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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Mechanisms of reef shielding breakdown and harbor vortex formation under extreme tsunamis: A case study of Yongxing Island, the South China Sea</title>
      <link>https://trid.trb.org/View/2768109</link>
      <description><![CDATA[The tsunami hazard to remote atolls in the South China Sea remains poorly quantified. This study numerically investigates mechanisms of reef shielding breakdown and harbor vortex formation at Yongxing Island under Mw 8.0 and Mw 9.1 tsunamis in the Manila Trench, employing nonlinear shallow water wave model and wavelet analysis. Under the Mw 9.1 scenario, maximum nearshore wave amplitude increases substantially from 0.25-1.0 m to 5-10 m. The dominant tsunami period nearshore is consistently 30-35 min, controlled by island bathymetry, while the strong earthquake extends the high-energy duration from 1-4 h to 1-6 h. Critically, the reef's sheltering effect, evident under the moderate earthquake, largely vanishes under the strong earthquake, leading to persistent large-scale vortices in the semi-enclosed harbor, extreme velocity amplification at the entrances, and a shift toward multi-directional currents. Consequently, the hazard zone expands from isolated windward headlands to the entire island. These findings clarify the coupled bathymetric and seismic controls on tsunami response, providing a scientific basis for hazard zoning and port infrastructure design on islands and reefs in the South China Sea.]]></description>
      <pubDate>Wed, 16 Sep 2026 16:15:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2768109</guid>
    </item>
    <item>
      <title>Particle crushing and its effect on compression and creep behaviors of calcareous sand in oedometer test</title>
      <link>https://trid.trb.org/View/2701535</link>
      <description><![CDATA[A series of oedometer tests were conducted to investigate the compression and creep behaviors of calcareous sand collected from the South China Sea. Two essential factors, i.e., vertical stress and relative density, were considered in test program. The test results were analyzed to reveal variations in compression and resilient indices, creep strain, characteristic particle sizes, grading indices, and particle breakage of calcareous sand. The research findings showed a noticeable grading change in calcareous sand during compression or creep, indicating the occurrence of significant particle crushing, and the compression or creep behavior was notably affected by particle crushing of calcareous sand. An asymptotic function was proposed to represent the nonlinear increase of creep strain with time, and a decaying exponential function was put forward to characterize the growth of relative breakage with vertical stress and relative density during compression or creep. Furthermore, 1D compression and creep empirical models for calcareous sand were developed and expressed as the product of several power function factors through regression analysis and mathematical derivation. These empirical models incorporated the relative breakage as an independent variable and can accurately represent changes in compression and creep strains with vertical stress, relative density and relative breakage of calcareous sand.]]></description>
      <pubDate>Fri, 28 Aug 2026 08:34:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701535</guid>
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    <item>
      <title>Prediction of corrosion in subsea multiphase mixed transport pipelines based on physics-informed neural networks</title>
      <link>https://trid.trb.org/View/2702735</link>
      <description><![CDATA[In subsea multiphase transport systems, pipelines are exposed to harsh thermal, hydraulic, and chemical conditions that accelerate internal corrosion and threaten operational safety. Accurate prediction of corrosion rates is critical for design optimization and proactive integrity management; however, existing models often overlook the nonlinear, multi-physics couplings that govern corrosion evolution. Here, we introduce EKP-PINN, a hybrid framework that integrates Empirical Mode Decomposition (EMD), Kernel Principal Component Analysis (KPCA), and physics-informed neural networks (PINNs) to achieve multiscale feature extraction, nonlinear condition reconstruction, and mechanism-guided learning. By embedding electrochemical, hydrodynamic, and mass-transfer equations into the loss function, the model captures both data-driven patterns and the governing physical laws. Engineering validation demonstrates that EKP-PINN achieves an R² of 0.9606 in training, 0.9435 in testing, and 0.9169 overall, with a MAPE of approximately 0.9%, outperforming OLGA while maintaining comparable computational costs. EKP-PINN provides a robust, interpretable and mechanism-consistent tool for corrosion-rate prediction and supports full-lifecycle integrity assessment in subsea pipeline systems.]]></description>
      <pubDate>Thu, 04 Jun 2026 11:56:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2702735</guid>
    </item>
    <item>
      <title>ASNGRC: A MIMO modeling and forecasting method for state information of USV</title>
      <link>https://trid.trb.org/View/2706995</link>
      <description><![CDATA[Low training efficiency and heavy modeling reliance on large datasets remain significant challenges for Unmanned Surface Vessels (USVs) modeling and prediction in complex marine environments. To address these challenges, this paper presents a USV state modeling and prediction approach called Adaptive Sparse Next Generation Reservoir Computing (ASNGRC). First, the hyperparameters of NGRC such as the time delay order are optimized through a grid search algorithm to determine memory depth and accomplish feature reconstruction. Then, the F-statistic is introduced to select important features of the reconstructed features, reducing computational burden and achieving adaptive sparse feature reconstruction. Subsequently, multi-step forecasting of state information is implemented by a sliding window method based on an event-triggering mechanism. Finally, state modeling and forecasting of USV are performed using real sea trial data from the Yellow Sea and South China Sea. The results show that ASNGRC delivered more reliable predictions than the other methods across different data sizes, and verify that its high accuracy was maintained while the computational cost was reduced. The proposed approach provides a practical tool for real-time USV state estimation and short-term intelligent prediction in complex marine environments.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:14:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706995</guid>
    </item>
    <item>
      <title>Environmental data driven dynamic Bayesian network: Spatiotemporal evolution of coastal shipping risk performance in China</title>
      <link>https://trid.trb.org/View/2656361</link>
      <description><![CDATA[The rapid development of the global shipping industry has led to increasingly prominent maritime traffic risks, which pose a serious threat to economic development, the ecological environment, and public safety. In this context, this study develops an environmental data-driven dynamic Bayesian network (DBN) model to simulate the spatiotemporal evolution of maritime traffic risks using large-scale data from complex shipping systems. Initially, based on the Systems Theoretic Accident Model and Processes (STAMP) accident causation framework, risk influencing factors (RIFs) are identified through the systematic analysis of maritime accident reports. Then, to address the dynamic nature of maritime traffic risks, a novel transition probability matrix learning mechanism integrating environmental data is proposed, enabling the DBN model to characterize risk performance spatiotemporal evolution. Finally, a case study of the four major sea areas along the China coast reveals that the evolution of risk performance exhibits significant spatiotemporal heterogeneity across different regions, with the East Sea and the South China Sea showing the most pronounced variations. Fluctuations in risk performance are highly correlated with seasonal meteorological and hydrological changes, and the distribution of accident risks is closely linked to extreme weather events. This study provides reliable quantitative tools to support spatiotemporal risk management and cross-regional decision-making in maritime traffic systems.]]></description>
      <pubDate>Mon, 13 Apr 2026 09:40:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2656361</guid>
    </item>
    <item>
      <title>Real-time analysis of drillstring dynamic insertion and system vibration-induced wellbore wear in offshore directional well</title>
      <link>https://trid.trb.org/View/2684967</link>
      <description><![CDATA[Environmental loads influence offshore directional oil and gas wells, and drillstring vibration-induced wellbore wear exhibits strong nonlinearity and spatial non-uniformity. Conventional fixed-length models struggle to capture boundary evolution and wear accumulation during continuous drilling. This work develops a system dynamics model that incorporates dynamic drillstring insertion and real-time monitoring of wellbore wear, while explicitly accounting for offshore environmental loads. The model enables synchronous updating of system configuration, boundary constraints, and contact states as the drill string extends, and it outputs real-time vibration responses and wellbore wear. A full-well traversal analysis is performed for Directional Well X in the South China Sea. A wear quantification and visualization method is proposed to generate visualizations of wellbore wear depth and drillstring–wellbore contact severity. The results reveal the mechanisms underlying the mapping among vibration response, contact mode, and wear morphology. Finally, the coupled Archard wear theory introduces the wellbore curvature wear amplification factor (WAF), providing a quantitative metric that links wellbore geometry to cumulative wear. The results show that the vertical section is dominated by low-frequency, low-amplitude random point contacts. Wear appears as discrete wear bands, and the primary mechanism is occasional transient impact wear. In the curved section, the coupling between geometric constraint and stick-slip vibration produces an intermittent line-contact pattern characterized by “wall sticking–stick-slip–recontact”. A continuous, wide wear belt develops on the low side, accompanied by ring-like wear bands. The wear mechanism is a strongly coupled combination of directional cutting and transient impacts. In the horizontal section, gravity-induced lateral loading and buckling drive the system into a sustained line contact state. Wear is dominated by continuous directional cutting under high contact stress, forming connected wear belts and typical crescent-shaped grooves. This section is the primary control zone for wellbore failure. Quantitative results indicate that the wear intensity in the curved and horizontal sections is 4.2 and 9.2 times that in the vertical section, respectively, and the horizontal section is further amplified by a factor of 2.2 relative to the curved section. These findings suggest that, under prescribed offshore boundary conditions, curvature-driven wear amplification is jointly governed by contact loading and cumulative sliding distance.]]></description>
      <pubDate>Thu, 02 Apr 2026 13:51:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684967</guid>
    </item>
    <item>
      <title>Coupled dynamic response of deep-sea drilling platform-mooring-riser systems under internal solitary waves</title>
      <link>https://trid.trb.org/View/2644062</link>
      <description><![CDATA[Deep-sea drilling platforms in the South China Sea are frequently subjected to strong internal solitary waves (ISWs), which can induce large nonlinear responses in platform-mooring-riser systems. Current literature inadequately addresses critical parameters including water depth and density stratification ratio, with limited insights into platform-mooring-riser coupling mechanisms. This study develops a specialized dynamic response algorithm for deep-sea drilling platform systems under ISW environments based on the Vector Form Intrinsic Finite Element (VFIFE) method. The algorithm enables fully coupled analysis of platform-mooring-riser interactions, accounting for the geometric nonlinearity and large deformation characteristics of the system. A systematic parametric study is conducted to investigate the coupled dynamic responses under varying ISW conditions, including different water depths, density stratification ratios, wave amplitudes, and incident angles. Results reveal that ISWs generate substantial impact loads on the system, with the peak upper-layer flow velocity identified as the key factor governing structural responses. Platform loads scale quadratically with flow velocity, while riser top tension increases quadratically with platform horizontal displacement and mooring line tension increment correlates with platform displacement ratio, with proportionality coefficients dependent on density stratification. These findings provide quantitative insights into the coupling mechanisms and highlight the critical risks posed by ISWs to deep-sea drilling operations.]]></description>
      <pubDate>Fri, 13 Mar 2026 08:46:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2644062</guid>
    </item>
    <item>
      <title>Pollution, degradation, and risk assessment of microplastic (&gt; 30 μm) in subsurface (5 m) seawaters along Tokyo-Bangkok shipping route</title>
      <link>https://trid.trb.org/View/2607718</link>
      <description><![CDATA[In this study, environmental microplastic samples (>30 μm) were collected from subsurface seawater (5 m depth) along a major Asia–Pacific shipping route from Tokyo to Bangkok. The samples were characterized, ecological risk was assessed, and results were also compared with surface water samples. The results showed spatial variation in microplastic concentrations along the route, with the highest concentration (5904 pieces/m³) observed in the South China Sea and the lowest concentration (3272 pieces/m³) in the offshore Tokai region. Subsurface microplastic concentrations were generally higher than surface concentrations. Polyethylene (PE) was the dominant polymer type, and polymer diversity was lower in the subsurface than in surface waters. Subsurface microplastics were found to be smaller in size while less degraded compared to surface microplastics. Despite higher concentrations, ecological risk levels at the subsurface were comparable to those in the surface due to the presence of less toxic polymer types in subsurface samples. Further evaluation indicated that estimated ecological risk levels are strongly influenced by mesh selectivity and the spatial coverage of sampling stations. This study highlights the spatial heterogeneity of subsurface microplastics and reveals important differences from surface counterparts. In addition, relying solely on surface data may result in biased estimation of total microplastic exposure and ecological impact. The findings from this study provide valuable reference data for future investigations, and can help the design of monitoring programs, the development of environmental policies, and the formulation of mitigation strategies.]]></description>
      <pubDate>Mon, 15 Dec 2025 10:34:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2607718</guid>
    </item>
    <item>
      <title>An improved hybrid FMEA method based on spherical fuzzy sets for risk assessment of offshore anchor pile installation</title>
      <link>https://trid.trb.org/View/2608933</link>
      <description><![CDATA[The single-point mooring system is an essential facility for offshore oil platforms, which can realize offshore positioning and limit platform offset, and its mooring capability mainly relies on anchor piles. Offshore anchor pile installation has high risks due to its size and special working conditions. The risk assessment tool failure mode and effect analysis (FMEA) can effectively assess potential failures during the installation process. This paper proposes an improved hybrid FMEA method based on spherical fuzzy sets (SFS), integrating the spherical fuzzy Dombi weighted Heronian mean (SFDWHM) operator, criteria importance assessment (CIMAS), entropy weight method (EWM), cumulative prospect theory (CPT) and combined compromise for ideal solution (CoCoFISo) methods. A new two-level risk factor structure is constructed to provide a comprehensive assessment of failure modes. The application of this method to the evaluation of anchor pile installation for a floating production storage and offloading (FPSO) in the South China Sea illustrates the practicality of the proposed method. The sensitivity analysis reflects the robustness and flexibility, and the comparative analysis indicates the reliability of this method. The results show that the proposed method is a risk assessment method capable of accurately, stably and flexibly analyzing the failure of offshore anchor pile installation.]]></description>
      <pubDate>Fri, 05 Dec 2025 14:08:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2608933</guid>
    </item>
    <item>
      <title>Nonlinear modeling of the 3-D ocean sound speed field via incremental sample convolutional exchange network</title>
      <link>https://trid.trb.org/View/2578083</link>
      <description><![CDATA[The accurate construction of the underwater sound speed fields (SSFs) is critical for systems of positioning, navigation, timing, and communication (PNTC). Currently, the 3-D ocean currents observation is limited by insufficient flow field data and technical constraints, resulting in significant sound speed errors that adversely affect underwater positioning accuracy. To address the challenge of achieving continuous spatiotemporal observations within marine areas, the authors propose an incremental sample convolutional exchange network (ISCEN) to construct localized 3-D ocean SSFs. Through split and interactive learning, the model iteratively extracts and exchanges ocean acoustic environmental parameters across multiple temporal resolutions. Therefore, it can learn enhanced features of the SSFs and predicting future sound speed distributions. Note that the limitations of computational power and prolonged training times associated with traditional offline learning, they introduce an improved incremental learning method. This approach leverages prior information to achieve intelligent and high-precision construction of SSFs. Experimental results indicate that the model can accurately reconstruct sound speed profiles (SSPs) within the 0 m to 2000 m depth range in selected regions of the South China Sea and the Western Pacific on CORTA 1.0-WNP dataset. The proposed method can flexibly provide real-time sound speed distributions tailored to the varying needs across different areas.]]></description>
      <pubDate>Thu, 14 Aug 2025 14:55:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2578083</guid>
    </item>
    <item>
      <title>A novel buoy optimization approach for PAWEC in sea states with seasonal wave distribution</title>
      <link>https://trid.trb.org/View/2560148</link>
      <description><![CDATA[The buoy size significantly affects the wave energy captured by the point-absorption wave energy converter (PAWEC). Understanding the parameter's dynamics is critical for tailoring buoy sizes to specific sea conditions. This study employs Design of Experiments (DOE) and ANSYS AQWA software to reveal that the buoys' radius draft ratio (R/L) has a predictable impact on wave energy absorption and, for the first time, identifies the accurate threshold that affects buoy oscillation performance. Considering that the wave energy in most sea areas worldwide exhibits distinct seasonal distribution characteristics, a novel buoy optimization method is proposed to fit the specific marine environments. Taking the South China Sea as an illustrative case, the seasonal and annual wave energy absorption of buoys with different R/L are discussed in detail. Ultimately, the buoy with R = 6.5 m and L = 6 m (R/L = 1.08) is verified as the most suitable one for the sea area, providing valuable insights for practical engineering applications.]]></description>
      <pubDate>Fri, 18 Jul 2025 09:05:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2560148</guid>
    </item>
    <item>
      <title>Effect of stress paths on cyclic behavior of marine calcareous sand for transportation infrastructure applications</title>
      <link>https://trid.trb.org/View/2568527</link>
      <description><![CDATA[As a new type of granular backfill material, calcareous sand is widely used in the construction of marine transportation infrastructure. And they are subjected to complex irregular long-term dynamic loading such as that from waves, traffic and even earthquakes. In this paper, 22 groups of undrained cyclic shear tests were performed with calcareous sand under various cyclic stress ratios and cyclic stress paths. The influence mechanism of stress path on the cyclic shear behavior of calcareous sand was investigated. The results show that the ultimate residual pore pressure at critical state was not affected by cyclic stress ratios and paths. But the cyclic shear behaviors of calcareous sand including failure pore water pressure and long-term deformation were changed significantly. Axial load plays a dominant role in each stress path. A stress path parameter ω was proposed to characterize the vertical shaking impact of cyclic stress paths with different initial orientation of the σ1 axis to vertical ασ0. And a power function of ω was used to describe the involvement level of soil skeleton in anti-liquefaction. This parameter performs well in representing cyclic stress paths with different orientation to the vertical. A series of formulas were proposed to predict the failure residual pore pressure and the long-term cumulative deformation behavior of calcareous sand. More accurate shakedown discriminant boundaries suitable for almost unbroken calcareous sand were proposed.]]></description>
      <pubDate>Thu, 26 Jun 2025 16:12:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2568527</guid>
    </item>
    <item>
      <title>Research and application of optimization method for semi-submersible platform mooring system based on deep learning</title>
      <link>https://trid.trb.org/View/2551474</link>
      <description><![CDATA[In deepwater oil and gas extraction, the mooring system is crucial for the safety and efficiency of production operations. This study proposes an optimized design method for mooring systems to address the challenges of accuracy and computational efficiency that traditional design methods encounter under extreme environmental conditions. This method utilizes enhanced multi-task deep learning and is applied to the design of the “Deep Sea No. 1″ mooring system. Firstly, a coupled numerical model of the system was established, generating a dataset of 2356 design scenarios. An enhanced multi-task deep learning model was developed, leading to the construction of an optimization surrogate model. An improved optimization algorithm was employed to determine the optimal Pareto front, yielding the best combination of mooring system parameters. The results indicate that the optimized maximum tension and platform offset were reduced by approximately 29.7 % and 34.2 %, respectively, significantly enhancing the performance of the mooring system under extreme conditions. This research provides essential theoretical foundations and practical guidance for designing ultra-deepwater mooring systems in marine engineering, significantly improving the safety and reliability of deepwater oil and gas operations.]]></description>
      <pubDate>Mon, 09 Jun 2025 14:49:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2551474</guid>
    </item>
    <item>
      <title>Extreme value prediction for the dynamic responses of a semi-submersible platform in harsh environments with consideration of mooring line failure accidents</title>
      <link>https://trid.trb.org/View/2554641</link>
      <description><![CDATA[Deep-sea platforms are crucial for exploring oil and gas resources, and ensuring the safety of the mooring system of semi-submersible platforms under harsh ocean conditions is a primary focus during the design phase. During the service life of a semi-submersible platform, mooring lines may unexpectedly fail due to fatigue or other factors, posing a threat to platform safety. Therefore, accurately predicting the extreme mooring tension and platform motion responses following a mooring line failure is crucial for assessing the resilience of the mooring system and ensuring the safe operation of the platform. In this work, the ACER method and the Gumbel method are employed to predict the extreme dynamic responses of a semi-submersible platform under both complete and failure mooring conditions, and platform safety is evaluated according to relevant regulations. Extreme sea states are selected in the South China Sea with a 100-year period. The results demonstrate the exceptional performance of the ACER method in handling both stationary and nonstationary stochastic processes. A comparison of the extreme mooring tension of the semi-submersible platform and the motion response of the platform under the two conditions reveals the impact of the accidental failure of a single mooring line on the safety of the platform under severe sea conditions. It is recommended that the ACER method be employed for extreme value prediction research during accidental conditions such as failure events of the mooring system. The extreme tension of the mooring lines adjacent to the failure line should be considered as a critical evaluation index in the mooring system design should be fully accounted for to prevent consecutive mooring line failures.]]></description>
      <pubDate>Thu, 05 Jun 2025 13:30:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2554641</guid>
    </item>
    <item>
      <title>Measuring maritime search and rescue (SAR) accessibility using an improved spatiotemporal two-step floating catchment area method: A case study in the South China Sea</title>
      <link>https://trid.trb.org/View/2517313</link>
      <description><![CDATA[Accessibility is a crucial metric for evaluating the effectiveness and disparity of search and rescue (SAR) services. Traditional models of accessibility are typically focused on land-based scenarios, often overlooking the unique challenges posed by complex, dynamic maritime emergencies. To bridge this gap, this study introduces an improved spatiotemporal two-step floating catchment area (ST-2SFCA) method, specifically designed to assess SAR accessibility in maritime contexts. The method simultaneously considers various time-dependent factors, including the SAR demand, rescue supply, and oceanic conditions, alongside typical normal or extreme oceanic scenarios. Geographic Information System (GIS)-based techniques are combined with diverse, spatiotemporal SAR datasets—including ship traffic flow data, incident records, rescue base and vessel parameters, and wind and wave data—to refine calculations of response times, supply-to-demand ratios, and overall accessibility. A case study in the South China Sea region across five countries—China, Vietnam, the Philippines, Singapore, and Malaysia—examines the authors' proposed method's applicability and effectiveness. Moreover, the results reveal that ignoring dynamic supply-demand interactions and oceanic influences can lead to inaccurate SAR accessibility estimates, potentially misleading stakeholders. These findings provide insights for policymakers, improving the understanding of dynamic SAR performance, offering recommendation for enhancing SAR systems, and supporting regional cooperation among nations.]]></description>
      <pubDate>Fri, 14 Mar 2025 16:28:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2517313</guid>
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