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    <title>Transport Research International Documentation (TRID)</title>
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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>CNN-based typhoon structural parameter prediction and 3D wind field modeling for offshore applications</title>
      <link>https://trid.trb.org/View/2641253</link>
      <description><![CDATA[Accurate modeling of typhoon wind fields is critical for wind hazard assessment and offshore structural design. This paper proposes an integrated framework that combines a convolutional neural network (CNN)-based typhoon structural parameter predictor with hybrid data-driven parametric models to reconstruct three-dimensional typhoon wind fields. A historical typhoon dataset spanning from 1980 to 2020 is created by inverting typhoon surface-level wind fields, serving as the foundation for data-driven model training. A CNN model is developed to predict typhoon structural parameters using common meteorological typhoon variables. The proposed CNN-based prediction model outperforms multiple regression methods in terms of generalizability. Cross-validation using independent typhoon datasets further validates the reliability of the reconstructed surface-level wind fields. Building on the structural parameter predictions, a semi-empirical three-dimensional typhoon wind field model is constructed, incorporating vertical wind profile, turbulence spectra, and spatial coherence functions, along with stage-dependent characteristics of typhoon evolution. Case study using Typhoon Doksuri in 2023 illustrates the model's applicability in capturing key wind characteristics and assessing the potential impacts on offshore structures. Compared to mesoscale atmospheric numerical simulations, the proposed method is more computationally efficient and better suited for scenario-based engineering applications, providing a scalable and data-adaptive solution for synthesizing typhoon wind field.]]></description>
      <pubDate>Wed, 11 Mar 2026 14:41:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2641253</guid>
    </item>
    <item>
      <title>Real-time probabilistic spatiotemporal forecasting of building functionality in flood emergencies: a deep learning approach to facilitate community evacuation planning</title>
      <link>https://trid.trb.org/View/2652078</link>
      <description><![CDATA[Effective evacuation planning during flood emergencies requires reliable predictions of dynamic evacuation demands, which are intrinsically linked to the community-wide evolution of building functionality under progressing flooding. However, existing models often face challenges in balancing the precision of physics-based simulations with computational efficiency, limiting their real-time applicability. To address this limitation, the Probabilistic Building Functionality Forecasting (PBFF) model is proposed –a real-time, community-scale surrogate for computationally expensive, physics-based, probabilistic assessments. The PBFF model leverages a deep neural network, trained on a comprehensive labeled dataset generated through physics-based assessment, to directly map rainfall sequences to the probabilistic prediction of building functionality in stricken communities for single-step forecasting. The temporal evolution of community-wide building functionality states throughout extreme rainfall events is captured by incorporating an iterative prediction strategy. Validation results highlight the PBFF model’s capability to accurately identify spatiotemporal distribution characteristics of functionality-impaired buildings, particularly during critical periods of significant functionality loss. The PBFF model’s development and application are exemplified in a flood-prone area in Fuzhou, China. A case study of typhoon-induced rainstorm showcases the model’s ability to accurately forecast the spatiotemporal evolution of building functionality and evacuation demands, establishing a new benchmark for real-time, community-scale impact forecasting to support proactive evacuation planning.]]></description>
      <pubDate>Thu, 29 Jan 2026 15:56:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652078</guid>
    </item>
    <item>
      <title>Mitigating Typhoon Disruptions and Enhancing Port Infrastructure Performance: A Risk Assessment Approach</title>
      <link>https://trid.trb.org/View/2613605</link>
      <description><![CDATA[Ports, positioned at the vital juncture of sea and land, are acutely vulnerable to external natural hazards such as typhoons, exposing them to significant risks and operational challenges. Assessing performance is crucial for understanding and mitigating typhoon-induced disruptions in port systems. In this study, a systemic framework of multistate model integrated with a Markov model is developed for assessing typhoon impacts on port operations. Using operational data from Shanghai Port in 2023, the research constructs transition matrices to analyze and predict the operational dynamics of port system in scenarios with and without typhoon disturbances. The paper extends the analysis by employing a system dynamics model to evaluate various risk response strategies, including typhoon preparedness and emergency response. Key findings demonstrate that strategic response measures significantly mitigate the adverse effects of typhoons on port operations, reducing the time to recover to the average operation level and the maximum reduction of infrastructure capacity. This comprehensive approach provides practical frameworks for port authorities and policymakers to implement risk management strategies under extreme weather conditions.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613605</guid>
    </item>
    <item>
      <title>Risk assessment of strait-crossing routes using typhoon-induced multi-hazard environmental contours sampled from optimized hierarchical Archimedean copula models</title>
      <link>https://trid.trb.org/View/2599629</link>
      <description><![CDATA[Due to the rapid nature of economic development, the demand for strait-crossing passages is increasing, thereby highlighting the importance of rational route planning. However, the development of high-resolution marine environmental hazard maps is crucial for addressing the challenges faced by offshore structures and for conducting reliable route risk assessments. Therefore, a multi-hazard map is constructed for corridor risk assessment of a sea area acquisition system on the basis of sampling-based environmental contours. The Qiongzhou Strait is selected as the study area, and a marine environmental database of typhoons that have significantly impacted the study region is established on the basis of the constructed hybrid wind field and the SWAN + ADCIRC model. Then, optimal wind–wave–current–surge joint probability models are established via the HAC model combined with environmental databases. The multi-hazard map of 100-year load combinations in the strait passage is obtained through the direct sampling-based environmental contour method based on the optimized joint probability models. Finally, both subjective and objective methods are employed to conduct a route risk assessment. The results show that the constructed system can effectively satisfy the requirements. Furthermore, this study provides valuable references and technical support for coastal engineering design and multi-hazard corridor planning.]]></description>
      <pubDate>Thu, 20 Nov 2025 17:07:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599629</guid>
    </item>
    <item>
      <title>Typhoon evolution characteristics and influence on ship navigation with polar coordinate data-driven: A case of historical tropical cyclone trajectory</title>
      <link>https://trid.trb.org/View/2585114</link>
      <description><![CDATA[To improve ship safety navigation in extreme weather, it is critical to understand and predict typhoon trajectories, especially in areas exposed to severe tropical cyclones. By normalizing the complex trajectory to the polar coordinate system, the temporal-spatial behavior analysis of typhoons is simplified, and new insights are prepossessed to interpret their evolution characteristics. First, based on a dataset of 1964 tropical cyclones samples spanning 78 years, the movement trends and trajectory characteristics of Pacific typhoon are revealed. Second, by introducing DTW and K-means methods, a novel framework is proposed to reveal hidden patterns in typhoon movement using polar coordinate transformation and advanced clustering algorithm. Third, this method is directly applied to maritime navigation, especially on the heavily trafficked Maritime Silk Road. The results reveal that the characteristics of typhoons at four phases have different influence on ship navigation, and ocean-going ships could predict and avoid potential risks according to the phase changes of typhoons.]]></description>
      <pubDate>Mon, 11 Aug 2025 09:12:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2585114</guid>
    </item>
    <item>
      <title>Structural response analysis of different submerged floating tunnel route selection conditions in the complex strait under the action of typhoon Sepat</title>
      <link>https://trid.trb.org/View/2545031</link>
      <description><![CDATA[The submerged floating tunnel (SFT), a newly proposed tunnel engineering concept, will replace traditional sea-crossing bridges potentially. The SFT has the advantages of the cost, environmental protection, and terrain adaptability. Existing route proposals for SFT suggest its possible construction in the strait on the western coast of the Pacific Ocean. However, these straits are frequently threatened by typhoon disasters, making it crucial to study the mechanical response of SFT under extreme marine environmental conditions. Therefore, this study has focused on the strait in it and utilized the ADCIRC hydrodynamic model and the SWAN wave model to assess storm surge disaster risks in the region. The finite element software ABAQUS has been used to model the SFT. The study has discussed the spatiotemporal heterogeneity of the coupled response between typhoon waves and the SFT, and the sensitivity of structural parameters under extreme marine conditions. The results indicate that: (1) The dynamic response of the SFT during the movement of the typhoon showed significant variation. (2) Increasing the elastic modulus and diameter of the cables significantly reduced the mechanical response fluctuation of SFT caused by typhoon. (3) The submerged depth of the SFT in the Penghu channel section was suggested to be set to 55–65 m when the typhoon is considered.]]></description>
      <pubDate>Thu, 12 Jun 2025 16:00:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2545031</guid>
    </item>
    <item>
      <title>Hydrodynamic model-based flood risk of coastal urban road network induced by storm surge during typhoon</title>
      <link>https://trid.trb.org/View/2517138</link>
      <description><![CDATA[The occurrence of storm surges during typhoons results in the exacerbation of flooding incidents in coastal cities, with road networks vulnerable to inundation facing an intensified risk. This study presents a framework for assessing the flood risk of urban road networks resulting from the storm surge caused by Typhoon Mangkhut in Macau. Tidal changes in the Pearl River Estuary were simulated using a storm surge model integrated with a cyclone wind field. A high-resolution, small-scale urban hydrodynamic model, accounting for buildings and drainage systems, was further developed. Based on the flood characteristics within the model grid and the stability of people and vehicles, the threat posed by the typhoon-induced storm surge on urban roads was estimated. The results indicate that the maximum storm surge in the Pearl River Estuary during Typhoon Mangkhut exceeded 4.0 m, with approximately 25 % of roads experiencing flooding depth greater than 1.5 m. Most vehicles were at risk of instability, while fewer areas on the west coast of the Macau Peninsula presented a risk to human stability on flooded roads. The findings of this study contribute to the development of flood risk management strategies and emergency evacuation during typhoons.]]></description>
      <pubDate>Fri, 23 May 2025 15:34:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2517138</guid>
    </item>
    <item>
      <title>Impact of flooding on truck movement in Metro Manila, Philippines</title>
      <link>https://trid.trb.org/View/2548255</link>
      <description><![CDATA[Flooding in Metro Manila is a perennial problem given the frequency of typhoons hitting the country every year. When a flood occurs along major roads, vehicular traffic usually results in a standstill, causing major disruptions that impede the flow of people, goods and services. The study assessed the impact of flooding in terms of changes in the route of trucks under reduced road capacities and design speeds while considering the impact on vehicle-distance travelled, vehicle-hour travelled, average travel speed, among others. GPS data loggers were used to track the movements of selected trucks during normal conditions to determine their regular routes. Face-to-face questionnaire survey was also conducted to know the behavior of truck drivers during flooding incidents. Scenario modelling under flooded conditions was developed for a typical day during which trucks are allowed to operate on the road under a 5-year and 25-year flood incident. On a metro-wide scale, during flooding, the vehicle distance travelled (VDT) and vehicle hour travelled (VHT) may not necessarily increase since some vehicles, including trucks, may not be able to travel or are unassigned resulting in a lesser number of them on the road, effectively reducing VDT and VHT. Furthermore, higher VDT during the 5-year flood event were observed compared to the 25-year flood event since there are still many vehicles travelling during the former in search of alternate routes resulting in more distance travelled. However, focusing only on flooded roads, the travel time spent by vehicles increased in order for them to reach their destinations even with reduced number of vehicles traveling on these flooded roads.]]></description>
      <pubDate>Wed, 21 May 2025 13:19:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548255</guid>
    </item>
    <item>
      <title>Resilience assessment of High-speed railway networks from the spatio-temporal perspective: A case study in Jiangsu Province, China</title>
      <link>https://trid.trb.org/View/2512716</link>
      <description><![CDATA[High-speed railways (HSR) are susceptible to disruptions due to a variety of factors such as extreme weather. Improving the resilience of HSR is crucial for minimizing losses and improving operation efficiency. This paper aims to strengthen the resilience of HSR by reducing network vulnerability and enhancing network reliability. An HSR spatio-temporal network (HSRSN) model is constructed to simulate trains’ operation on railways. The model is grounded in the train timetable, combining infrastructure networks and train operations. Critical trains and critical nodes are components that exhibit reduced resilience when the network is subjected to disruptions. Percolation theory is used to identify the critical trains and the information entropy algorithm is introduced for identifying critical nodes. Additionally, a typhoon occurrence is chosen as the disruption for analyzing network vulnerability and connectivity. As for recovery post-disruptions, a strategy is proposed that utilizes timetable adjustments to mitigate the delays caused by disturbances. The performance of the proposed methods has been demonstrated in the case of the HSR network in Jiangsu Province, China. Results show that suspending critical trains during 13:00–15:00 and 17:00–19:00 would significantly reduce the network’s connectivity. Network vulnerability is correlated with both the information entropy of nodes and the timing of link occurrences.]]></description>
      <pubDate>Mon, 31 Mar 2025 08:54:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2512716</guid>
    </item>
    <item>
      <title>Insurance-Service-Oriented Maintenance Strategy of Rural Highway Slopes under Typhoon Disasters</title>
      <link>https://trid.trb.org/View/2499060</link>
      <description><![CDATA[Rural highway slopes are characterized by poor resistance to natural disasters and low insurance coverage, which poses a significant challenge for insurance companies. This paper aims to construct an insurance-oriented rural highway slope maintenance decision-making framework to optimize the slope maintenance strategy and effectively reduce the insurance company’s claim costs. Based on the expectation theory, a set of flexible calculation methods for slope maintenance cost and post-disaster reconstruction cost is proposed. Combined with the probability of slope disaster occurrence, the corresponding maintenance decision-making scheme is formulated. Through the analysis of practical engineering cases in China, the effectiveness of the proposed method is verified. The results show that, after calculating the maintenance strategy of 184 slopes, it is found that nine of the slopes are maintained before the typhoon disaster, and it is expected that claims costs can be saved of up to 44.5?million?Chinese yuan. This study not only provides a new way to improve the income of insurance companies, but also provides theoretical support and practical guidance for disaster risk management of rural highway slopes.]]></description>
      <pubDate>Fri, 31 Jan 2025 08:57:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2499060</guid>
    </item>
    <item>
      <title>Short-term panel data analysis of the effect of flood risk communication on individual evacuation decisions</title>
      <link>https://trid.trb.org/View/2371472</link>
      <description><![CDATA[People-centered risk communication is important to mitigate the flood damage caused by the recent increase in heavy rainfall events in Japan. Longitudinal studies are particularly important for evaluating the effectiveness of risk communication methods; however, current research is insufficient. To address this gap, the authors conducted a longitudinal study, specifically through four panel surveys conducted over a short period, to investigate the effects of various risk communication methods such as running an evacuation simulation to learn about flood damage, providing information about the evacuation behavior of others, and distributing hazard maps. The results of a fixed effects analysis of the panel data suggest that the impact of risk communication depends on the initial evacuation attitude. In particular, the authors find that distributing hazard maps had a negative effect on the evacuation behavior of those who initially responded that they would evacuate. This suggests that residents in non-flood-prone areas may have acquired the correct hazard perception from these hazard maps. However, for those who initially chose not to evacuate, receiving the distributed content had a positive effect on their evacuation behavior 12 h before the typhoon hit. This suggests that those who initially chose not to evacuate may have reconsidered their decision. The findings of this study may help future risk communication by reducing congestion at evacuation sites due to excessive evacuation, while increasing the evacuation rate of those who should evacuate.]]></description>
      <pubDate>Mon, 27 Jan 2025 15:11:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2371472</guid>
    </item>
    <item>
      <title>Slamming load and hydroelastic response of marine very large floating structures under coupled typhoon-wave-current action</title>
      <link>https://trid.trb.org/View/2486505</link>
      <description><![CDATA[Marine very large floating structures (VLFS) are continuously bearing wave slamming loads during operation. Accurate prediction of nonlinear slamming load and the hydroelastic response of VLFS under extreme typhoon-wave-current environments is a key prerequisite for ensuring structural stability. In this study, based on the secondary development of the Model Coupling Toolkit (MCT) coupling platform, the spatio-temporal evolution of wind-wave-current during the landfalling process of super typhoon Meranti are accurately simulated, and the parameter distributions of wind-wave-current in different regions during the typhoon are comparatively analyzed. Furthermore, numerical tank tests of VLFS are designed and conducted by combining the medium/small scale nesting technology. The characteristics of the slamming load and hydroelastic response of VLFS in different typhoon regions are systematically investigated. Finally, the Spearman correlation coefficient is adopted to reveal the correlation mechanism between the nonlinear dynamic responses of VLFS. The research demonstrated that the column slamming load in the typhoon eyewall region is significantly greater than that in the typhoon eye and periphery regions, the wave slamming on the bottom deck of the top floating plate mainly appears in the typhoon eye and eyewall regions. The 2nd-order high-order octave components of surge and pitch account for 28.41% and 18.26% of the fundamental frequency in the typhoon eyewall region. The maximum hydroelastic deformation of VLFS is concentrated in the windward bottom floating plate. The pitch of the VLFS in typhoon eye, eyewall and peripheral regions presented significant correlations with the horizontal load, deck slamming load, and column slamming load, respectively, with Spearman correlation coefficients of 0.80, 0.83, and 0.89, respectively. The research conclusions of this study can provide theoretical references for the structural design of VLFS.]]></description>
      <pubDate>Mon, 27 Jan 2025 08:55:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2486505</guid>
    </item>
    <item>
      <title>A methodology to quantify risk evolution in typhoon-induced maritime accidents based on directed-weighted CN and improved RM</title>
      <link>https://trid.trb.org/View/2488502</link>
      <description><![CDATA[To mitigate the risk evolution and serious consequences of typhoon-induced maritime accidents, this study proposes a methodology that integrates a directed-weighted complex network (CN) with an improved risk matrix (RM). Firstly, event tree analysis (ETA) is utilized to extract causal chains from accident reports, thereby constructing the directed-weighted CN. Secondly, topology indicators are employed to assess the risk events within the developed CN quantitatively. Thirdly, simulations involving random and deliberate attacks are conducted to evaluate the robustness of the directed-weighted CN. By considering the network characteristics, the risk levels of causal chains within the CN are assessed and classified using the improved RM. The results indicate that dragging anchors, underestimation of typhoon impact, and improper selection of anchorage are key risk events in the risk evolution of typhoon-induced maritime accidents. These events are predominantly observed in vessels with a length of less than 100 m and those of less than 1, 000 gross tonnage, particularly bulk carriers, followed by dry cargo ships and tankers. Finally, targeted risk mitigation strategies are proposed to prevent risk evolution and chain reactions in typhoon-induced maritime accidents.]]></description>
      <pubDate>Mon, 27 Jan 2025 08:55:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2488502</guid>
    </item>
    <item>
      <title>Spatial-temporal big data analysis of ship avoidance patterns during typhoon approaches</title>
      <link>https://trid.trb.org/View/2491728</link>
      <description><![CDATA[Typhoons pose a significant threat to maritime safety, affecting numerous ships and ports in South Korea annually. This study analyzes ship avoidance patterns during Typhoons SOULIK and KONG-REY using Automatic Identification System data. Through K-means clustering, anchorage and drifting patterns both inside and outside territorial waters are identified. A spatial-temporal analysis, utilizing minimum bounding geometry and centroid comparison, assesses the positions of ship clusters relative to the typhoon's path. The analysis recommends maintaining a minimum distance of 300 km from the typhoon's path for safe avoidance. Statistically significant differences in ship patterns under non-typhoon conditions were also identified using Kuiper's test. These findings emphasize the importance of data-driven decisions for enhancing maritime safety and developing typhoon avoidance strategies.]]></description>
      <pubDate>Mon, 27 Jan 2025 08:55:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2491728</guid>
    </item>
    <item>
      <title>Assessing economic resilience in aviation system disruptions based on CGE model</title>
      <link>https://trid.trb.org/View/2459386</link>
      <description><![CDATA[This study employs a Computable General Equilibrium (CGE) model to assess the economic resilience of Shanghai's aviation system disruption caused by Typhoon Lekima. The research integrates advanced modules for disaster shock and economic resilience, providing a comprehensive framework to evaluate economic resilience tactics and their effectiveness. Specially, the disaster shock module is designed to account for perturbations in both commodity flow and passenger flow, and the economic resilience module incorporates both inherent and adaptive resilience tactics. The results show the following. First, Typhoon Lekima significantly impacted Shanghai's aviation system, resulting in substantial GDP losses of 0.52 %, decreased government revenue by 0.29 %, and reduced total investment in the base scenario. Second, the implementation of resilience tactics, both inherent and adaptive, mitigated these losses. Inherent resilience reduced potential GDP losses by 0.29 % in the Shanghai region. Adaptive resilience tactics, such as flight rescheduling, flight diversion, and effective management processes, though initially suppressing GDP due to resource reallocation towards recovery efforts, ultimately enhanced the system's overall resilience. Third, traffic disruptions have a significant hindering effect on regional trade activities, especially in the regional output and value added. The industries most sensitive to traffic disruptions were transportation, storage, and postal service, and wholesale and retail trade. These findings provide valuable insights for policymakers and stakeholders in the aviation industry, highlighting the necessity of resilience tactics to mitigate the economic impacts of future disruptions.]]></description>
      <pubDate>Mon, 30 Dec 2024 15:51:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2459386</guid>
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