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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>Global sensitivity analysis of high-speed train dynamics system with high-dimensional inputs and multiple outputs</title>
      <link>https://trid.trb.org/View/2685645</link>
      <description><![CDATA[A high-speed train dynamics system involves numerous uncertainty parameters, and there are multiple evaluation indices for its dynamic performance. In this paper, we conduct high-dimensional and multi-output global sensitivity analysis for the dynamic performance of high-speed trains by comprehensively considering these dynamics parameters and indices. Firstly, the dynamics simulation model of the high-speed train is established and six dynamics indices for evaluating the safety and comfort of the train are obtained under operating conditions. Subsequently, considering the multi-output and high-dimensional characteristics of train sensitivity analysis, we propose a multi-output global sensitivity analysis method based on the correlation-analysis-guided Kriging model (CA-K). Finally, global sensitivity analysis of 96 uncertainty parameters on six dynamics indices is conducted under three scenarios utilising the proposed method. The results show that (1) CA-K achieves higher accuracy in approximating high-dimensional train dynamics indices than existing conventional surrogate models. (2) The multi-output global sensitivity analysis method can simultaneously identify all important dynamics parameters and exclude unimportant parameters.]]></description>
      <pubDate>Tue, 30 Jun 2026 15:52:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685645</guid>
    </item>
    <item>
      <title>Overpredicted Resistances of Non-Displacement Piles in Sands Using Static Analysis Methods</title>
      <link>https://trid.trb.org/View/2720554</link>
      <description><![CDATA[he goal of this research is to determine the cause of the overpredicted resistances of the low-displacement piles in the project-specific subsurface conditions and either recommend modification factors that can be applied to the Nordlund method or recommend another static analysis method (such as the Beta or API method) to accurately estimate pile lengths. To achieve these goals, the existing data (where the resistance of low-displacement piles in sands was overpredicted) as well as data from two new projects (where the Minnesota Department of Transportation plans to drive low-displacement piles) will be systematically analyzed in this study. Regression methods and sensitivity analyses, as well as numerical simulations, will be used to better understand the reason for the overprediction of the pile resistance, and modify the existing static analysis models to improve the pile resistance predictions in sands. ]]></description>
      <pubDate>Tue, 30 Jun 2026 15:40:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720554</guid>
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    <item>
      <title>Optimization parameter selection method “point to line to surface to point” of electromechanical composite transmission system based on vibration power</title>
      <link>https://trid.trb.org/View/2680757</link>
      <description><![CDATA[As electromechanical composite transmission (EMT) advances toward higher speeds, heavier loads, and greater power density, the intricate vibration transmission paths within the system intensify the coupled vibrations among its components. This study builds upon previous research into vibration transmission in simple single-degree-of-freedom systems. Employing vibration power theory, it analyzes how vibrations propagate between interfaces of subsystems, identifying key parameters influencing vibration to enhance the efficiency of dynamic optimization. Furthermore, this research refines an electromechanical coupling interface model represented by interface forces, based on the system’s electromechanical coupled dynamic model. By utilizing vibration power to characterize the work done by interface forces in EMT system, this study introduces novel perspectives in model analysis of vibration transmission. Simultaneously, this study proposes a “point-to-line-to-surface-to-point” optimization parameter pre-screening method based on vibration power. This method integrates vibration power with sensitivity analysis, progressively narrowing down the range of optimization targets and parameters through analyzing the transmission of vibration power within the system and calculating the sensitivity of component parameters to vibration power. Research findings indicate that tooth profile manufacturing error between the sun gear and planetary gears is the optimal parameter for reducing torsional vibration displacement in the studied EMT system. This study serves as a practical validation of vibration power theory in complex systems, providing guidance for the dynamic optimization and performance enhancement of EMT system.]]></description>
      <pubDate>Tue, 30 Jun 2026 10:21:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680757</guid>
    </item>
    <item>
      <title>Sensitivity analysis of fuel cell operating conditions based on LOESS-Sobol method</title>
      <link>https://trid.trb.org/View/2680779</link>
      <description><![CDATA[Decoupling the influence of operating factors such as temperature, humidity, and back pressure is essential for improving fuel cell efficiency. This study employs a regression model combining Locally Weighted Scatterplot Smoothing (LOESS) with the Sobol index method to analyze the effects of two major parameter categories: temperature and humidity, and stoichiometry and back pressure, on fuel cell output voltage. Using limited experimental data, it uncovers complex interactions and sensitivities among these factors. The results indicate that the stack temperature has the greatest impact, accounting for 60%, with minimal influence from the changes in the current density. Cathode humidity impacts output voltage by about 10%, while anode humidity accounts for approximately 5%. Significant interactions between temperature and both anode and cathode humidity contribute around 9% each. Among stoichiometries, cathode stoichiometry has the largest impact, exceeding 50% at low current density and growing to over 70% as current increases. Back pressure and anode stoichiometry each have an impact of around 10%, with minimal mutual influence. This study highlights the extent to how different operating parameters influence fuel cell performance, offering valuable insights for optimizing fuel cell operating conditions.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:29:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680779</guid>
    </item>
    <item>
      <title>Coupled Probabilistic and Numerical Limit Analysis for Stability Assessment of Rock Tunnels Considering Uncertainties of Input Rock Properties</title>
      <link>https://trid.trb.org/View/2684184</link>
      <description><![CDATA[This study presents a stability analysis of circular tunnels in rock masses following the generalized Hoek–Brown (GHB) yield criterion with uncertain rock properties. Hybrid second-order exponential cone programming (HSOECP) is proposed to capture the nonlinear GHB yield criterion in its original form and is implemented within the framework of finite-element lower-bound limit analysis to model the yielding of rock masses. The probabilistic approaches, including Sobol’s global sensitivity analysis (GSA), the radial basis function–response surface method (RBF–RSM), and Monte Carlo simulations (MCSs), are coupled with numerical limit analysis to propagate input uncertainties to the outputs of interest (OIs). The study is conducted in three steps. Initially, the surrogate relationships between inputs and OIs are developed based on numerical limit analysis for the input realizations generated via Latin hypercube sampling (LHS). In the second step, the sensitive inputs are identified via Sobol’s GSA performed using Saltelli’s MCS algorithm. Finally, the uncertainties of the sensitive inputs are propagated to the OIs by performing MCSs on the surrogate RBF–RSM relationships. The coupled analysis is applied to evaluate the stability of an unlined circular tunnel in a rock mass with a surcharge on the ground surface. The geological strength index (GSI) and the Hoek–Brown constant (mi) are estimated to be the most sensitive inputs in Sobol’s GSA. The tunnel cover-depth-to-diameter ratio and the statistics of the sensitive inputs, i.e., GSI and mi, have a significant effect on the probability of failure.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:29:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684184</guid>
    </item>
    <item>
      <title>Global assessment of bike-sharing sensitivity and resilience to extreme weather</title>
      <link>https://trid.trb.org/View/2706450</link>
      <description><![CDATA[As global climate extremes intensify, assessing how bike-sharing systems respond and recover from weather disruptions is increasingly important for urban resilience. This study develops a comparative framework using a time-series Transformer model and scenario-based simulations to evaluate bike-sharing demand under extreme heat, cold, heavy rain, and snowfall, using hourly trip and weather data from 14 cities worldwide between 2023 and 2025. The weather sensitivity analysis shows that extreme heat reduces demand by over 40% in hotter cities but has limited impacts in temperate ones, while extreme cold and snowfall cause the strongest suppression effects, often exceeding 80%. To further evaluate system resilience, we simulate recovery curves after rainfall and snowfall shocks. North American systems typically rebound within 6–7 hours, whereas Montreal and Seoul show more prolonged recovery periods, while Oslo and New York recover faster due to stronger winter cycling adaptation and operational preparedness. These findings highlight how climatic exposure, travel behavior, and operational readiness shape resilience and provide evidence to support climate-adaptive management and long-term system planning.]]></description>
      <pubDate>Fri, 12 Jun 2026 09:19:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706450</guid>
    </item>
    <item>
      <title>Predictive energy management of series-parallel hybrid electric vehicles and its sensitivity analysis to dynamic traffic environment</title>
      <link>https://trid.trb.org/View/2680783</link>
      <description><![CDATA[This paper proposes a efficient model predictive controller (MPC) for the energy management problem of dual mode intelligent (DM-i) hybrid powertrain equipped vehicles in navigation driving scenarios. The controller is divided into two layers where the upper-layer plans the optimal state of charge (SOC) trajectory according to the dynamic traffic information provided by the navigation system, while the lower-layer determines the optimal operation mode and engine working points. The alternating direction multiplier method (ADMM) is employed in the upper-layer to obtain the optimal solution considering mode switching. Simulation results show that compared with the rule-based strategy, MPC operates the powertrain with 1.48% and 2.49% lower fuel consumption in urban and highway routes, respectively. In the complex routes composed of urban and highway, the fuel-saving rate of MPC is 6.2% and 8.92%, respectively. In the varying scenarios where the driver temporarily changes the driving route, the economy of MPC is still better than the rule-based strategy, which ensures that MPC has strong robustness in practical applications.]]></description>
      <pubDate>Wed, 20 May 2026 09:10:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680783</guid>
    </item>
    <item>
      <title>Quantitative analysis of tire lateral force and stability region boundary sensitivity in vehicle planar motion system based on energy deviation</title>
      <link>https://trid.trb.org/View/2701161</link>
      <description><![CDATA[For the first time, this paper introduces the energy deviation method for quantitative analysis of sensitivity between the stable region boundary and tire lateral force. The vehicle model adopts a three degree of freedom vehicle model and unified tire model suitable for large side-slip angle. Through comprehensive analysis from vehicle handling diagram, dissipation of energy, equilibrium points, and energy deviation, the results demonstrate that this method can not only reveal the sensitive areas on the stable region boundary but also quantitatively characterize the sensitivity. It is more intuitive, concise, and convenient compared to traditional methods. Additionally, this research for the first time quantitatively demonstrates the spiral phenomenon occurring at the boundary between stable and unstable region due to fluctuations in tire force from energy perspective. Furthermore, it explains that this method based on conserved quantity, making it applicable to higher-dimensional vehicle models and has a wide range of applications.]]></description>
      <pubDate>Wed, 20 May 2026 09:10:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701161</guid>
    </item>
    <item>
      <title>A data-driven comparative risk assessment of marine traffic accidents using an object-oriented Bayesian network</title>
      <link>https://trid.trb.org/View/2660617</link>
      <description><![CDATA[Arctic shipping is expanding as sea ice retreats, yet navigation remains exposed to rapidly changing ice regimes, severe weather, and limited shore-support infrastructure. This study develops an object-oriented Bayesian network (OOBN) to support a comparative, accident-type-specific risk assessment of collisions, groundings, and machinery damages. Risk factors were compiled through a structured literature review and coded from 49 official accident investigation reports; 196 normal transit records were introduced as non-accident data to mitigate sampling bias. In the OOBN, accident causation is organised into human, technical, organisational and environmental domains, and the resulting sub-networks allow sensitivity-based ranking of influential factors. Because the transit (non-accident) records do not explicitly describe MTO states, we repeated the ranking under two bounding treatments for unobserved MTO variables (assigned 0.5 versus set to 0). Model outputs differ by accident type, indicating distinct risk signatures; they also suggest interaction-driven amplification in which environmental stressors narrow operational margins and then couple with degraded human performance and technical condition. Overall, the framework links coded accident evidence to a ranked list of intervention targets, which can inform maintenance planning, polar training programmes and regulatory oversight.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2660617</guid>
    </item>
    <item>
      <title>Cost-benefit analysis methodology for new rail vehicle concepts with alternative powertrain systems</title>
      <link>https://trid.trb.org/View/2657086</link>
      <description><![CDATA[There is currently an increased interest in the reactivation of secondary railway lines in Germany. These lines are mostly in bad condition and are not electrified. As diesel-powered vehicles are to be phased out in the future, in order to reduce greenhouse gas emissions, emission-free vehicles are required.Market available vehicles are too large and not suited to the needs of low-frequency secondary lines. Due to the high cost of track electrification, vehicles with alternative drive systems are brought into focus. In addition, high infrastructure costs are incurred for track reactivation.The aim of this work is to develop a comprehensive evaluation approach for a cost-benefit analysis to analyse the economic viability of low frequented railway lines and lines to be reactivated. The advantages of small rail vehicles were discussed on the basis of two tracks to be reactivated and two lines currently in operation. Based on these operational scenarios, cost analyses and cost-benefit analyses were carried out using four different types of vehicles. A sensitivity analysis was used to analyse the impact of passenger utilization and reactivation costs on economic viability.The results show the significant influence of infrastructure-related costs associated with reactivating tracks, as well as track access charges and station fees for tracks in operation. Small vehicle concepts such as rail buses can contribute to cost-efficient operation on low-frequency secondary lines. This study aims to contribute to a better understanding of the factors influencing the economic viability of rail operations on lines with low passenger utilization rates.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:20:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2657086</guid>
    </item>
    <item>
      <title>Capacity Utilisation and Estimated Profitability of Public Fast Charging Stations in Norway</title>
      <link>https://trid.trb.org/View/2579989</link>
      <description><![CDATA[In this paper we set out to determine the profitability of public fast charging stations in Norway based on data from actual use of the infrastructure. With estimated costs for investment and operation, we find that a significant share of the available charging stations was profitable with the current usage pattern. A sensitivity analysis showed that the pricing scheme were the most influential factor in the analysis. If we include a funding policy in the calculation, almost all stations were found to be profitable. This emphasizes the need for funding in a starting phase for charging infrastructure, or for fast charging stations in remote areas to provide sufficient charging options on long distance trips.]]></description>
      <pubDate>Tue, 21 Apr 2026 16:23:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579989</guid>
    </item>
    <item>
      <title>Efficient probabilistic damage analysis of pile group foundations in long-span bridges subjected to ship impact</title>
      <link>https://trid.trb.org/View/2656382</link>
      <description><![CDATA[Ship-bridge collisions pose a growing threat to marine infrastructure, causing severe damage to vulnerable pile foundations and potentially triggering catastrophic bridge collapse. Although the ship collision response of sea-crossing bridges has received scholarly attention,most efforts have been devoted to analyzing the impact mechanics. Meanwhile, probabilistic fragility analysis, crucial for performance-based risk assessment, has been developed mainly for inland bridges under barge collisions. Therefore, a dedicated fragility assessment framework for sea-crossing bridges subjected to large-tonnage ship impact is still lacking. Compounding this, the computational expense of high-fidelity models makes large-sample fragility analysis impractical.This research has developed a computationally efficient fragility assessment framework, using curvature as the damage indicator. It combines the finite element model of fiber-reinforced beam units with an enhanced uniform design-assisted Gaussian process regression surrogate model to conduct reliable probabilistic evaluations and significantly reduce computational costs. Key uncertain parameters are sampled using the Augmented Uniform Design (AugUD) method to generate training data for a Gaussian Process Regression (GPR) surrogate model. The GPR surrogate model has extremely high prediction accuracy. In three different erosion depth scenarios, its R² value is all greater than 0.92. This model enables large-scale Monte Carlo simulations to evaluate damage probabilities under different collision conditions. Finally, a global Sobol sensitivity analysis identifies the most influential parameters governing the probabilistic damage outcomes.]]></description>
      <pubDate>Tue, 21 Apr 2026 14:30:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2656382</guid>
    </item>
    <item>
      <title>From Perception to Prediction: Modeling Pedestrian Satisfaction Using Multilevel Statistical and Sensitivity Methods</title>
      <link>https://trid.trb.org/View/2693758</link>
      <description><![CDATA[This study presents an integrated modeling approach to evaluate pedestrian satisfaction in new urban cities characterized by rapid growth and limited multimodal connectivity. A structured questionnaire, distributed to stratified participants across residential, administrative, and service zones, captured user perceptions of 13 key urban design features, including safety, accessibility, visual coherence, and economic vibrancy. Descriptive statistics and visual analytics revealed that accessibility, protection from crime and traffic, and urban aesthetics were strong correlates of satisfaction. To model these relationships quantitatively, the study employed both ordinal and multinomial logistic regression, with the latter achieving 92.45% classification accuracy. K-means clustering and principal component analysis further uncovered latent user typologies, highlighting the heterogeneity of pedestrian priorities. Local and global sensitivity analyses, including mutual information metrics, identified easy access, protection from traffic, and crime prevention as the most influential features. Response surface modeling illustrated nonlinear interactions among key variables, emphasizing the multidimensional and synergistic nature of satisfaction outcomes. The findings showed that pedestrian experience is shaped not by isolated design features, but by their interactive effects across spatial, psychological, and infrastructural domains. The study offers actionable insights for human-centered urban design, while the presented analytical framework is scalable and supports evidence-based interventions in emerging urban contexts.]]></description>
      <pubDate>Fri, 17 Apr 2026 08:57:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2693758</guid>
    </item>
    <item>
      <title>Understanding the Workload of Remote Truck Operators with Discrete Event Simulation</title>
      <link>https://trid.trb.org/View/2675682</link>
      <description><![CDATA[This study employs a discrete event simulation (DES) model to understand the dynamic workload of remote truck operators managing partially-automated trucks. The DES model uses operator queues and event generators simulating automated truck events and leverages data from the California DMV’s disengagement database and driving simulation experiments. Disengagement data were partitioned into three groups by disengagement frequency: low, moderate, and high and separate arrival time distributions were developed for each group. Simulations from the model suggest that for companies with low disengagement rates, operator utilization will likely remain below minimal thresholds to prevent boredom. In contrast, companies with moderate or high disengagement rates both exceed operator utilization capacity and generate prolonged wait times as more trucks are controlled. These findings suggest that calibrating remote truck control to human capabilities will be challenging. A sensitivity analysis suggests that accurately estimating disengagement rates will be crucial for model accuracy and predictive performance.]]></description>
      <pubDate>Wed, 25 Mar 2026 11:44:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2675682</guid>
    </item>
    <item>
      <title>Stress-testing road network resilience using counterfactual flood events (1953–2024) in Great Britain</title>
      <link>https://trid.trb.org/View/2681318</link>
      <description><![CDATA[Road infrastructure is facing increasing flooding risks, causing asset damage and disrupting traffic flows. Effective risk management requires integrated assessments that capture network vulnerability, disruption and recovery. While localised studies have simulated traffic disruptions, national-scale assessments have largely focused on flood exposure rather than systemic disruption analysis. We developed a modelling framework combining process-based flow model of passenger travel-to-work flows and applied it to stress-test Great Britain’s road networks against 17 historical flood events from 1953 to 2024. Results reveal significant variations between direct and indirect damage losses, with single carriageway A roads and suburban bridges emerging as critical points. Notably, indirect losses due to disruption and rerouting can be significantly higher than direct damages depending on hazard event. Early clearance and speed restriction removal are key to mitigating the overall indirect impacts. The model is generalisable and can be applied to stress-test other road networks and flood scenarios worldwide.]]></description>
      <pubDate>Wed, 25 Mar 2026 11:44:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681318</guid>
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