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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>
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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>Adaptive Health-Conscious Operation of PEMFC System for Hydrogen Locomotives in Plateau Environment</title>
      <link>https://trid.trb.org/View/2735078</link>
      <description><![CDATA[To decelerate the degradation of the proton exchange membrane fuel cell (PEMFC) system for hydrogen locomotives during long-term operation in plateau environments, this article proposes an adaptive health-conscious operation strategy. First, a degradation mechanism model based on membrane electrode assembly (MEA) decay is established to accurately simulate the degradation of the PEMFC system for hydrogen locomotives in a plateau environment. The electrochemical surface area (ECSA) and membrane thickness are then selected as the key degradation indices to extract the health state of the stack. Combined with the net power of the system, a comprehensive evaluation model is constructed to capture the tradeoff relationship between the state of health (SOH) and performance output. By analyzing the operation characteristics under different altitudes and load currents, an optimal health-conscious operation region is identified. A decoupling sliding mode control (SMC) approach based on a disturbance observer is designed to reliably track this optimal operation region. Comparative experiments on a hardware-in-the-loop (HIL) platform demonstrate that the proposed strategy effectively extends the service life while maintaining high net power output of the PEMFC system for hydrogen locomotives under plateau conditions.]]></description>
      <pubDate>Fri, 07 Aug 2026 09:21:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2735078</guid>
    </item>
    <item>
      <title>Optimizing Smart Wireless Charging and Data Acquisition for Uavs with Battery Life Prediction</title>
      <link>https://trid.trb.org/View/2731639</link>
      <description><![CDATA[As network technology advances rapidly, the use of unmanned aerial vehicles (UAVs) is rapidly growing across diverse applications, revealing unprecedented potential for widespread deployment. However, these UAVs often encounter the challenge of insufficient power during their missions. To overcome this problem, this study addresses mission interruption and energy wastage due to insufficient power by charging UAVs with a Charging UAV (CUAV). Traditional research in this area is mostly based on one key assumption: constant battery capacity. However, the battery capacity actually decreases gradually with the usage time, a fact that imposes constraints on the operational range and duration of UAVs. To address this issue, this paper proposes a wireless energy charging strategy for UAVs based on battery life prediction. The strategy first predicts the remaining lifetime of the UAV battery, and then based on this, a charging UAV is deployed to charge the UAV on mission to ensure that it can continue to fulfill its mission without having to return to the base station to recharge or replace the battery. This paper further explores a practical application scenario where multiple UAVs perform data collection from multiple sensor nodes, and these UAVs are charged by CUAVs. To achieve efficient task scheduling, this study proposes and implements a UAV scheduling algorithm based on Deep Reinforcement Learning (DRL). Through large-scale simulation evaluation, we demonstrate that the proposed scheme enables UAVs to explore and optimize the scheduling strategy more efficiently and exhibits significant advantages in system performance compared to traditional schemes when considering the battery life factor.]]></description>
      <pubDate>Fri, 31 Jul 2026 16:05:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731639</guid>
    </item>
    <item>
      <title>Improvement of End-of-Life Vehicle Chassis Number Reading Software Using AI-OCR</title>
      <link>https://trid.trb.org/View/2695920</link>
      <description><![CDATA[Starting in April 2026, a new regulation will require accurate management of parts removed from end-of-life vehicles (ELVs). This demands precise reading of vehicle identification numbers (VINs) and tracking of related part information. To address this, we developed VIN reading software, but its recognition accuracy was initially inadequate. In this study, we aimed to improve the software's accuracy. Through testing and analysis, we succeeded in enhancing recognition performance. Additionally, we identified new challenges, such as the impact of VIN plate design on reading accuracy, which must be considered in future improvements.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2695920</guid>
    </item>
    <item>
      <title>Hierarchical Attention Temporal Model with Degradation Mode-Aware Health Indicator Similarity Matching for Aeroengine Remaining Useful Life Prediction</title>
      <link>https://trid.trb.org/View/2698794</link>
      <description><![CDATA[Health indicator similarity matching(HISM)-based prognostic methods have achieved promising results in aeroengine remaining useful life (RUL) prediction, but they still face several limitations: 1) difficulty in constructing accurate HIs to effectively characterize aeroengine degradation because of insufficient consideration of long-term temporal dependencies in multidimensional time-series (MTS) data, particularly for aeroengines working under nonstationary conditions; and 2) neglect of the differences among degradation modes (DMs) within HISM, leading to mismatched HIs and inaccurate RUL predictions across diverse degradation scenarios. Accordingly, a novel hierarchical attention temporal model with DM-aware HISM framework (HATFormer) is proposed, which integrates spatiotemporal representation learning with DM-aware HISM (DMAHISM) strategy, to improve prognostic performance under complex DMs. First, a hierarchical attention-based spatiotemporal aggregation autoencoder is designed, which embeds multi-head self-attention into a specially designed time-series encoder-decoder to achieve spatial aggregation and temporal memory of MTS in an unsupervised manner, thereby enabling accurate HI extraction. Second, a novel DMAHISM strategy is designed, which decouples HISM into DM recognition and DM-specific HI matching, and performs RUL prediction by probability-weighted fusion of DM-specific predictions, significantly improving prediction accuracy and robustness. Finally, the effectiveness of HATFormer is validated by extensive comparative experiments on four aeroengine degradation datasets with diverse and complex DMs.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698794</guid>
    </item>
    <item>
      <title>Zero-Shot Cross-Domain Transfer for Remaining Useful Life Prediction of Aero-Engines via Iterative Diffusion Refinement</title>
      <link>https://trid.trb.org/View/2697544</link>
      <description><![CDATA[Accurate prediction of the Remaining Useful Life (RUL) of turbofan engines is critical for effective predictive maintenance. However, conventional models often struggle to generalize when sensor data distributions shift due to variations in operating profiles, environmental conditions, or system configurations. Existing unsupervised domain adaptation methods alleviate this issue by exploiting unlabeled target-domain data, but they still require additional data sampling. In this paper, we present RUL-DiT, a Diffusion Transformer architecture that combines Denoising Diffusion Probabilistic Models with a Transformer backbone and a novel LSTM-based conditioning network to iteratively refine RUL predictions via diffusion-based posterior denoising. At each reverse-diffusion step, RUL-DiT refines a Gaussian latent posterior whose mean and schedule-defined variance progressively concentrate the RUL estimate, enabling more faithful modeling of gradual degradation processes than conventional models. Crucially, when trained on a single subset of CMAPSS and N-CMAPSS, two established benchmark datasets for aircraft engine prognostics, RUL-DiT achieves strong performance relative to previously reported baselines on both datasets. Moreover, RUL-DiT enables zero-shot cross-domain transfer and achieves competitive performance across transfer tasks on several source-target pairs, without requiring any target-domain labels or fine-tuning. This source-only capability enables direct deployment on unseen subsets and engine operating conditions, substantially reducing data collection overhead for RUL prognostics.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697544</guid>
    </item>
    <item>
      <title>A review of the composition, regeneration mechanism, and performance of cold recycled asphalt mixture</title>
      <link>https://trid.trb.org/View/2714522</link>
      <description><![CDATA[This review aims to enhance the mechanical and road performance of cold recycled asphalt mixture, and advocate the application of cold recycling technology, which features lower energy consumption and reduced carbon emissions. The properties of composition materials were initially studied for cold recycled asphalt mixture, meanwhile which regeneration mechanism was subsequently revealed. Additionally, a summary of the impact of complex factors on the mechanical and road performance of cold regenerated mixtures was provided, along with a proposed method for optimizing their performance. This review summarizes the main challenges of current cold recycling technologies and discusses future research directions. From numerous studies, it is found that the composition of cold recycled asphalt mixture significantly impacts its performance. The gradation variability and dosage of reclaimed asphalt pavement (RAP) material are the main factors affecting the performance of cold recycled material. The bonding property of binder has a significant effect on the mechanical properties of the mixture. The cold regeneration mechanism of waste asphalt mixture includes the rejuvenation of aged asphalt, the bonding mechanism of binder and the enhancement impact of additives. There are many factors affecting the performance of cold reclaimed asphalt mixture. Currently, improvements in mechanical and road performance can primarily be achieved through three main avenues: controlling the quality of RAP material, modifying the binders, and incorporating high-performance additives. However, the cold recycled asphalt mixture still faces several challenges, including a low utilization rate of RAP and limited application structure layers. In addition, insufficient early strength delays the opening of traffic. In the future, it is still necessary to propose more reasonable and efficient approaches to optimize the performance of cold reclaimed asphalt mixture, diverging from traditional methods. Moreover, the intelligent monitoring, evaluation, and prediction of performance for cold recycled asphalt pavement is also highly essential.]]></description>
      <pubDate>Mon, 27 Jul 2026 09:46:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714522</guid>
    </item>
    <item>
      <title>Full-Scale Field Performance of Steel Wire Mesh Reinforced Unpaved Road</title>
      <link>https://trid.trb.org/View/2580998</link>
      <description><![CDATA[The present study investigates the efficiency of hexagonal steel-wire-mesh reinforcement in the granular layer of unpaved roads through a full-scale field test. Three-test sections were constructed in the widening portion of the Sahol-Kim state highway in Gujarat, India. The first test section was reinforced with geogrid. The second was reinforced with hexagonal steel wire mesh, and the third was left unreinforced for comparison purposes. The test sections were subjected to in situ light weight deflectometer (LWD) tests to determine the in situ elastic modulus. With the addition of geogrid and steel wire mesh in the base layer, the composite elastic modulus of pavement layers increased by factors of 1.10 and 1.32, respectively. Finite element analysis was conducted in PLAXIS 2D to obtain critical vertical compressive strain and service life ratio (SLR) values. A higher SLR value of 1.65 for steel-wire-mesh (SWM) reinforcement indicates its effectiveness in enhancing road durability and confirms its suitability in preventing rutting failure.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:49:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580998</guid>
    </item>
    <item>
      <title>The European Transport Network: Risks for Bridges and Tunnels</title>
      <link>https://trid.trb.org/View/2717341</link>
      <description><![CDATA[Transport infrastructure is vital for the European society and essential for a vibrant economy, territorial cohesion and social well-being. Many bridges and tunnels in the Trans-European Transport Network present structural deficiencies or are reaching the end of their design life. These problems are aggravated by reduced maintenance activities due to recurrent cuts in public budgets. Therefore, massive strategic investment is needed to complete missing links and to modernise transport infrastructure. This report presents a literature review on the structural and operational challenges facing bridges and tunnels in the Trans-European Transport Network with a focus on risks that may affect these structures. All components of risk assessment, i.e. hazard, exposure and vulnerability, are covered. The report addresses weather-related (floods, extreme heat, extreme precipitation, droughts, wildfires, high humidity, sea-level rise, heavy winds, extreme cold), geological (earthquakes, landslides, liquefaction), hydrological and fire risks, as well as the impact of climate change. It also includes a brief review of case studies and research projects on aspects of vulnerability and resilience of transport infrastructure in order to identify knowledge gaps. The work presented in this report will support future activities aiming to provide technical and scientific advice for the assessment of rail and road bridges and tunnels of the Trans-European Transport Network and in the prioritisation and planning of upgrading measures.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:48:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717341</guid>
    </item>
    <item>
      <title>Enhanced Understanding of Concrete Pavement Performance</title>
      <link>https://trid.trb.org/View/2731921</link>
      <description><![CDATA[Michigan’s wet-freeze climate causes pavement durability issues such as freeze-thaw scaling, while salt exposures
significantly impact the long-term performance of Jointed Plain Concrete Pavements (JPCP). These environmental stressors
initiate joint staining and can progress to joint spalling, eventually lead to structural failures like shear cracking under traffic
loads. Structural inputs like slab thickness and modulus of rupture govern mechanical performance, while durability factors
influence how a JPCP pavement degrades over time. These material properties affect roughness and service life. In addition,
the University of Michigan (UofM) Center can provide specialized technical expertise and examinations related to further development of its pavement
design program, specifically as it relates to Pavement Mechanistic-Empirical Design (PMED).]]></description>
      <pubDate>Fri, 17 Jul 2026 13:20:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731921</guid>
    </item>
    <item>
      <title>5G-Enabled Cyber-Physical Infrastructure for Intelligent Automotive Battery Management</title>
      <link>https://trid.trb.org/View/2717678</link>
      <description><![CDATA[This paper presents a prototype of an architecture of a cyber-physical system (CPS) for extending the lifetime of electric vehicle batteries. The proposed solution features a secure, AUTOSAR-compliant architecture with wireless connection designed to facilitate advanced optimization techniques for battery usage. Central to this architecture is the integration of a cloud-based complex Digital Twin - built upon high-precision behavioral models - and the deployment on the vehicle of corresponding simplified models for edge computing. This enables real-time estimation of battery status and optimal usage parameters locally, without relying on continuous cloud connectivity. To address performance degradation over time, the system incorporates a methodology for remote, wireless retraining of edge models using the cloud Digital Twin via 5G communication. The proposed solution has been fully implemented and validated in laboratory using a real battery yielding State-of-Charge (SoC) predictions with an error margin below 3.5%. Additionally, behavioral models were also developed for State-of-Health (SoH), Remaining Useful Life (RUL), State-of-Security (SoS) and State-of-Power (SoP). These models also provide, in a second iteration analysis, values for the maximum current to demand from the battery and the optimal operating temperature. Collectively, the proposed CPS architecture enables advanced battery management with a positive impact in the battery lifetime.]]></description>
      <pubDate>Wed, 15 Jul 2026 16:27:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717678</guid>
    </item>
    <item>
      <title>Effects of Diamond Grinding on Airfield Concrete Pavements</title>
      <link>https://trid.trb.org/View/2727280</link>
      <description><![CDATA[Diamond grinding involves the use of a series of diamond saw blades and spacers stacked together to cut a pavement surface to a shallow depth, giving it a “corduroy” appearance. It has been used for decades on civilian and military airfield concrete pavements to smooth surfaces, correct surface elevation, remediate surface distresses, increase friction, and ultimately extend service life. ACPTP-2022-6 site visits and stakeholder interviews revealed that diamond ground surfaces (ranging in age from less than 1 to greater than 30 years) have generally performed well, retaining texture and not generating foreign object debris (FOD). Some of these diamond ground surfaces are subjected to harsh winters with exposure to freeze-thaw cycles, snow removal equipment, and aircraft deicing chemicals. Worn texture was often evident in highly trafficked areas on runways (e.g., touchdown zone), especially in areas where high-pressure water blasting is used for rubber removal operations. Diamond ground surfaces older than approximately 15 years exhibited varying levels of texture loss in the mortar surrounding coarse aggregates. When done correctly, grinding is a viable treatment for airfield concrete pavements. It is most effective when performed on “good quality” concrete—pavements that are durable, structurally adequate, and have appropriate distress levels for grinding treatment. Special consideration should be given when grinding for surface distress remediation as there is increased risk of FOD (e.g., popouts) if aggregates are not adequately bonded to the paste. However, recurring FOD from diamond ground surfaces was not found to be a widespread concern for stakeholders and was only documented on a runway during one site visit, the cause being generally attributed to poor paste-aggregate bond. This guidebook covers all aspects of diamond grinding airfield concrete pavements, including planning, design, and construction, with detailed emphasis on proper applications and selecting candidate pavements with attributes favorable to successful grinding outcomes. Supporting information was gathered from a literature review, project records, stakeholder interviews, and site visits to 12 airports in the United States and one airport in Canada. Detailed case studies are provided to highlight diamond ground airfield concrete pavements.]]></description>
      <pubDate>Tue, 14 Jul 2026 09:29:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727280</guid>
    </item>
    <item>
      <title>Current Methods for Determining the Influence of Hydrogen in Metallic Materials and Their Limits</title>
      <link>https://trid.trb.org/View/2579347</link>
      <description><![CDATA[The selection of materials under the influence of hydrogen can be carried out using a variety of different testing and evaluation methods. The respective methods differ significantly in terms of their relevance to reality, informative value and technological and financial expenditure. In order to select a suitable method for material qualification and service life estimation for the respective application, a deeper understanding is required, as there is no scientific consensus on the existing damage mechanisms under the influence of compressed hydrogen and there are no internationally valid standards for the qualification of metallic materials for compressed hydrogen applications. The present work represents a literature study in which selected common methods for the qualification of metallic materials are taken up. Advantages and disadvantages are taken up and discussed on the basis of scientific work.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579347</guid>
    </item>
    <item>
      <title>Assessing Functional Performance of Asphalt Pavements under Data Sparsity: A Probabilistic-Deterministic Approach</title>
      <link>https://trid.trb.org/View/2724783</link>
      <description><![CDATA[Asphalt pavements, subjected to continuous traffic loads and environmental stressors, undergo deterioration processes that gradually compromise their structural and functional integrity. Pavement management systems (PMS) have been implemented to forecast deterioration and plan maintenance, but empirical models commonly used in PMS encounter limitations in data-scarce environments. To address this, a probabilistic-deterministic approach is proposed to evaluate the functional condition of in-service asphalt pavements. The international roughness index (IRI) was selected as a functional condition indicator. IRI measurement data were used for two modeling approaches: (i) a Markov chain-based probabilistic model for short-term IRI condition states and (ii) a deterministic model for long-term IRI prediction and remaining service life estimation. The probabilistic model categorizes the IRI into five condition states, while the deterministic model uses exponential regression with estimated pavement age as input. Results show that the Markov chain model effectively represents functional deterioration and provides short-term predictions without historical data. Analysis revealed a gradual decline in pavement condition with a corresponding rise in lower condition states across all functional classes. State roads exhibited an accelerated transition to lower states, highlighting the need for early interventions. A faster degradation rate was also observed once pavements declined to “fair” or “poor.” Validation confirmed that the short-term predictions were consistent with field observations, with absolute state proportion differences ranging from 0.0002 to 0.1116. The deterministic model demonstrated accurate IRI predictions, with R² ranging from 0.84 to 0.86. Consequently, integrating both models enables reliable condition evaluation and maintenance planning, regardless of historical data availability.]]></description>
      <pubDate>Mon, 13 Jul 2026 08:47:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724783</guid>
    </item>
    <item>
      <title>A New Methodological Framework for Bridge Deck Deterioration Modeling Based on National Bridge Element (NBE) Data</title>
      <link>https://trid.trb.org/View/2721765</link>
      <description><![CDATA[The National Bridge Element (NBE) dataset offers granular, quantitative condition data of bridge components; however, its potential for developing advanced deterioration models remains largely untapped. Current research often translate NBE condition states into coarser National Bridge Inventory (NBI) ratings, overlooking the rich information contained in the temporal changes in element quantities across condition states. This paper introduces a novel methodological framework that treats the transition of element quantities between condition states as the primary input for deterioration modeling. The core of this framework lies in constructing a survival data set directly from NBE element-level changes, where a “failure event” is defined as a partial quantity of an element transitioning to a worse condition. To bridge the gap between these localized, partial transitions and the overall deterioration of the entire bridge deck, an inverse probability weighted Cox proportional hazards model is used. This weighting scheme is designed to approximate the global survival characteristics of the deck based on observable local changes. As a proof-of-concept, this framework is applied to a sample set of concrete bridge deck data from the Long-Term Bridge Performance InfoBridge database under the simplifying assumption of no maintenance interventions to isolate natural deterioration. The results demonstrate feasibility of the proposed framework, showing that the IPW–Cox model can be effectively fitted and that the weighting approach systematically adjusts the survival probabilities, offering a more realistic representation of the overall deck’s lifespan compared with unweighted models. This paper establish a foundational paradigm rather than a definitive prediction tool.]]></description>
      <pubDate>Thu, 09 Jul 2026 14:05:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2721765</guid>
    </item>
    <item>
      <title>Chip Seal for Uniform Usages Across the Districts of NMDOT</title>
      <link>https://trid.trb.org/View/2720103</link>
      <description><![CDATA[Chip seals are a cost-effective pavement preservation treatment widely used by the New Mexico Department of Transportation (NMDOT) to extend pavement life and improve surface performance. Despite their extensive application, NMDOT has not previously adopted a standardized design procedure or construction specification, resulting in variability across districts. This research reviewed current practices, analyzed performance trends using Pavement Management System (PMS) data, and developed a formal design methodology tailored to New Mexico’s conditions. The Modified Kearby method, documented in AASHTO R 102-22, was selected as the most suitable design approach based on its practicality and compatibility with available resources. Laboratory testing of 13 aggregate sources, including reclaimed asphalt pavement (RAP), revealed significant variability in material properties and application rates, confirming the need for project-specific design. Validation through two field projects demonstrated strong agreement between laboratory-designed and field-applied rates, supporting adoption of the method. PMS analysis showed that chip seals generally perform well, with minimal bleeding and acceptable aggregate retention. Service lives average six to eight years, consistent with current practice. The study recommends adopting the Modified Kearby method, implementing statewide specifications, integrating PMS data into project selection, and constructing pilot test sections in each district during initial implementation. These measures will improve consistency, optimize material usage, and enhance long-term performance of chip seal treatments across New Mexico.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:05:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720103</guid>
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