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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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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Studies of Driver Behavior and Vehicle Performance by United States Public Roads Administration</title>
      <link>https://trid.trb.org/View/2742162</link>
      <description><![CDATA[During the past two years the Public Roads Administration of the Federal Works Agency has designed and constructed special instruments and equipment necessary in connection with studies of driver behavior and vehicle performance. These instruments are now being used in research work being carried on by the Public Roads Administration in cooperation with a number of State highway departments, the Quartermaster Corps of the United States Army at Camp Holabird, Baltimore, Maryland, the National Bureau of Standards, Johns Hopkins University and a number of motor truck manufacturers. The special instruments and equipment were demonstrated at Baltimore, Maryland, on October 26 and 27 before some of the executives of the motor truck industry, safety organizations and governmental agencies and departments primarily for the purpose of acquainting them with the techniques employed in the driver behavior and vehicle performance studies. Upon completion of the demonstration, Professor J. Trueman Thompson, research specialist for the Public Roads Administration and Professor of Civil Engineering at Johns Hopkins University, presented the paper that is included in this report summarizing the uses and implications of the equipment and data.]]></description>
      <pubDate>Mon, 31 Aug 2026 11:07:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742162</guid>
    </item>
    <item>
      <title>Preliminary Evaluation of an Improved Flammability Test Method for Aircraft Materials</title>
      <link>https://trid.trb.org/View/2742163</link>
      <description><![CDATA[Small-scale flammability test methods were evaluated by comparing data obtained on a series of interior honeycomb panels with fire test results obtained with a 1/4-scale cabin model. Generally, the vertical Bunsen burner, limiting oxygen index and radiant panel test methods ranked the phenolic-faced panels higher (better performance) than the epoxy-faced panels. It appears as if these test methods, which employ relatively moderate exposure conditions, are reflecting the superior ignition resistance of the phenolics over the epoxies. Thus, these tests cannot predict the performance of materials that exhibit high burning rates when subjected to heating conditions above their ignition threshold. The heating conditions used in the Ohio State University (OSU) apparatus, however, can be set at higher levels. At 5 watts/cm², rank ordering materials based on peak heat release rate measured via oxygen depletion in the OSU apparatus agreed with materials ranking in the 1/4-scale model. Based on the scope of this investigation, the OSU apparatus operated at these conditions and employing oxygen depletion calorimetry is the recommended improved fire test method for interior panels.]]></description>
      <pubDate>Mon, 31 Aug 2026 11:07:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742163</guid>
    </item>
    <item>
      <title> Evaluate the Implementation of Hot Mix Asphalt Thick-Lift Paving</title>
      <link>https://trid.trb.org/View/2772116</link>
      <description><![CDATA[The research team will explore the feasibility and benefits of using thick lift hot mix asphalt (HMA) paving to improve the efficiency of Texas Department of Transportation's (TxDOT’s) construction operations. Researchers will also explore if standard vibratory pavers can produce thick lifts that meet current quality and ride specifications and identify the best practices for durable, smooth pavements.]]></description>
      <pubDate>Fri, 28 Aug 2026 17:25:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2772116</guid>
    </item>
    <item>
      <title>Application of the multimodal model for predicting rock mechanical parameters via MWD feature splicing and fusion</title>
      <link>https://trid.trb.org/View/2697216</link>
      <description><![CDATA[The real-time acquisition of rock mechanical parameters is a critical challenge in intelligent tunnel construction, particularly in deep-buried and geologically complex environments where conventional laboratory testing methods are inherently time-consuming, costly, and incapable of providing real-time feedback during drilling. This temporal disconnect between excavation and parameter characterization poses significant risks to construction safety and support design optimization. To address this limitation, this study aims to develop a multimodal predictive framework that integrates MWD data with tunnel face imagery to enable real-time, in-situ estimation of five key rock mechanical parameters, including c, v, E, φ, and Rc. The proposed CNN-XL model employs a convolutional neural network for hierarchical feature extraction from tunnel face images, combined with a dual-stage stacking ensemble of XGBoost and LightGBM optimized by the Exponential-Trigonometric Optimization (ETO) algorithm. A comprehensive dataset comprising 69,391 boreholes from the Qixingping Tunnel in Sichuan, China, was collected and processed using mean, root mean square, and median statistics to construct 12 MWD input indicators. The results demonstrate that the CNN-XL model achieves exceptional predictive accuracy, with R² values of 0.942, 0.933, 0.989, 0.921, and 0.945 for c, v, E, φ, and Rc, respectively. The inclusion of image features improves R² by 5.7–6.8% compared to using MWD data alone, with the largest gain observed for Young’s modulus (+6.8%). SHAP-based interpretability elucidates feed pressure PtAve and rotation pressure-derived features (PrMed, PrRMS) as dominant contributors, highlighting their nonlinear and interactive effects. The synergistic integration of multimodal data fusion, ensemble learning optimization, and model interpretability constitutes a foundational contribution, enabling real-time geotechnical characterization, adaptive support selection, and stability analysis, while laying the groundwork for digital twin–enabled autonomous construction in complex geological settings. While the model demonstrates high accuracy, its current site‑specific nature calls for future transferability studies across different geological settings. Nevertheless, this integrated evaluation framework provides accurate parameter estimation and valuable guidance for tunnel excavation design and support selection, filling the existing gap in while‑drilling prediction of multiple rock mechanical parameters in complex geological environments.]]></description>
      <pubDate>Fri, 28 Aug 2026 08:35:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697216</guid>
    </item>
    <item>
      <title>Correlation of Laboratory-Scale Fire Test Methods for Seat Blocking Layer Materials With Large-Scale Test Results</title>
      <link>https://trid.trb.org/View/2732482</link>
      <description><![CDATA[An interlaboratory study was conducted to determine the adaptability of various laboratory fire test devices to measure aircraft seat cushion blocking layer effectiveness. Full-scale tests conducted by the Federal Aviation Administration (FAA) have shown blocking layers to be an effective means of delaying aircraft seat cushion fire involvement when exposed to a large external fuel fire. Large-scale tests conducted in the Douglas Aircraft Company Cabin Fire Simulator (CFS) have also shown similar findings. Such findings are fostering development of new candidate materials. However, it is more practical to evaluate these materials in a suitable laboratory test device rather than continuously performing expensive full- or large-scale tests. Several such devices were determined to be satisfactory when operated under specific conditions and when certain parameters are measured. The satisfactory devices are the Ohio State University (OSU) Rate of Heat Release Apparatus operated at 5.0 Watts centimeter squared, the FAA Standard Two Gallon Hour Burner operated for a two minute exposure, and the Lockheed Aircraft Company Meeker Burner. For a series of blocking layer material candidates, test measurements obtained with the above devices exhibit comparable rankings with weight loss or percent weight loss from larger scale CFS tests.]]></description>
      <pubDate>Sat, 22 Aug 2026 12:31:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732482</guid>
    </item>
    <item>
      <title>Integrating Paver-Mounted Thermal Profiling and Dielectric Profiling as Process Control Tools for Asphalt Pavement Construction</title>
      <link>https://trid.trb.org/View/2762073</link>
      <description><![CDATA[In-place density and uniformity are crucial for asphalt pavement performance. Even minor low-density areas can cause distress, despite overall compliance with specifications. Traditional quality-control methods, such as coring and nuclear gauge testing, often fail to capture the variability across the pavement mat. To overcome these limitations, this study explores the combined use of the paver-mounted thermal profiler (PMTP) and the dielectric profiling system (DPS) as continuous process control tools. The data for this research were collected from six national demonstration projects conducted by the Mobile Asphalt Technology Center (MATC), representing a range of climates, mixtures, and paving conditions. The PMTP was used during placement to develop thermal maps of mat temperature, while the DPS was employed after compaction to generate continuous dielectric profiles. Calibration of the DPS using gyratory-compacted specimens showed strong correlations with density (R² = 0.97–0.99), an improvement over calibration based on narrow-banded roadway cores. When validated against roadway cores, the DPS predictions had root mean square errors of 0.6%–1.5%, with mean bias generally within ±1%, and most projects showed moderate to strong correlation (R² = 0.65–0.92). PMTP data indicated thermal anomalies, but temperature alone cannot account for all density variability. Case studies show that combining PMTP, DPS, and a few core samples can identify localized risk zones and give contractors actionable feedback. Continuous profiling can eliminate low-density areas associated with spot testing, enhance quality control, and support specifications that account for both density and uniformity across the mat.]]></description>
      <pubDate>Thu, 20 Aug 2026 09:54:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2762073</guid>
    </item>
    <item>
      <title>Research on Characterization Parameters of Main Bearing Wear
          Condition Based on Vibration Signals</title>
      <link>https://trid.trb.org/View/2761796</link>
      <description><![CDATA[This study aims to investigate the influence of torque, rotational speed,                     lubricating oil temperature, and main bearing clearance on the vibration signals                     of diesel engine block surfaces, thereby establishing a foundation for                     diagnosing abnormal main bearing wear conditions using engine block surface                     vibration signals. An experimental test bench was constructed for a six-cylinder                     diesel engine to collect vibration signals under varying rotational speeds,                     torques, lubricant temperatures, and main bearing clearances. Frequency domain                     analysis and wavelet packet decomposition were then performed. The frequency                     domain analysis results indicate that the vibration signal amplitudes associated                     with abnormal main bearing wear are primarily concentrated below 5 kHz.                     Specifically, the energy in frequency bands below 1 kHz and around 2.5 kHz tends                     to increase with higher rotational speed, torque, and main bearing clearance,                     while the overall frequency domain amplitudes decrease with rising lubricant                     temperature. The wavelet packet decomposition results reveal that the energy in                     most decomposed frequency bands exhibits a positive correlation with rotational                     speed, torque, and main bearing clearance, but a negative correlation with                     lubricant temperature. Notably, the energy in wavelet packet bands 1–5 is                     significantly affected by rotational speed, bands 1, 3, 4, and 5 are notably                     influenced by torque, and bands 1 and 2 are strongly affected by main bearing                     clearance. The findings of this study provide a theoretical foundation and data                     support for the identification of abnormal wear states in the crankshaft–main                     bearing system.]]></description>
      <pubDate>Wed, 19 Aug 2026 13:49:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761796</guid>
    </item>
    <item>
      <title>Scalable and Modular Data-Driven Hybrid Chassis Dynamometer Framework for EV Powertrain Evaluation</title>
      <link>https://trid.trb.org/View/2761829</link>
      <description><![CDATA[In its conventional form, dynamometers typically provide a fixed architecture for measuring torque, speed, and power, with their scope primarily centered on these parameters and only limited emphasis on capturing aggregated real-time performance factors such as battery load and energy flow across the diverse range of emerging electric vehicle (EV) powertrain architectures. The objective of this work is to develop a valid, appropriate, scalable modular test framework that combines a real-time virtual twin of a compact physical dynamometer with world leading real-time mechanical and energy parameters/attributes useful for its virtual validation, as well as the evaluation of other unknown parameters that respectively span iterations of hybrid and electric vehicle configurations, ultimately allowing the assessment of multiple chassis without having to modify the physical testing facility's test bench. This integration enables a blended approach, using a live data source for now, providing a point of calibration and validation for the virtual model(s), as well as using the virtual model capability to determine other unknown/measurable characteristics about the physical model. So, this test framework makes that system's capability, representing an enhancement to its ability, with a virtual twin merging them together to enable virtual evaluation of multiple configurations of the chassis without changing the physical test stand. So, this combined real-world and virtual framework offers a scalable and flexible testing and modelling platform for both early performance characterisation, as well as life cycle-based energy evaluations. In responding to the identified gaps, this work introduces an innovative hybrid chassis dynamometer framework that applies to a real-world test bench in tandem with a concurrently simulated virtual model, offering early-stage validation and optimisation potential using the shift-left development proposition. The result is a reusable and forward-thinking platform supporting efficient EV development by forecasting and drawing informed insights into energy flow, battery performance, and lifecycle behaviour from ahead of typical physical testing boundaries.]]></description>
      <pubDate>Wed, 19 Aug 2026 13:48:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761829</guid>
    </item>
    <item>
      <title>Strength and Rotor Dynamic Simulation Analysis of a Brake Testing Device</title>
      <link>https://trid.trb.org/View/2761664</link>
      <description><![CDATA[The brake test bench is an effective method for studying wheel-rail interaction by simulating the braking process of rail vehicles. To ensure the safe and reliable operation of the brake test bench, this article focuses on introducing a comprehensive single-wheel brake test device. A finite element model of the wheelset assembly and test bench was established, and the strength, mode, and dynamic performance of the wheelset assembly and braking system were analyzed by simulating the braking process. The analysis results indicate that the wheelset assembly and braking system meet the strength requirements of the braking test process, and the test speed is maintained below the critical speed of the test bench. This validates the rationality and safety of the brake testing device and provides a foundation for subsequent brake research.]]></description>
      <pubDate>Wed, 19 Aug 2026 10:54:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761664</guid>
    </item>
    <item>
      <title>Modeling Method of Aircraft Hydraulic Pipeline Cleaning Test Equipment Based on MBSE</title>
      <link>https://trid.trb.org/View/2761647</link>
      <description><![CDATA[With the continuous improvement of performance requirements for aviation equipment, the importance and complexity of hydraulic systems as the core carrier of flight control are becoming increasingly prominent. The cleanliness of aircraft hydraulic pipelines directly affects the reliability and flight safety of hydraulic systems, and it is necessary to use specialized cleaning and testing equipment during design and manufacturing to achieve efficient cleaning. The design of traditional cleaning equipment relies on experience-driven development, with mechanical, hydraulic, and electrical systems developed independently. There are problems such as unclear requirement definitions, low efficiency of interdisciplinary collaboration, and lagging validation, making it difficult to achieve the goal of forward design. Therefore, this study introduces Model-based Systems Engineering (MBSE) method in the development process of pipeline cleaning test equipment, proposes a modeling process based on RFLP (Requirements-Function-Logical-Physical), and uses SysML system modeling language to construct a top down design model system for aircraft hydraulic pipeline cleaning equipment. Through requirement analysis modeling, functional behavior definition, and system architecture design, the significant advantages of MBSE method in the development of complex aviation test equipment have been verified, effectively improving the bold design capability and top down design efficiency. MBSE method can not only improve the design efficiency of equipment, but also promote the intelligent and efficient operation of equipment, which has important significance for the development of intelligent manufacturing and electromechanical integration technology.]]></description>
      <pubDate>Wed, 19 Aug 2026 10:54:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761647</guid>
    </item>
    <item>
      <title>Pneumatic-structural coupled response of flexible ventilated skirts for air-cushion vehicles under wave-induced heave excitation</title>
      <link>https://trid.trb.org/View/2737402</link>
      <description><![CDATA[To investigate the dynamic performance of flexible skirts in air cushion vehicles (ACVs) under realistic venting conditions and wave-induced heave disturbances, a numerical model of a skirt finger based on a pneumatic equilibrium mechanism is developed. The wave excitation is represented by the periodic oscillation of a rigid plate. A multi-parameter sensitivity study is conducted to examine the influence of key design and operating parameters—including heave amplitude, period, inflator flow rate, orifice number, and skirt elastic modulus—on air-chamber pressure and skirt motion. Results indicate that heave amplitude and period dominate the magnitude of pressure fluctuations and frequency, while orifice number primarily governs the pressure differential between the airbag and cushion. Inflator flow rate and material modulus mainly affect the steady-state formation of air chambers, with limited influence on transient dynamics. For skirt motion, heave amplitude and period strongly affect displacements at key locations of the skirt, whereas orifice number adjusts the response amplitude and frequency near the airbag front and fingertip. The proposed modeling approach reliably captures skirt-cushion coupling under typical sea states and offers a practical tool for skirt system performance evaluation and parameter optimization.]]></description>
      <pubDate>Mon, 10 Aug 2026 15:03:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2737402</guid>
    </item>
    <item>
      <title>An oblique impact test rig for next-generation European bicycle helmet testing standard</title>
      <link>https://trid.trb.org/View/2752024</link>
      <description><![CDATA[This project has developed a highly repeatable oblique impact test rigaligned with the forthcoming European standards. The infrastructure incorporates the new EN 17950 headform, which, in comparison to the Hybrid III counterparts, possesses high biofidelity (in terms of friction of coefficient and moment of inertia) to ensure an accurate physical interaction between the human head and the helmet liner during an impact. To guarantee realistic tribological behaviour, the headform's surface coefficient of friction was rigorously calibrated and verified using a standardized Capstan-based methodology. Utilizing this advanced platform, an empirical evaluation of eight representative bicycle helmets available on the Swedish market was conducted. The selected cohort deliberately encompassed diverse price points and integrated rotational protection technologies. The testing matrix subjected the helmets to oblique impacts against a 45° angled anvil at four specific cranial locations (termed as pXR, pYR, nYR, and pZR) and two initial velocities (6.0 m/s and 7.6 m/s). Impact kinematics were recorded using an embedded 6-degree-of-freedom wireless sensor system. To bridge the gap between external kinematics and internal injury risk, high-fidelity finite element analysis was employed to evaluate tissue-level responses during helmeted impacts, specifically quantifying the maximum principal strain within the brain. The eleven experimental kinematics-based injury metrics and maximum principal strain of the brain are highly dependent on the initial impact velocity and the specific impact location. As anticipated, increasing the impact velocity from 6.0 m/s to 7.6 m/s consistently increased the values of all linear, rotational, and combined injury metrics. The simulations revealed a distinct stratification in protective performance: helmets equipped with rotational protection systems consistently attenuated peak maximum principal strain more effectively than conventional designs across all tested configurations. This project not only resolves a national deficit in safety testing infrastructure but also establishes a robust empirical framework to guide consumer choices, inform future European standardization, and incentivize the helmet industry toward continuous technical advancement, thereby reinforcing Sweden's leading position in traffic injury prevention.]]></description>
      <pubDate>Fri, 07 Aug 2026 08:35:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2752024</guid>
    </item>
    <item>
      <title>Research on Reliability Test Methods for Electric Drive Axle
                    Differentials</title>
      <link>https://trid.trb.org/View/2742652</link>
      <description><![CDATA[With the rapid development of the global economy, issues such as the energy                     crisis and environmental pollution have become increasingly severe. Owing to                     their environmental friendliness, structural simplicity, and high energy                     efficiency, electric vehicles have attracted widespread attention. Electric                     drive technology serves as the most promising and versatile propulsion solution                     for battery electric vehicles, hybrid electric vehicles, and fuel cell vehicles.                     As an advanced mechatronic transmission system, the electric drive axle offers                     high transmission efficiency, flexible packaging, and ease of digital and active                     chassis control integration, and has thus been increasingly adopted in modern                     vehicle architectures. The differential is a key component within the electric                     drive axle, responsible for regulating the rotational speed difference between                     the left and right wheels and ensuring balanced torque distribution. It plays a                     decisive role in vehicle stability and traction performance. This study focuses                     on the reliability testing methodology for differentials in electric drive                     axles, primarily including the extraction of reliability test conditions and the                     feasibility analysis of the proposed testing scheme. Specifically, based on the                     parameters of a given electric vehicle, a Simulink model of the motor and                     differential is established, and a complete four-wheel-drive vehicle model is                     constructed. Through simulation under typical driving conditions, operational                     data of the rear-drive axle differential are obtained. The collected data are                     then preprocessed and subjected to dimensionality reduction using Principal                     Component Analysis. The selected principal components are further analyzed using                     K-means clustering to construct representative differential reliability test                     conditions. The limitations of existing testing methods are analyzed based on                     the simulated results and relevant literature. Finally, a reinforced fatigue                     testing method for the differential is designed according to the extracted test                     conditions, and the feasibility of the corresponding test bench is                     evaluated.]]></description>
      <pubDate>Mon, 03 Aug 2026 15:43:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742652</guid>
    </item>
    <item>
      <title>Analysis, Design, and Demonstration for Rotation-Type Experimental System of Dynamic Wireless Power Transfer</title>
      <link>https://trid.trb.org/View/2685803</link>
      <description><![CDATA[Experiments on dynamic wireless power transfer (DWPT) for electric vehicles (EVs) typically require vast testing grounds and significant costs, making them difficult to implement. As a solution, experimental systems utilizing rotational motion for DWPT have been proposed. However, few such systems have been developed and their design methods and fundamental characteristics remain unclear. This paper presents the construction of a rotation-type experimental system for DWPT and discusses its design methodology and basic characteristics. In developing the prototype, mechanical stability was verified through simulations analyzing stress and critical rotational speed of the rotating components. A sector-shaped transmitter coil, suitable for this system, was designed and analyzed using electromagnetic field simulations, confirming similar characteristics to conventional linear-rail-based systems. Furthermore, the effects of misalignment between transmitter and receiver coils and the electrical characteristics of slip rings and brushes were evaluated. Finally, power transfer characteristics were validated through experiments at a linear velocity equivalent of 40 km/h and 3.3 kW power transfer.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685803</guid>
    </item>
    <item>
      <title>Path-following algorithm for hovercraft considering safe navigation</title>
      <link>https://trid.trb.org/View/2721058</link>
      <description><![CDATA[In order to solve dangerous driving situations such as rollover and tail shaking that are prone to occur during the navigation of air cushion vehicles, a path-following control method for hovercraft that considers safe navigation was proposed in this paper. This paper adopts model predictive control as the path-tracking control method, generating optimal control commands by solving rolling optimization problems. This approach can handle multiple system constraints and predict future states. To ensure safe navigation in complex environments, further improvements are made upon this foundation. Firstly, the selection method of the target point of the reference path was modified, and the selection of the target point is proportional to the speed, so that the performance of the hovercraft is released to a greater extent; Then, the artificial potential field method was introduced to design the obstacle avoidance navigation function and the safety limit function was introduced to ensure the navigation safety of the hovercraft; Moreover, the path following was extended to contour tracking. Considering the distribution of obstacles, the asymmetric dynamic constraint corridor was designed to realize the intelligent adjustment of the constraint boundary and ensure the safety and stability of the hovercraft in the process of high-speed movement. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments.]]></description>
      <pubDate>Mon, 27 Jul 2026 09:46:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2721058</guid>
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