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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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    <item>
      <title>Assessment of pavement–subgrade deformation in permafrost highways using UAV photogrammetry and ground-penetrating radar: Case study of Qinghai–Tibet highway</title>
      <link>https://trid.trb.org/View/2652492</link>
      <description><![CDATA[Permafrost-related deformation of highway embankments is a major constraint on the long-term serviceability of the Qinghai–Tibet Highway (QTH). Freeze–thaw cycles, water migration and heavy traffic loads produce rutting, corrugation and differential settlement at the surface, but their relationship to subsurface anomalies is not yet fully understood. This study combines unmanned aerial vehicle (UAV) photogrammetry with ground-penetrating radar (GPR) to examine coupled pavement–subgrade behaviour on three permafrost sections of the QTH. UAV-derived digital surface models are used to quantify rut depth, roughness and longitudinal/transverse elevation differentials, whereas 2D GPR profiles and depth-dependent reflection-intensity maps are interpreted to identify stratigraphic undulations, localised loosening and the position of the permafrost table. The joint analysis shows that sections with large elevation differentials and roughness systematically coincide with zones of strong GPR anomalies, and that the three sites exhibit contrasting deformation patterns ranging from severe settlement with rutting and cracking to pseudo-corrugations and localised depressions. Vertically continuous bands of anomalous reflections indicate that, in some cases, weaknesses extend from the active layer into the embankment body, providing a plausible link between subsurface degradation and surface distress under combined freeze–thaw and traffic loading. The case study suggests that integrating established UAV and GPR techniques offers a practical, non-destructive means of characterising pavement–subgrade deformation in permafrost highways and can inform the early identification of problematic sections and the planning of maintenance strategies.]]></description>
      <pubDate>Thu, 02 Apr 2026 16:58:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652492</guid>
    </item>
    <item>
      <title>An attention-enhanced deep learning model for detecting vessel anomalous behavior</title>
      <link>https://trid.trb.org/View/2623751</link>
      <description><![CDATA[Intelligent surveillance is critical for ensuring the safety and efficiency of maritime traffic, especially in busy waterways where the volume of vessel traffic presents substantial monitoring challenges. To effectively detect vessel anomalies and minimize potential risks, we propose a novel deep learning model called Seq2Seq-Attention for Vessel Anomalous Behavior Detection (SA-VABD). Specifically, the speed-aware Douglas-Peucker algorithm is employed to compress trajectory data to reduce data complexity and improve processing efficiency. This compression allows us to extract high-level attributes of vessel trajectories more effectively. Building on these attributes, we present a seq2seq-driven model designed to capture both static and dynamic characteristics of vessels. To further improve the model’s detection capability, an attention mechanism is embedded into the Seq2Seq network. This allows the model to focus on the critical features of vessel behavior. A series of comprehensive experiments were conducted, comparing our method against baseline approaches using realistic vessel trajectories extracted from Automatic Identification System (AIS) data. The experimental results demonstrate that the proposed detection method can identify anomalous vessel behavior with high precision and accuracy, significantly outperforming traditional methods.]]></description>
      <pubDate>Fri, 21 Nov 2025 08:44:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623751</guid>
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    <item>
      <title>In-Cycle Predictability and Control of Knock in a PFI HD SI Engine Fueled with Methanol</title>
      <link>https://trid.trb.org/View/2600403</link>
      <description><![CDATA[Knock is an anomalous combustion occurrence limiting the efficiency of the spark-ignited engine, hence increasing fuel consumption and emissions. The global aim to cut the emissions from green-house-gases therefore makes knocking combustion a very appropriate research topic of today. This paper explores the possibility to do in-cycle spark timing control of knock, based upon cycle-to-cycle adaptation of the temperature of a hypothesized hot spot. The potential for post-spark timing control is also examined. Experiments were carried out on a single cylinder port fuel injected spark ignited engine fueled with methanol. Knock was quantified by the Maximum Amplitude of Pressure Oscillations metric and predicted by the Livengood-Wu integral. Normalized distributions, together with different s confidences, of the in-cylinder state such as gas temperature, in-cylinder pressure and Livengood-Wu integral were computed both pre- and post-spark timing. Type I and Type II errors of the computed metrics revealed that knocking cycles cannot be distinguished from normal cycles, and that hot spots are likely not the root cause of auto-ignition in the current engine. Hence, in-cycle control of knock based upon a hypothesized hot spot temperature would be fruitless. A proven method to mitigate knock in-cycle is the use of water injection. Nevertheless, the post-spark timing analysis showed that this control post-spark timing may be counterproductive. The knocking and normal cycle combustions have a large overlap before the knocking occurs. Therefore, in-cycle regulation through water injection can penalize normal cycles, to a degree that the indicated thermal efficiency would drop more than just retarding the spark timing to 1% knocking (regular knock controller). Lubricant oil, instead of hot spots or fuel-rich spots, was demonstrated to be the most plausible cause of knock in the current engine-fuel configuration.]]></description>
      <pubDate>Tue, 16 Sep 2025 11:12:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2600403</guid>
    </item>
    <item>
      <title>Smartphone-based image analysis method for estimating moisture content in subgrade filling</title>
      <link>https://trid.trb.org/View/2570885</link>
      <description><![CDATA[Accurate and efficient estimation of moisture content during subgrade compaction is critical for ensuring compaction quality and structural integrity. Traditional measurement methods, however, are often lab-intensive, time-consuming, and costly. This study proposes a smartphone-based approach to estimate moisture content in subgrade filling, addressing these limitations. Laboratory experiments captured images of subgrade filling with varying moisture content, gradation and compaction levels. A color correction method based on a color calibration card was applied to mitigate illumination-induced deviations, and an image segmentation technique was used to remove anomalous pixels such as cracks and pores. Feature importance was analyzed using five different methods to identify key variables, which were then used to train and evaluate multiple machine learning models. The proposed approach demonstrated high accuracy in estimating moisture content, offering a practical and scalable solution for subgrade compaction quality monitoring using smartphones.]]></description>
      <pubDate>Fri, 29 Aug 2025 10:03:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2570885</guid>
    </item>
    <item>
      <title>Research on the determination of subgrade gravimetric moisture content under different compactness based on the ground penetrating radar</title>
      <link>https://trid.trb.org/View/2517036</link>
      <description><![CDATA[It is essential for improving the accuracy of subgrade compactness detection to realize the real-time determination of gravimetric moisture content during subgrade compaction. In this study, a subgrade gravimetric moisture content semi-empirical model is established to evaluate the influence of subgrade filling materials types and compactness on the subgrade gravimetric moisture content. The laboratory and field tests for different subgrade types are carried out to collect the subgrade dielectric constant under different compactness. The proposed semi-empirical model is fitted based on the experimental results and the data from the literature. The Ground Penetrating Radar (GPR) technique is then employed to obtain gravimetric moisture content by collecting the dielectric constant of the subgrade in the field test based on the proposed semi-empirical model. The results after removing anomalous data are compared with the results from the time domain reflectometry (TDR) technique. The results show that the subgrade dielectric constant subgrade increases with the gravimetric moisture content growth. And the higher compactness, the higher the dielectric constant with the same gravimetric moisture content. It can be explained that the higher compactness of the subgrade means better water retention. The proposed semi-empirical model obtains the subgrade gravimetric moisture content satisfactorily considering the types and the compactness of the subgrade, as illustrated in comparison with other models in the literature. Based on this, the GPR technique measures subgrade gravimetric moisture content more accurately compared to the TDR technique after removing anomalies. It has the advantages of not disturbing the subgrade, a wide range of applications, and high measurement accuracy, and can realize real-time non-destructive testing. This study provides a basis for determining subgrade gravimetric moisture content in real-time and non-destructive and it is important to improve the accuracy of subgrade quality evaluation.]]></description>
      <pubDate>Thu, 10 Apr 2025 09:21:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2517036</guid>
    </item>
    <item>
      <title>Cumulative frost heave and hydrothermal process of the high-speed railway subgrade under extreme climate conditions in northwest China</title>
      <link>https://trid.trb.org/View/2390963</link>
      <description><![CDATA[The mechanisms underlying the long-term deformation response and hydrothermal processes of high-speed railway subgrades in high altitude, seasonally frozen regions remain poorly understood, especially under extreme weather conditions. This study, based on an eight-year continuous field monitoring of the Lanzhou-Xinjiang High-Speed Railway (LXHR), presents several novel findings. From 2015 to 2022, air temperature, ground surface temperature, and subgrade surface temperature consistently increased, while the average annual rainfall showed a decreasing trend. During this period, sporadic heavy rainfall events occurred, and the climate demonstrated anomalous fluctuations. Such occasional heavy rainfall can cause a rise in the groundwater table, leading to an increase in frost heave within the subgrade. Given the same climatic conditions, embankments display a greater frozen depth compared to road cuts, but experience relatively less frost heave. Frost heave deformation within the subgrade comprises two components: residual deformation and inherent frost heave deformation. Residual deformation primarily contributes to the annual cumulative increase in frost heave, a process succinctly described as the transportation and deposition of fine particles (less than 2 mm in diameter) in coarse fillers by water, in close proximity to the frozen edge, ranging from 0.8 m to 1.2 m of the subgrade. In summary, the results of this study serve as a reminder for engineering designers and researchers to give more attention influence of residual deformation and the current climate change, in consideration of the stability and long-term service performance of subgrade under extreme weather conditions in the future.]]></description>
      <pubDate>Thu, 11 Jul 2024 13:53:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2390963</guid>
    </item>
    <item>
      <title>Jämförande provning korndensitet och vattenabsorption : jämförelse mellan laboratorier</title>
      <link>https://trid.trb.org/View/2388967</link>
      <description><![CDATA[Test comparisons have been carried out between road material laboratories in Sweden for particle density and water absorption according to SS-EN 1097-6:2013 in 2020. The comparison was made with four materials, two with the grading 11/16 mm and two with the grading 0/4 mm. Each participant performed double tests of each material. There were 49 laboratories participating. Generally, are there small variations for particle density between the participants. The coefficient of variation1 is less than 1%. For the water absorption, the variations between the participating laboratories are relatively large. However, this can partly be explained with that the results consists of low values and the "natural" variation is almost as great as the results, about 0.3%. Water absorption has just under 30% in variation coefficient1for the coarser materials in grading 11/16 mm and about 60–70% for the finer ones in grading 0/4 mm. Clearly anomalous participants for particle density for the finer materials is laboratory number 20 with very low results, where even laboratory No. 6 is located low. For water absorption, is it mainly laboratories 33, 12 and 50 that most clearly stand out in a negative way. In general, are the repeatability and the reproducibility, in this comparing analysis better or equal with SS-EN 1097-6:2013.]]></description>
      <pubDate>Mon, 10 Jun 2024 14:04:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2388967</guid>
    </item>
    <item>
      <title>Deep Learning Joint Inversion of Electrical Data for Ahead-Prospecting in Tunneling</title>
      <link>https://trid.trb.org/View/2145535</link>
      <description><![CDATA[Water inrush has become one of the bottlenecks restricting tunnel construction. Among various advanced forecasting techniques, the direct current method is more cost-effective and sensitive to water-bearing structures. It has been widely used in exploring water inrush disasters in practical engineering. Although traditional resistivity linear inversion methods are reasonably practical, they usually suffer from volume effects and cannot accurately locate the location and morphology of water-bearing bodies. Therefore, nonlinear techniques such as deep learning have recently become popular to directly approximate the inversion function by learning the mapping of apparent resistivity data to the geoelectric model. This work presents a novel deep learning-based electrical approach that combines resistivity and polarizability to estimate water-bearing location and morphology. Specifically, the authors design an encoder-decoder network. A shared encoder extracts features from the input data, two encoders output resistivity, and polarizability models, respectively, and fine-tuned collinear regularization for both outputs reduces solutions’ multiplicity. Compared with traditional linear inversion methods and independent parameter inversion, the authors' proposed joint inversion method shows superiority in locating and delineating anomalous bodies.]]></description>
      <pubDate>Fri, 21 Apr 2023 09:49:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2145535</guid>
    </item>
    <item>
      <title>Experimental Validation of a Simple Analytical Model for Specific Heat Capacity of Aqueous Nanofluids</title>
      <link>https://trid.trb.org/View/1822333</link>
      <description><![CDATA[The aim of this study is to explore the anomalous variation of thermo-physical properties of aqueous nanofluids.  The specific heat of three water-based nanofluids containing silicon dioxide (SiO₂), titanium dioxide (TiO₂), and aluminum oxide (Al₂O₃) nanoparticles were measured using a differential scanning calorimeter (DSC).  Measurements were performed over a temperature range of 30°C - 80°C which was chosen to be between melting point and boiling point of water.  The experiments were implemented with different sizes of nanoparticles to investigate the effect of the size of nanoparticles on the specific heat of nanofluids.  The specific heat of the nanofluids was plotted as a function of the diameter of nanoparticles and the mass concentration of nanoparticles.  The results indicate that the specific heat of aqueous nanofluids decreases as the mass concentration of nanoparticles increases from 0.5% to 20%.  Moreover, the results show that the specific heat of nanofluids is less sensitive to the variation of the nanoparticle size and more sensitive to the variation of the mass concentration of nanoparticles.  A simple analytical model for the specific heat of nanoparticle suspensions in a solvent is proposed to explain the observed behavior.  The model accounts for the contribution to the specific heat by an interfacial layer formed at the solid-liquid interface.  The predictions from the proposed analytical model for the specific heat of nanofluids are found to be in close agreement with the experimental results.]]></description>
      <pubDate>Thu, 09 Dec 2021 10:34:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/1822333</guid>
    </item>
    <item>
      <title>Challenges in Bridge Health Monitoring: A Review</title>
      <link>https://trid.trb.org/View/1867154</link>
      <description><![CDATA[Bridge health monitoring is increasingly relevant for the maintenance of existing structures or new structures with innovative concepts that require validation of design predictions. In the United States there are more than 600,000 highway bridges. Nearly half of them (46.4%) are rated as fair while about 1 out of 13 (7.6%) is rated in poor condition. As such, the United States is one of those countries in which bridge health monitoring systems are installed in order to complement conventional periodic nondestructive inspections. This paper reviews the challenges associated with bridge health monitoring related to the detection of specific bridge characteristics that may be indicators of anomalous behavior. The methods used to detect loss of stiffness, time-dependent and temperature-dependent deformations, fatigue, corrosion, and scour are discussed. Owing to the extent of the existing scientific literature, this review focuses on systems installed in U.S. bridges over the last 20 years. These are all major factors that contribute to long-term degradation of bridges. Issues related to wireless sensor drifts are discussed as well. The scope of the paper is to help newcomers, practitioners, and researchers at navigating the many methodologies that have been proposed and developed in order to identify damage using data collected from sensors installed in real structures.]]></description>
      <pubDate>Tue, 27 Jul 2021 15:59:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1867154</guid>
    </item>
    <item>
      <title>Effects of climate changes and road exposure on the rapidly rising legionellosis incidence rates in the United States</title>
      <link>https://trid.trb.org/View/1849192</link>
      <description><![CDATA[Legionellosis is an infection acquired through inhalation of aerosols that are contaminated with environmental bacteria Legionella spp. The bacteria require warm temperature for proliferation in bodies of water and moist soil. The legionellosis incidence in the United States has been rising rapidly in the past two decades without a clear explanation. In the meantime, the US has recorded consecutive years of above-norm temperature since 1997 and precipitation surplus since 2008. The present study analyzed the legionellosis incidence in the US during the 20-year period of 1999 to 2018 and correlated with concurrent temperature, precipitation, solar ultraviolet B (UVB) radiation, and vehicle mileage data. The age-adjusted legionellosis incidence rates rose exponentially from 0.40/100,000 in 1999 (with 1108 cases) to 2.69/100,000 in 2018 (with 9933 cases) at a calculated annual increase of 110%. In regression analyses, the rise correlated with an increase in vehicle miles driven and with temperature and precipitation levels that have been above the 1901–2000 mean since 1997 and 2008, respectively, suggesting more road exposure to traffic-generated aerosols and promotive effects of anomalous climate. Remarkably, the regressions with cumulative anomalies of temperature and precipitation were robust (R2 = 0.9145, P = 4.7E-11), implying possible changes to microbial ecology in the terrestrial and aquatic environments. An interactive synergy between annual precipitation and vehicle miles was also found in multiple regressions. Meanwhile, the bactericidal UVB radiation has been decreasing, which also contributed to the rising incidence in an inverse correlation. The 2018 legionellosis incidence peak corresponded to cumulative effects of the climate anomalies, vast vehicle miles (3,240 billion miles, 15904 km per capita), record high precipitation (880.1 mm), near record low UVB radiation (7488 kJ/m²), and continued above-norm temperature (11.96°C). These effects were examined and demonstrated in California, Florida, New Jersey, Ohio, and Wisconsin, states that represent diverse incidence rates and climates. The incidence and above-norm temperature both rose most in cold Wisconsin. These results suggest that warming temperature and precipitation surplus have likely elevated the density of Legionella bacteria in the environment, and together with road exposure explain the rapidly rising incidence of legionellosis in the United States. These trends are expected to continue, warranting further research and efforts to prevent infection.]]></description>
      <pubDate>Mon, 28 Jun 2021 17:38:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/1849192</guid>
    </item>
    <item>
      <title>An expert-based method for the risk assessment of anomalous maritime transportation data</title>
      <link>https://trid.trb.org/View/1736889</link>
      <description><![CDATA[Risks in maritime navigation linked to cyberthreats emerge, and they must be assessed together with the more traditional risks such as grounding or colliding another vessel, as now the latter might be the consequence of a cyberattack. The fields of mobility and transportation data see vulnerabilities of navigation systems jeopardising their normal use, and putting both users and their environment at risk. In this article, the authors propose a method based on expert knowledge for the risk assessment of cyberthreats in maritime transportation data. A specific focus is proposed on the AIS (Automatic Identification System), a world-wide message-based vessel localisation system that has demonstrated weaknesses allowing errors, falsification and spoofing of its transmitted data. The discovery of abnormal reporting cases is assessed by an expert-designed rule-based analysis frame resulting in the triggering of alerts and the assignment of risk levels, tailored to increase the awareness of the people in charge of monitoring the maritime traffic.]]></description>
      <pubDate>Tue, 27 Oct 2020 12:27:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1736889</guid>
    </item>
    <item>
      <title>A Study on Viscous Wave Drift Force on Semi-submersible and Prediction of The Extreme Value of Mooring Force</title>
      <link>https://trid.trb.org/View/1703979</link>
      <description><![CDATA[In 2012, a mooring line of the semi-submersible "Deepsea Atlantic" that had been operating at Gullfaks South Field in the North Sea was broken. A JIP team investigated causes of the accident in Norway and reported that the accident occurred due to the combination of viscous wave drift force and anomalous wave. Until now, potential wave drift force has been used in the mooring design for semi-submersible but viscous wave drift force has not been taken into consideration. Generally, in the frequency band where the wave length is long, the ratio of potential wave drift force is small among wave drift forces acting on the floating body, while viscous wave drift force becomes dominant. In a structure of which splash zone has a short diameter, such as a column of semi-submersible, the wave length is long compared to the column, and the viscous wave drift force acts remarkably. In this paper, the authors demonstrated a method for a moored semi-submersible to estimate the viscous wave drift force in irregular waves. Then, the validity of a simulation model was verified by comparing the result of numerical simulation and the result of model test. In addition, with regard to the safety evaluation of mooring force, the authors repeated Monte Carlo simulations using the same simulation model, and investigated the influence of number of samples and duration on the prediction of the extreme value of mooring force using different methods for extreme value statistical analysis.]]></description>
      <pubDate>Fri, 15 May 2020 11:20:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/1703979</guid>
    </item>
    <item>
      <title>Total Temperature Measurements in Icing Cloud Flows Using a Rearward Facing Probe</title>
      <link>https://trid.trb.org/View/1631224</link>
      <description><![CDATA[This paper reports on temperature and humidity measurements from a series of ice-crystal icing tunnel experiments conducted in June 2018 at the Propulsion Systems Laboratory at the NASA Glenn Research Center. The tests were fundamental in nature and were aimed at investigating the icing processes on a two-dimensional NACA0012 airfoil subjected to artificially generated icing clouds. Prior to the tests on the airfoil, a suite of instruments, including total temperature and humidity probes, were used to characterize the thermodynamic flow and icing cloud conditions of the facility. Two different total temperature probes were used in these tests which included a custom designed rearward facing probe and a commercial self-heating total temperature probe. The rearward facing probe, the main total temperature probe, is being designed to reduce and mitigate the contaminating effects of icing and ingestion of ice crystals and water droplets at the probe’s inlet. The probe also serves as an air-sample inlet for a light absorption based humidity measurement. The paper includes a section which discusses total temperature and humidity measurement considerations, and another section which provides an analysis of the main probe’s performance characteristics. A computational fluid dynamic model of the flow around the probe was also conducted to gain insight into the trajectory of the flow entering the probe inlet. The experiments included a series of tests in which the relative humidity of the facility flow was swept through with increasingly larger values. The data showed that the rearward facing probe can reasonably capture the flow’s total temperature and humidity under mild to moderate icing conditions but can produce anomalous results under more intense icing conditions. The experimental data was also compared to an in-house developed thermodynamic model which takes into account the interaction of the main flow with the icing cloud. Comparison to the thermodynamic model showed that the rearward facing probe measured the predicted trends.       ]]></description>
      <pubDate>Thu, 27 Jun 2019 14:41:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1631224</guid>
    </item>
    <item>
      <title>Assessment and source identification of pollution risk for touristic ports: Heavy metals and polycyclic aromatic hydrocarbons in sediments of 4 marinas of the Apulia region (Italy)</title>
      <link>https://trid.trb.org/View/1533337</link>
      <description><![CDATA[The Apulia region in Italy has the longest Adriatic coastline; thus, maritime tourism is the driving force for its economic development. Pollution risk for four representative touristic ports of the region was assessed by determining the concentrations of 10 metals, 16 polycyclic aromatic hydrocarbons (PAHs) congeners, and the main nutrients. The cumulative mean Effects Range–Median quotient (mERMq) was used to assess the hazard degree, while the distribution patterns and content ratios of different PAH sediment concentrations were investigated to identify the pollution sources. Principal component analyses indicated an anomalous pollution trend for one of the small touristic ports assessed; this trend emerged from contamination by heavy metals and PAHs to a larger extent than expected, considering the main activity in this port, especially in its inner basin. The reason of this anomaly is thought to be the hydrodynamic and/or other stress factors.]]></description>
      <pubDate>Tue, 16 Oct 2018 15:43:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/1533337</guid>
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