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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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>On-Engine Measurement of Automotive Turbocharger Turbine Blade Vibration</title>
      <link>https://trid.trb.org/View/2691953</link>
      <description><![CDATA[Automotive turbochargers are carefully designed to avoid resonance of the turbine blades and backwall, which can result in High Cycle Fatigue failures. Blade Tip Timing is an established technique which utilizes fiber optic probes to measure turbine blade displacements in real time on turbochargers spinning at upwards of 150,000 RPM. Historically, Blade Tip Timing measurements of automotive turbochargers have been made under steady-state conditions using a Hot Gas Stand. In an industry first, General Motors conducted testing of a turbocharger on a running gasoline engine to capture realistic exhaust pressure dynamics. A reference turbocharger was measured on an engine testbed running a production calibration; the same turbocharger was then tested on a Hot Gas Stand to observe how the blade behavior changed. Blade displacements were found to be lower on engine, because the dynamics of engine pulsation reduced the in-phase work available to drive the turbine blades, resulting in lower blade stresses and an improvement in calculated blade fatigue life. Testing also confirmed that key blade resonances had been successfully moved out of the operating space of the engine. Additionally, blade vibration was measured at multiple temperatures on the hot gas stand, and a clear trend was observed between blade temperature and frequency of vibration. The conclusion is that the new turbine design is ready for adoption and poses no concerns for High Cycle Fatigue. While on-engine testing is more challenging to perform, significant advantages are noted; on-engine testing provides a more realistic life estimate for turbine stages than can be obtained using hot gas stand data alone.]]></description>
      <pubDate>Tue, 14 Apr 2026 15:11:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691953</guid>
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    <item>
      <title>Precision Traffic Monitoring: Leveraging Distributed Acoustic Sensing and Deep Neural Networks</title>
      <link>https://trid.trb.org/View/2561835</link>
      <description><![CDATA[Distributed Acoustic Sensing (DAS) has recently emerged as a promising technology for traffic monitoring. It transforms standard fiber-optic telecommunication cables into an array of vibration sensors capable of capturing vehicle-induced subsurface deformation with high spatio-temporal resolution. In this study, we propose a deep learning framework for the detection and velocity estimation of traffic flow. Our neural network based model yields accurate and well-resolved vehicle localization and speed tracking, outperforming off-the-shelf Dynamic Time Warping based solutions while achieving an order of magnitude faster processing time. A multi-day comparison with dedicated sensors installed along an urban highway shows a strong correlation, even under dense traffic conditions.]]></description>
      <pubDate>Mon, 23 Mar 2026 17:14:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2561835</guid>
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    <item>
      <title>C11 Development of a System-Level Distributed Sensing Technique for Long-Term Monitoring of Concrete and Composite Bridges</title>
      <link>https://trid.trb.org/View/2669644</link>
      <description><![CDATA[The research problem we are trying to solve is the long-term monitoring problem of bridges (e.g., concrete and composite bridges), using multiple modes of sensing technology including fiber optic (BOTDA), optical, and electromagnetic (GPR) sensors. We instrumented a composite bridge (Grist Mill Bridge in Hampden, Maine) with sensing textiles. We have developed structural health monitoring algorithms to process the experimental measurement collected from Grist Mill Bridge (Hampden, ME) to study the long-term bridge monitoring problem. We have developed bridge models for extracting the flexural rigidity (EI) of the bridge. We will use it as one of the indicators for long-term health monitoring. We developed a bound approach to determine the structural properties of bridges by using single-point optical measurement.]]></description>
      <pubDate>Mon, 02 Mar 2026 13:24:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669644</guid>
    </item>
    <item>
      <title>Distributed acoustic sensing-based real-time monitoring of far-field cracks in reinforced concrete bridge decks</title>
      <link>https://trid.trb.org/View/2667271</link>
      <description><![CDATA[Monitoring cracks is critical for the safety and efficiency of the construction and operation of civil infrastructure. Distributed fiber optic sensors offer advantages for crack monitoring, but their applications are largely limited to near-field cracks. This paper presents an approach for in situ, real-time monitoring of far-field cracks using distributed acoustic sensing. The approach is developed through multi-physics modeling of a representative concrete highway bridge. The influence of key configuration parameters, including gauge length, channel spacing, and sampling rate, is evaluated for crack detection and localization. Results show that cracks located up to 6 m from a fiber optic cable are detected and localized with an average error of 0.94 m across 60 tests with varying crack scenarios and configurations. A cost-benefit analysis compares the proposed approach with state-of-the-art methods based on acoustic emission and distributed fiber optic sensing, demonstrating its benefits for far-field crack monitoring.]]></description>
      <pubDate>Fri, 20 Feb 2026 14:15:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2667271</guid>
    </item>
    <item>
      <title>Remote Health Monitoring of the First Smart Bridge in Florida</title>
      <link>https://trid.trb.org/View/2235143</link>
      <description><![CDATA[Monitoring of civil engineering structures is a new area that has gained significant attention recently and became a topic of extreme national interest. This area is being driven by the need to develop efficient condition assessment procedures for structural performance in response to societal and economic needs. The main goal of monitoring is to detect accurately and efficiently structural damage either due to long-term deterioration processes or due to extreme events (e.g. earthquakes, blasts). With the emergence of new technologies, structures can now be monitored remotely from a central monitoring station located several miles away from the field. Sensors are placed at several critical locations along the structure, and send structural information to a central station. The structure is thus thought of as an intelligent or smart system that is capable of sending information and providing warnings before any major failure. This remote capability allows immediate damage detection, so that necessary actions that ensure public safety are taken. The research work concerns the development, construction, and testing of the first smart bridge structure in Florida, the East Bay bridge over Bullfrog Creek in Gibsonton, Hillsborough County. Fiber Optic Fabry-Perot smart sensors were both surface-mounted to the concrete, and bonded to the deck reinforcing bars during the construction phase of the bridge. Static and Dynamic testing of the bridge were performed using loaded SU-4 trucks. A 3-dimensional analytical finite element model of the bridge was developed and its results were compared to the test data. The study confirmed the accuracy of the sensors in estimating the bridge behavior under heavy truck loads. In addition to the tests described above, the smart sensors are currently being connected to a data acquisition system permanently installed on-site. The acquisition system could be accessed through remote communication with DSL lines, which permits the evaluation of the bridge behavior under live traffic loads. Currently, live structural data under traffic loading is being transmitted continuously to the county maintenance office. The technology developed under this work will enable practical, cost-effective, and reliable maintenance of bridge structures, and the study will provide a unique opportunity for future growth of this technology within the state of Florida.]]></description>
      <pubDate>Tue, 17 Feb 2026 13:12:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2235143</guid>
    </item>
    <item>
      <title>Distributed Fiber Optic Sensing System for Bridge Monitoring</title>
      <link>https://trid.trb.org/View/2663099</link>
      <description><![CDATA[The fabricated sensing textile was installed on three bridges: Salmon Falls Bridge in New Hampshire, Grist Mill Bridge in Maine, and a pedestrian bridge at UMass Lowell (UML). (1) Salmon Falls Bridge (NH): Strain responses were collected for both baseline conditions and during train crossings. (2) Grist Mill Bridge (ME): Frequency and strain responses were measured under different truck loads and compared with baseline data. (3) UML Pedestrian Bridge: Distributed strain responses were recorded for various human activities, including walking, running, and jumping, under different load conditions. Field tests on each bridge were conducted over several years. The collected data demonstrated the sensing textile’s capability for long-term structural health monitoring. Results from these studies have been published in journals and presented at conferences.]]></description>
      <pubDate>Thu, 12 Feb 2026 08:52:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663099</guid>
    </item>
    <item>
      <title>Bending strain progression and damage of asphalt beams based on distributed fibre optic sensors</title>
      <link>https://trid.trb.org/View/2643552</link>
      <description><![CDATA[Under long-term vehicle loading, asphalt pavement surfaces undergo settlement, while the lower layers develop cracks due to the imposed loads. These cracks gradually propagate upwards until they penetrate the surface layer. In extensive transportation environments, many newly constructed roads often develop bottom cracks after a period of use. These cracks can expand gradually under sustained loads and natural conditions, potentially evolving into through cracks, thereby exacerbating damage to the road surface and reducing its lifespan. To enhance the longevity of asphalt pavement, it is crucial to conduct health monitoring to track crack development. This study addresses this issue by using small asphalt beams to simulate damage progression. Static and fatigue loading three-point bending tests were conducted on these asphalt beams. Distributed fibre optic sensors were employed to monitor strain distribution curves during loading, enabling analysis of the failure process of asphalt beams. This approach systematically evaluates deformation capacity, stages of crack development, and load-bearing capacity based on the strain distribution curves. The test results indicate that distributed fibre optic sensors can effectively monitor the strain conditions of asphalt beams. They are also capable of accurately identifying the origins of cracks and tracking their formation and development in real time.]]></description>
      <pubDate>Sun, 25 Jan 2026 15:40:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643552</guid>
    </item>
    <item>
      <title>Bridging the gap between research and practice: the case of distributed fiber optic sensors for SHM of concrete structures</title>
      <link>https://trid.trb.org/View/2640594</link>
      <description><![CDATA[This paper shows the path followed by a research team at UPC-BarcelonaTech in order to implement the technology of distributed strain sensing using fiber optical sensors to structural concrete. To reach this objective it was necessary to bridge the existing huge gap between a monitoring technology developed in other fields to the specific case of civil engineering concrete structures. Therefore, bridging this gap was mandatory for a successful implementation of the new technology. This was achieved by a ‘3-span bridge’. How the 3 spans are defined, founded and built up is explained through the chapters of the paper by showing several laboratory and full-scale applications carried out in the last 15 years where thin-coated distributed fiber optical sensors (DFOS) and Rayleigh backscattering were the selected options for the distributed sensing. The process shown in the paper may have similar applications to other techniques born in other disciplines different from civil engineering, but that present clear potential applicability. After some adaptation developments because of the characteristics of the materials used in civil engineering structures, the research and testing at the laboratory level finally derives in a full developed methodology that is finally tested on some real-world prototypes.]]></description>
      <pubDate>Thu, 22 Jan 2026 09:10:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640594</guid>
    </item>
    <item>
      <title>Developing Advanced Technologies for Field Performance Monitoring of Polypropylene Pipe</title>
      <link>https://trid.trb.org/View/2655578</link>
      <description><![CDATA[The Kansas Department of Transportation (KSDOT) has recently adopted polypropylene (PP) plastic pipes for highway drainage. Different from concrete and metal pipes, plastic pipes are expected to have large deformations under loading due to their lower stiffness. It is well known that plastic materials have creep behavior, i.e., deformations increase with time under constant loads. PP materials have more creep deformations than other polymer materials. However, when pipes are buried in the ground, they are subjected to lateral confinement from surrounding soils, which may reduce vertical deformations of pipes. This research team monitored two steel-reinforced high-density polyethylene (SRHDPE) pipes in the ground in the past K-TRAN projects using strain gauges, displacement transducers, and earth pressure cells. This field monitoring demonstrated that SRHDPE pipes performed well with small creep deformations at a slowly increasing rate. This good performance may be attributed to steel strip reinforcement embedded in the ribs around the pipe. So far, limited data is available on the deformations of PP plastic pipes in the ground; therefore, there is a great need for field monitoring of this type of pipe in the ground to ensure their long-term performance. Strain gauges and displacement transducers have been proved effective for field monitoring of pipes; however, they have major limitations: (1) they are placed at sparse locations along the pipe, (2) strain gauges do not last long, and (3) temperature effect is hard to consider for displacement transducers. To overcome these problems, distributed fiber optic sensors (DFOS) have been increasingly used to monitor infrastructures including pipes. One or multiple fibers are included a cable to be fixed on an object for measurements. Different from resistance types of gauges that measure resistance changes, DFOS measure the changes of light energy or frequency. The major advantages of DFOS are (1) they are suitable for long distance measurements (up to miles), (2) they provide almost continuous measurements along one fiber, (3) they significantly reduce the number of individual cables, (4) they can measure strains and temperatures so that the temperature effect can be corrected, (5) fibers can be placed not only along the longitudinal direction of the pipe but also around the cross-section of the pipe, and (6) fibers are relatively inexpensive. However, this technology has not been well implemented in field monitoring of plastic pipes; therefore, it requires research, confirmation, and development. For example, how measured strains are converted into deformations of pipes. To overcome the limitation of displacement transducers, photogrammetry has been used to capture deformed objects, such as pipes. Photogrammetry is also suitable for field monitoring of existing pipes. To take advantage of both technologies, the research team proposes to conduct a laboratory study to verify these two technologies and develop procedures for implementing them in future field monitoring of plastic pipes.]]></description>
      <pubDate>Thu, 15 Jan 2026 12:31:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655578</guid>
    </item>
    <item>
      <title>Use of Distributed Acoustic Sensing for Structural Health Monitoring of Asphalt Pavements</title>
      <link>https://trid.trb.org/View/2643008</link>
      <description><![CDATA[This research investigates the feasibility of utilizing Distributed Fiber Optic Sensing (DFOS) technology to monitor strain within pavement structures. Unlike traditional sensors, DFOS provides high-resolution strain measurements along the entire length of an optical fiber, enabling continuous monitoring of pavement behavior under traffic loading. The study involved calibrating a DFOS system using a dedicated jig and implementing it within a laboratory-scale accelerated pavement testing setup. Challenges related to sensor installation, compaction, and slab support were encountered and addressed. Results demonstrated the ability of DFOS to capture high-resolution strain distributions within asphalt slabs subjected to simulated traffic loads, surpassing traditional methods and with readings every 2.6 mm along the fiber. The study concludes that DFOS offers significant advantages in real-time pavement monitoring, improving the accuracy and efficiency of data collection for maintenance planning. These findings will support the development of best practices for implementing DFOS systems, equipping pavement engineers with tools for proactive road management and optimizing infrastructure maintenance strategies.]]></description>
      <pubDate>Fri, 09 Jan 2026 16:58:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643008</guid>
    </item>
    <item>
      <title>Use of Distributed Acoustic Sensing for Structural Health Monitoring of Asphalt Pavements [supporting dataset]</title>
      <link>https://trid.trb.org/View/2643009</link>
      <description><![CDATA[For access to these files, contact the Oklahoma Transportation Library (OTL) at ODOT-​Library@ou.edu. The accompanying files contain experimental raw measurements compiled into two separate spreadsheet documents. For each file, key details such as its name, size, file format, and a brief description of the data it holds are outlined. This summary serves as a quick reference, allowing users to readily understand the context of each dataset including the experimental setup.  An additional explanation of the content of each file is provided in the Overview ta​b within each file. File Name: Strain Measurements - Testing with MMLSFile Size: .xlsx (Microsoft Excel Spreadsheet)Fil​e Type:49.9 MBType of Data: Experimental measurements obtained using strain sensor. Description: Distributed fiber optic strain measurements collected during accelerated loading tests of an asphalt slab using a Model Mobile Load Simulator (MMLS). Data includes strain readings at various locations along the fiber optic sensor as a function of time (various MMLS wheel passes recorded).  Each tab stores the raw data file for each test. File Name: Strain Measurements - Testing with Three-Point Bending Testing of Aluminum Bar for Calibration of DFOSFile Size: .xlsx (Microsoft Excel Spreadsheet)Fil​e Type:231 MBType of Data: Experimental measurements obtained using strain sensor. Description: Distributed fiber optic strain measurements obtained during three-point bending test of an aluminum bar. This file also includes the loading rate of the MTS machine used for the test. This data is intended for calibrating the strain fiber optic sensor.]]></description>
      <pubDate>Fri, 09 Jan 2026 16:58:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643009</guid>
    </item>
    <item>
      <title>Continuous 3D Strain Imaging for Structural Health Monitoring of Pavements </title>
      <link>https://trid.trb.org/View/2646968</link>
      <description><![CDATA[This project proposes to advance road infrastructure monitoring by leveraging distributed fiber optic sensing (DFOS) technologies in conjunction with advanced visualization techniques. While typical assessment tools rely on surface measurements and back calculation methods to infer internal conditions, they cannot measure strains within the pavement layers directly. On the other hand, traditional localized sensors offer limited spatial coverage, missing critical information between sensing points. Embedding distributed fiber optic sensing sensors directly into pavement structures will potentially enable the acquisition of high-resolution, real-time distributed strain measurements across extended lengths, providing an unprecedented, comprehensive understanding of the infrastructure condition under traffic loads. Furthermore, the integration of distributed fiber optic sensing measurements with mapping tools will allow transportation engineers to readily identify potential damage areas and structural deficiencies, which can potentially lead to optimized maintenance scheduling, improved road safety, and reduced long-term infrastructure management costs for highway agencies. 

This project aims to develop methods and tools to advance road infrastructure monitoring by integrating fiber optic strain sensing with 3D visualization. To achieve this goal, laboratory testing of pavement specimens strategically instrumented with distributed fiber optic sensing while trafficked with simulated traffic loads will be conducted to generate detailed strain measurements. Key objectives include developing methods for referencing, acquiring, and processing real-time, distributed strain data from embedded fiber optic sensors to generate insightful maps capable of representing strain distributions and their evolution in response to traffic, environment, and distress. This will facilitate the early identification of structural deficiencies, ultimately supporting proactive maintenance planning for highway agencies.  

The project scope involves developing and validating a comprehensive monitoring and visualization framework. This includes optimizing data acquisition, creating algorithms for efficient data reduction and processing of continuous strain measurements, and designing interactive 3D visualization tools. Laboratory validation of the techniques will be conducted, with the goal of future field testing on actual test sections to demonstrate the practical applicability and benefits of the developed system for highway agencies. ]]></description>
      <pubDate>Tue, 06 Jan 2026 17:23:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646968</guid>
    </item>
    <item>
      <title>Implementing Fiber Optic Technology for Underground Gas Storage Well Monitoring</title>
      <link>https://trid.trb.org/View/2637283</link>
      <description><![CDATA[This project will establish a comprehensive understanding of the applicability of the fiber optic monitoring technology for underground gas storage (UGS) wells (including salt caverns and depleted reservoirs) by leveraging learnings from past projects with full-scale laboratory tests. The knowledge obtained through this project will form a basis to establish guidelines and best practices for implementing the fiber optic downhole monitoring technology in UGS wells. The expected outcomes of this project are to establish guidelines and best practices to guide the implementation of the fiber optic technology for continuous downhole integrity monitoring of underground natural gas storage wells with consideration of applications for future underground hydrogen storage (UHS). The critical targets of the fiber optic monitoring system for UGS wells include: (1) cost effectiveness; (2) effective well integrity monitoring; (3) long-term integrity of the fiber optic system; and (4) minimal risks of introducing leak paths.]]></description>
      <pubDate>Tue, 30 Dec 2025 08:57:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2637283</guid>
    </item>
    <item>
      <title>Design and Development of Fiber Optic Vibration Sensor for Automobile Applications</title>
      <link>https://trid.trb.org/View/2623850</link>
      <description><![CDATA[This work goals at designing and developing a vibration sensor based on fiber optics and it is a component of the Structural Health Monitoring (SHM) system. The main component of the SHM system is a network of sensors (strain, vibration, acoustic, etc.) that can track the physical condition of the structures in real time and assist in identifying the beginning of any damage. During flight, launch vehicles typically experience extreme dynamic stresses such shock, random vibration, aerodynamic, and thermal. The assessment of health and the detection of any part detachment or loosening of sub- assemblies are greatly aided by vibration monitoring. Compared to traditional electrical sensors (such piezoelectric or capacitive), SHM systems based on fiber optic sensors show promise because of their EMI resistance, ease of integration into structures, and widespread sensing capabilities. Multiplexing capability of optical fibers is the main additional benefit for system monitoring the numerous dispersed sensors. Surface- bonded and embedded fiber bragg gratings (FBG) are commonly utilized configurations for aircraft and flight structure monitoring. The frequency of vibration changes, or the frequency signature changes, as structural damage is beginning. Thus, a vibration sensor provides vital information about the structure’s condition before any catastrophic damage occurs.]]></description>
      <pubDate>Thu, 18 Dec 2025 15:37:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623850</guid>
    </item>
    <item>
      <title>Using Fiber-Optic Sensors to Assess the Strength Characteristics of Road Structures Allowing for Vehicle Speed</title>
      <link>https://trid.trb.org/View/2603916</link>
      <description><![CDATA[The study of the strength characteristics of road pavements is important to ensure the reliability of road infrastructure in the face of growing traffic and changing climate conditions. Understanding the mechanisms that affect strength and durability allows us to develop stable pavements that can withstand heavy loads and fluctuations in temperature and moisture. The aim of this study was to develop a system for monitoring the road surface and determining the modulus of elasticity of the road surface in moving traffic using fiber-optic sensors. The methods that were used to carry out the study were the finite-element method, Newmark direct integration method, and experiment. As a result of the study, it was proved that the monitoring system using fiber-optic sensors can provide an accuracy of up to 98.5% in determining the category of vehicles. At vehicle speeds of 8 and 70  km/h, the developed system provides reliable longitudinal sensor measurements with accuracy levels of 86.3% and 89.5%, respectively, making it a reliable and effective tool for monitoring and controlling road traffic and roadway condition. It can analyze various vehicle characteristics such as the speed, axle spacing, and number of axles, which provides additional data for optimizing road infrastructure and developing more accurate pavement maintenance and repair strategies. The practical significance of the results obtained is a significant increase in road safety, which is a critical aspect in the current conditions of growing traffic load and increasing the number of cars on the roads.]]></description>
      <pubDate>Thu, 20 Nov 2025 17:07:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2603916</guid>
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