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    <title>Transport Research International Documentation (TRID)</title>
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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>Performance-Based Structural-Fire Engineering Analysis Approaches for Highway Bridges</title>
      <link>https://trid.trb.org/View/2694515</link>
      <description><![CDATA[This report is the second part of a two-phase study to assemble performance-based design guidance for the evaluation and mitigation of severe fire hazards for highway bridges. The following are addressed: (1) summarize design-basis tools that can be used for “engineering analysis” per NFPA 502 Chapter 6 to calculate the thermo-structural impact of design-basis fires on a particular bridge; (2) summarize approaches for evaluating common thermo-structural limit states of steel and prestressed girders as well as other common structural elements in bridge structures under fire; and (3) review fire mitigation strategies and recommend needs for future research. Thermal and structural finite element (FE) analysis is demonstrated as an effective tool for evaluating both steel and concrete bridge elements under fire exposure. Simpler lumped mass methods of thermal analysis are appropriate for steel materials, which have relatively high thermal conductivity and can therefore be approximated as having a relatively uniform temperature increase over their cross- section, which has a large ratio of exposed area to thermal mass. For other materials with lower thermal conductivity like concrete, a significant internal thermal gradient will develop under fire exposure, thus making lumped mass methods ineffective. More research is needed to develop simplified calculation tools to evaluate concrete bridge elements under fire.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694515</guid>
    </item>
    <item>
      <title>Thermal Management of Double-side Cooled SiC MOSFET Power Modules for Lifetime Enhancement of Automotive Applications</title>
      <link>https://trid.trb.org/View/2580030</link>
      <description><![CDATA[The rise of electric vehicles (EVs), driven by environmental concerns and increasing consumer demand, presents challenges such as reducing charging times, extending range, and ensuring reliability. Innovations in power electronics provide solutions for faster charging and enhanced efficiency but generate more heat in smaller volumes, necessitating efficient thermal management. This study investigates various cold plate designs for double-side cooled (DSC) SiC MOSFET power modules in high-power EV traction inverters. The performance of these designs is evaluated through lifetime assessments and thermal analyses, employing Computational Fluid Dynamics (CFD) simulations across a range of conditions.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:55:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580030</guid>
    </item>
    <item>
      <title>Thermal analysis and efficiency optimization of diesel- stirling combined cycle with CI engine exhaust heat recovery</title>
      <link>https://trid.trb.org/View/2685063</link>
      <description><![CDATA[Nowadays, because of their widespread applications in thermal efficiency enhancement, combined power cycles have attracted the attention and interest of the researchers. This research is devoted to provide a comprehensive modeling and thermal analysis of a new arrangement of combined cycle based on a compression ignition (CI) engine and α-type Stirling engine. Furthermore, the influences of the diesel exhaust gas temperature and Stirling working pressure on Stirling and combined engines power and efficiency are examined considering various scenarios. The Stirling engine cycle is combined with a CI engine cycle to recover the CI engine exhaust gas waste heat. OM355 experimental results have been considered for generated power, thermal balance and exhaust gas temperature analysis. According to thermal analysis and the obtained results, it is revealed that about 34% of input energy wastes by the exhaust gas. The simulation of α-type Stirling engine is also performed and the Solo V161 experimental results were employed for validation. Furthermore, Stirling engine heater is suggested for installation on the exhaust pipe in order to analyze the new proposed combined cycle properties. Thermodynamic analysis of combined cycle is implemented and thermal efficiency and net power are obtained for Stirling engine, diesel engine and combined cycle for various Stirling engine and diesel exhaust temperatures. The results indicate that, by installing a Stirling engine heater on the exhaust pipe of the CI engine, about 9.3 kW of the wasted heat could be recovered. Compared to the ordinary engine, coupled engines heat balance reveals higher thermal efficiency and combined cycle power which increase by 7.3% and 5.6%, respectively.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:30:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685063</guid>
    </item>
    <item>
      <title>Characterization of a Low-Cost Insulator Substrate for Traction Power Modules</title>
      <link>https://trid.trb.org/View/2691899</link>
      <description><![CDATA[Demand for cost-effective automotive traction inverters requires improved power module packaging. This paper presents a packaging method using an epoxy composite insulator applied directly to the cold plate surface, replacing Direct Bonded Copper (DBC) and Active Metal Brazed (AMB) substrates. This integration removes the substrate-to-cold plate solder interface and eliminates two material layers from the thermal path. The epoxy composite demonstrates a dielectric strength greater than 60 kV/mm. Thermal resistance (junction-to-coolant) measured approximately 0.17 K∙cm2/W. Electrical characterization showed a relative permittivity of 3.9, which is lower than standard ceramics and results in reduced parasitic capacitance. Initial thermal cycling tests indicated no significant degradation in thermal or electrical performance. These results suggest the epoxy composite insulator could be a promising alternative for traction power modules.]]></description>
      <pubDate>Tue, 14 Apr 2026 15:11:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691899</guid>
    </item>
    <item>
      <title>Research on State of Charge Estimation Method for Lithium Iron Phosphate Batteries Based on Expansion Force</title>
      <link>https://trid.trb.org/View/2675987</link>
      <description><![CDATA[To enhance the accuracy and robustness of State of Charge (SOC) estimation for lithium iron phosphate (LiFePO₄) batteries and to overcome the limitations of traditional electrical signal-based methods—such as cumulative errors in Coulomb counting and the need for rest periods in open-circuit voltage (OCV) methods—this study proposes a novel SOC fusion estimation algorithm based on mechanical expansion force signals. Addressing the challenge of feature extraction, a model framework integrating the Sparrow Search Algorithm (SSA), Least Squares Support Vector Machine (LSSVM), and Adaptive Extended Kalman Filter (AEKF) is developed. The state equation is constructed via Coulomb counting, while SSA optimizes the LSSVM to establish an observation model centered on expansion force as the input. The AEKF is employed to achieve real-time, precise SOC prediction. Experimental validation under varying temperatures (25°C, 35°C) and dynamic driving cycles (FUDS, UDDS) demonstrate that this fusion algorithm significantly outperforms traditional electrical signal-based methods, with cumulative SOC estimation errors not exceeding 2.2%. The approach exhibits higher accuracy, improved environmental adaptability, and enhanced robustness. This research confirms the feasibility and effectiveness of using expansion force as a non-electrical quantity for SOC estimation, providing a new perspective for high-precision battery state assessment.]]></description>
      <pubDate>Thu, 26 Mar 2026 13:38:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2675987</guid>
    </item>
    <item>
      <title>Early Detection of Thermal Runaway with Advanced Diagnostics</title>
      <link>https://trid.trb.org/View/2658328</link>
      <description><![CDATA[In support of the National Highway Traffic Safety Administration's (NHTSA’s) vehicle safety mission, this report investigates the state-of-the-art in early detection of thermal runaway in lithium-ion (Li-ion) battery packs contained in electric vehicles (EVs). This work uses an open-architecture test-demonstration platform to aid in the characterization of four battery safety sensors that can be used for EVs. This report focuses on employing rapid electrochemical impedance spectroscopy (EIS), volatile organic compound (VOC) sensing, and hydrogen (H2) gas sensing technology to monitor cells and battery packs for signs of failure. Experimental results with individual cells and packs subjected to thermal or electrical abuse reveal that rapid EIS and VOC sensors provide earlier warning of thermal runaway compared to H2 sensors. Furthermore, it was demonstrated that the implementation of rapid EIS and VOC sensor monitoring enables the detection and prevention of thermal runaway. The study also delves into how these sensors respond based on cell chemistry (lithium nickel manganese oxide, lithium iron phosphate), capacity, and system engineering (heat transfer). Additionally, the report discusses the challenges with integrating sensor systems in large EV battery packs, including issues with signal-to-noise for impedance sensors or placement of VOC sensors in larger packs.]]></description>
      <pubDate>Mon, 02 Feb 2026 14:13:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658328</guid>
    </item>
    <item>
      <title>A physics and data co-driven initial temperature field reconstruction approach for real-time thermal analysis of concrete bridges</title>
      <link>https://trid.trb.org/View/2632535</link>
      <description><![CDATA[Substantial non-uniform temperature fields, induced by the combined effects of solar radiation, ambient air temperature, and convective heat transfer, can generate thermal loads exceeding the operational limits of concrete bridges, causing structural deformation or damage. Accurate temperature field prediction is crucial for assessing service conditions and providing early warnings of thermal-induced failures. However, conventional numerical simulations face significant challenges, including reliance on approximate boundary conditions, high computational costs, and limited accuracy due to the sparsity of measured data. Existing interpolation methods rarely incorporate physical constraints and are, therefore, less applicable to bridge engineering. To address these issues, a physics and data co-driven approach is proposed, coupling the ray-tracing algorithm with physics-informed neural networks to enhance both computational efficiency and prediction accuracy. Low-fidelity numerical pre-analysis and sparse high-fidelity measurements are integrated via transfer learning to reconstruct initial temperature fields with high precision, even under minimal data conditions. The reconstructed field subsequently serves as the initial condition for temperature prediction. Additionally, a level-of-detail multi-scale model based on the ray-tracing priority principle is introduced to enhance shadow effect analysis, significantly improving the efficiency of external heat flux calculation. Validation on the Huinan Bridge in Shanghai demonstrates a mean absolute error of 1.05°C, satisfying precision requirements for thermal load calculations. Compared to numerical simulations and data-driven simulations, substantially lower short-term prediction errors are achieved with only 18 initial-value inputs, while heat flux updating efficiency is accelerated by 26.3 %. This work provides an effective tool for real-time assessment of bridge service conditions.]]></description>
      <pubDate>Tue, 27 Jan 2026 09:19:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2632535</guid>
    </item>
    <item>
      <title>A Computational Tool for the Reliable Prediction of Pavement Performance based on Temperature Data</title>
      <link>https://trid.trb.org/View/2636111</link>
      <description><![CDATA[This study presents a computational tool for predicting pavement performance using long-term temperature data from thermocouple trees embedded in three flexible and two rigid pavement sections at the MnROAD facility. The research leverages spectral and probabilistic analyses to assess thermal behavior and its impact on pavement condition. Temperature measurements, supplemented by weather data, were processed to address missing data and artifacts using compressed sampling, ensuring a uniform 15-minute sampling interval. Spectral analysis techniques based on Fourier Transform and Wavelet Analysis with Generalized Harmonic Wavelets were used to model pavement layers as a cascade of filters, revealing the time-varying behavior of the filters' gain and phase shift, which indicates that they are sensitive to aging, moisture, and compaction. Wavelet analysis provided superior temporal resolution for detecting transient thermal phenomena. A probabilistic framework using Markov Chain Monte Carlo (MCMC) methods estimated thermal diffusivity coefficients, achieving residuals below 1.17 degree C and robust uncertainty quantification. The results highlight distinct thermal responses across pavement layers, with asphalt showing uniform behavior and base/subgrade layers exhibiting environmental sensitivity. Interfaces between layers displayed significant time-dependent changes, potentially linked to densification. Implemented as a modular Python package with Jupyter notebook examples, publicly available on GitHub, the tool offers a scalable solution for pavement monitoring. This research demonstrates that thermocouple-derived temperature data, when analyzed with advanced computational methods, provides reliable indicators of pavement degradation, supporting data-driven infrastructure management decisions.]]></description>
      <pubDate>Mon, 29 Dec 2025 09:33:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2636111</guid>
    </item>
    <item>
      <title>Thermal Effectiveness of a New Type of Air Convection Embankment to Preserve a Northern Airstrip near the Hudson Bay Coast, Canada</title>
      <link>https://trid.trb.org/View/2604121</link>
      <description><![CDATA[Since the 1990s, an obvious increase in mean annual air temperature has been recorded in Nunavik, Quebec. This has resulted in the degradation of permafrost, threatening the stability of airstrip infrastructure managed by Transport Quebec. The air convection embankment (ACE) on side slopes with additional crushed rocks on the natural ground provides one option to preserve permafrost around the toe of embankments where permafrost degradation usually first occurs. To test the combined thermal effectiveness, this protection technique was used at the Puvirnituq airstrip in Nunavik, Quebec, in the summer of 2009. Thermistor strings were installed under the ACE layer to monitor the annual variation of ground temperatures near the toe of the embankment. The measured data indicate cooling trends at the ACE layer/natural ground interface, and the rise of the permafrost ceiling was observed. A numerical model based on site-specific conditions was developed to reproduce subsurface thermal regime and evaluate long-term climate warming effects. The model was calibrated using ground temperature measurements collected between 2010 and 2015. Numerical results indicate that the new type of ACE produces thermal cooling benefits as well as shifts the worst degradation location away from the embankment toe. This study provides a new design option for the ACEs to preserve warming airstrip infrastructures, and this design should be considered for other airstrip infrastructures in Nunavik, Quebec.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604121</guid>
    </item>
    <item>
      <title>Machine Learning-Enhanced Electrical Circuit Model Parameterization for Battery Cells: Reducing Experimental Workload Through GITT Testing with Altair RapidMiner®</title>
      <link>https://trid.trb.org/View/2623952</link>
      <description><![CDATA[This study addresses the challenge of reducing the experimental workload involved in characterizing battery cell behavior as a function of state of charge and temperature. Galvanostatic Intermittent Titration Technique tests were carried out in a climate chamber across a wide temperature range, from -20 °C to 70 °C, with 10 °C intervals. The voltage and current response data collected from these tests were used to train several machine learning algorithms. The trained models could then be used to predict the cell voltage response every 5 °C from -15 °C to 55 °C. While the models were experimentally validated at 15 °C, 25 °C, and 35 °C, the predicted voltages across this range contribute to enhancing the characterization process. In particular, the inclusion of these predicted voltage profiles—combined with the experimental data collected every 10 °C from -20 °C to 70 °C—allows for the creation of more accurate lookup tables for the parameters of the equivalent circuit model. These parameters include the open circuit voltage, series resistance, and multiple resistor-capacitor pairs representing dynamic electrochemical behavior. This approach results in significantly improved parameter estimation compared to using only the original experimental dataset.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:05:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623952</guid>
    </item>
    <item>
      <title>Clarification of the Mechanism of Abnormal Combustion in Hydrogen Engines -Investigation of Abnormal Combustion Location by Visualization Measurement-</title>
      <link>https://trid.trb.org/View/2623941</link>
      <description><![CDATA[Hydrogen internal combustion engines present a promising path towards carbon neutrality, yet their development is challenged by abnormal combustion phenomena like backfire and pre-ignition. These phenomena limit engine torque and reduce component reliability. This study is aimed to elucidate the mechanisms behind these phenomena in hydrogen internal combustion engines. We utilized a multi-cylinder engine with optical access for direct high-speed imaging of in-cylinder processes to visualize backfire and pre-ignition. Initial analysis, combining visualization data with one-dimensional (1D) simulations, indicated that high temperatures of the ground electrode of the spark plug could be a key trigger factor for abnormal combustion. To investigate this hypothesis, the surface temperature of the ground electrode was measured under firing conditions using a two-color thermometry system. The measurements revealed that the electrode temperature exceeded the compressed gas temperature near Top Dead Center (TDC). This finding suggests the possibility of hot surface ignition initiated by heat transfer from the hot electrode surface to the hydrogen-air mixture prior to the spark event. To mitigate this, the ground electrode material was replaced with a material with higher thermal conductivity to improve heat dissipation. Subsequent tests on the multi-cylinder engine confirmed the effectiveness of this modification, and the spark plug with the high-conductivity ground electrode showed a significant reduction in pre-ignition frequency. These results establish that the ground electrode temperature is one of the factors contributing to abnormal combustion, particularly pre-ignition, in hydrogen engines. This study provides valuable insights into mitigating abnormal combustion in hydrogen internal combustion engines, advancing their development towards more reliable and efficient operation, and supporting the broader goal of carbon neutrality.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:05:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623941</guid>
    </item>
    <item>
      <title>Investigation on the vehicle-bridge dynamic interaction considering the vertical curvature of bridge and environmental thermal effects</title>
      <link>https://trid.trb.org/View/2617023</link>
      <description><![CDATA[River-crossing bridges often utilise curved design to account for the highway profile change, distribute traffic loads and manage water flow. The vehicle-curved bridge interaction (VBI) is complicated, especially combining with environmental thermal effects. These thermo-mechanical interactions differ substantially from those in straight bridges and warrant detailed study. In this study, a curved bridge is modeled as a Timoshenko beam (TB) with pinned supports at both ends. Governing equations are derived using the four-node isoparametric beam element and cubic polynomial shape function. The vehicle is modelled as a half-car model to account for its bouncing and pitching motions. Thermal effects are represented by a linear temperature gradient through the beam depth, which is converted into equivalent thermal loads. An analytical framework that superimposes moving vehicle loads and thermal loads within the coupled motion equations is developed. The dynamic response of the VBI system is analyzed using a zero-order displacement and velocity overshoot (U0-V0) iterative method. The parametric study reveals that: (1) the shear deformation significantly affects high vibration modes; (2) the bridge stiffness increases when the radius of its curvature reduces, which induces the reduction of bridge and vehicle displacement responses; (3) the thermal bending and expansion of the bridge have a large effect on dynamic amplification factor (DAF), while the impact of its curvature on dynamic load coefficient (DLC) becomes dominant for high vehicle speeds. These findings provide valuable insights for the design, analysis, and maintenance of curved bridges operating under combined vehicular and thermal loading conditions.]]></description>
      <pubDate>Mon, 22 Dec 2025 09:52:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617023</guid>
    </item>
    <item>
      <title>Concrete Works Version 2.0 Users Manual</title>
      <link>https://trid.trb.org/View/2583986</link>
      <description><![CDATA[The purpose of this manual is not to give an exhaustive compilation on all concrete thermal, durability and corrosion research in the literature. Instead, this manual is designed to give the user a working knowledge of concrete behavior needed to successfully use ConcreteWorks, built upon an already existing knowledge of fundamental concrete behavior. It is recommended that users carefully read this user manual before using the software, as well as cited references when necessary. ConcreteWorks is designed to be a user-friendly concrete mixture proportioning, thermal analysis, and chloride diffusion service life software package. The software package contains design modules for several mass concrete shapes, bridge deck types, precast concrete beams, and concrete pavements.]]></description>
      <pubDate>Mon, 01 Dec 2025 11:04:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2583986</guid>
    </item>
    <item>
      <title>In Situ Monitoring and Numerical Studies on the Performance of Gentle Slopes to Preserve the Transportation Infrastructure in Northern Canada</title>
      <link>https://trid.trb.org/View/2596411</link>
      <description><![CDATA[Permafrost degradation occurs underneath the side slope due to snow accumulation, which prevents heat from being extracted from the ground in winter. This paper presents the in situ snow dynamics and thermal behavior of an airstrip in an area of continuous permafrost, in Nunavik, Quebec, Canada. The dynamic change of snow thickness around the embankment toe was measured in the field during 2014–2015. Thermistor strings were installed under the side slope and around the toe of the embankment. An empirical relationship between snowpack thickness and the freezing 𝘯-factor was proposed. The ground temperature data collected were used to calibrate a thermal conduction model, which was then used to develop the design chart for gentle slopes. The design chart was further validated using data from another experimental site at Tasiujaq airstrip in Nunavik, Canada. This work enhances the design capacity of gentle slopes to stabilize thaw-sensitive permafrost beneath the embankment shoulder.]]></description>
      <pubDate>Fri, 21 Nov 2025 17:09:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2596411</guid>
    </item>
    <item>
      <title>Cool Pavement Evaluation: Sun Valley, Los Angeles</title>
      <link>https://trid.trb.org/View/2611283</link>
      <description><![CDATA[In recent years, the City of Los Angeles has been leading the efforts to combat Urban Heat. In particular, the City outlined a goal of reducing the urban-rural temperature differential by 3°F by 2035 (Sustainable City pLAn, 2015). To achieve this goal, the Bureau of Street Services (StreetsLA), initiated the installation of solar reflective 'Cool Pavements' across fifteen City Council Districts. The report draws upon three empirical research methods to examine the thermal comfort of the novel Cool Pavements Project in the Sun Valley neighborhood in Los Angeles. For this study, Sun Valley site was selected because the area received three different treatments of the Cool Pavements, and has a patch of regular asphalt pavement within the same neighborhood block.]]></description>
      <pubDate>Wed, 19 Nov 2025 09:26:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2611283</guid>
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