate>Thu, 23 Apr 2026 16:44:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2696019</guid>
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