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    <title>Research in Progress (RIP)</title>
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    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMTYiIC8+PC9wYXJhbXM+PGZpbHRlcnM+PGZpbHRlciBmaWVsZD0iaW5kZXh0ZXJtcyIgdmFsdWU9IiZxdW90O0ZpYmVyIG9wdGljcyZxdW90OyIgb3JpZ2luYWxfdmFsdWU9IiZxdW90O0ZpYmVyIG9wdGljcyZxdW90OyIgLz48L2ZpbHRlcnM+PHJhbmdlcyAvPjxzb3J0cz48c29ydCBmaWVsZD0icHVibGlzaGVkIiBvcmRlcj0iZGVzYyIgLz48L3NvcnRzPjxwZXJzaXN0cz48cGVyc2lzdCBuYW1lPSJyYW5nZXR5cGUiIHZhbHVlPSJwdWJsaXNoZWRkYXRlIiAvPjwvcGVyc2lzdHM+PC9zZWFyY2g+" 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>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>Developing Advanced Technologies for Field Performance Monitoring of Polypropylene Pipe</title>
      <link>https://rip.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://rip.trb.org/View/2655578</guid>
    </item>
    <item>
      <title>Continuous 3D Strain Imaging for Structural Health Monitoring of Pavements </title>
      <link>https://rip.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://rip.trb.org/View/2646968</guid>
    </item>
    <item>
      <title>Instrumentation And Monitoring For G-Beam/Stillwater Avenue Bridge Replacement</title>
      <link>https://rip.trb.org/View/2582413</link>
      <description><![CDATA[In the proposed project, the research team plans to deploy an extensive instrumentation and communication system that will be embedded in the G-Beam girders proposed for the Stillwater Avenue bridge in Orono/Old Town.  Some of the details of the specific monitoring plan will need to be deferred to coincide with girder design.
The study will include the following. First, an array of fiber optic cabling will be installed along the longitudinal beam axis at different locations relative to the neutral axis.  Each cable will include discrete sensors at different locations along the beam axis to capture strain at those points.  Second, an array of accelerometers will be located it key locations in order to capture frequencies and modes of vibration during service.  Both the accelerometers and the fiber optic system will be connected to a communications network that both collects data from the sensor array and broadcasts the data over a wireless network to a server at University of Maine (UMaine).  Depending on collection rates, the data will either be transmitted over a conventional 5G cellular network, or more likely via a closed network that sends the data through a series of discrete repeaters in between the bridge site and the server.  Third, the team proposes a system of digital cameras that will be used both to trigger the acquisition and transmission system, but also through machine vision, be able to identify the vehicle type (e.g. number of axles.)  Once triggered, the array of strain gages and accelerometers, will preprocess data and send to the UMaine server.  In this way, resulting strain and vibration data can be tied to load types.  Fourth, a weather station will monitor current temperature, sunlight, and relative humidity data to complement the acquired structural data.  Depending on design issues, additional on-site sensors can monitor water level, ice status, and other environmental conditions that may be relevant. Finally, we will conduct diagnostic live load tests on the completed structure immediately before it is opened to traffic and approximately one year after its completion]]></description>
      <pubDate>Thu, 31 Jul 2025 14:23:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/2582413</guid>
    </item>
    <item>
      <title>Revenue Opportunities from MDOT Fiber
Infrastructure
and Other Utility Types</title>
      <link>https://rip.trb.org/View/2562269</link>
      <description><![CDATA[Various state highway agencies permit telecommunications to be located longitudinally along freeway rights-of-way (ROW). 
Michigan Department of Transportation (MDOT) is interested in a study of alternative sources of transportation revenues that could be phased in over time to replace
revenue lost as motor and diesel fuel decline become obsolete. MDOT focus would be on non-vehicle related revenue streams,
such as, leasing rights-of-way for Fiber Communications and/or other utility types, possibly private transportation facilities,
and/or public-private partnerships.]]></description>
      <pubDate>Fri, 06 Jun 2025 15:08:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2562269</guid>
    </item>
    <item>
      <title>Use of Distributed Fiber Optic Sensing (DFOS) to Assess Bonding and Failure Mechanisms of Asphalt Pavements</title>
      <link>https://rip.trb.org/View/2480363</link>
      <description><![CDATA[Phase I of this project was focused on understanding and developing tools for utilizing Distributed Fiber Optics Sensing (DFOS), also known as Distributed Acoustic Sensing (DAS), to establish best practices for implementing this technology to gain insight into the pavement condition. In Phase II, this project advances to implement DFOS to assess the failure mechanisms of pavements. Under ASPIRE research activities, research is being conducted to address the inclusion of Inductive Power Transfer (IPT) technology components embedded in pavements. A critical concern with embedding transmitter pads near the surface is the potential development of high tensile stress under traffic conditions. These stresses can lead to cracking or delamination due to poor bonding with the encasing materials, i.e., asphalt or PCC. Moreover, tensile stresses are expected to occur in locations difficult to instrument with vibrating wire strain gauges, such as edges and corners of embedded IPT components. While strain gauges can only be placed at discrete points and usually a few inches away from critical locations, fiber optic sensors can acquire data continuously along various paths, closer to these critical locations. As observed in Phase I, this technology provides enhanced spatial measurements with a resolution as fine as 2.6 mm in near-real time. These capabilities are suitable for the assessment of bonding conditions and failure mechanisms. This technology can benefit Region 6 DOTs as a tool that can be potentially utilized in the laboratory or in the field to collect pavement response to predict pavement performance for assessing highway infrastructure life and even to develop or adjust distress models when new technologies are implemented within pavements. 
To address the objective of this study, the scope of work consists of the following: Task 1: Utilizing DFOS to instrument asphalt specimens with embedded IPT components and subjecting them to flexural tests. This approach aims to assess bonding and flexural behavior while identifying failure mechanisms. Task 2: Numerical modeling will be conducted to simulate the behavior of the instrumented specimens, focusing on identifying critical points for crack development or delamination under various bonding conditions. Task 3: The numerical model responses will be compared against experimental results with the purpose of fine-tuning the model. Limitations of DFOS technology will be examined, and recommendations for its application in assessing pavement performance will be developed. The findings, along with guidelines for instrumenting pavement locations prone to cracking, will be documented into a draft report.
]]></description>
      <pubDate>Wed, 01 Jan 2025 17:18:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2480363</guid>
    </item>
    <item>
      <title>Assessing Condition of Rehabilitated Concrete Pavement with Slab Fracturing and Asphalt Overlay Using Distributed Fiber Optic Sensors</title>
      <link>https://rip.trb.org/View/2373771</link>
      <description><![CDATA[The United States is experiencing a significant increase in registered motor vehicles, resulting in increasing traffic loads on transportation infrastructure, particularly on roads prone to cracking. Asphalt overlay is commonly used to rehabilitate concrete pavements. However, asphalt overlay often results in reflective cracking, leading to expensive repairs. To address this issue, slab fracturing and asphalt overlay has been popularly applied to rehabilitate cracked concrete pavements in recently years. To investigate the effectiveness of the slab fracturing and asphalt overlay for concrete pavement rehabilitation, his research focuses on understanding how crack propagate through the asphalt overlay. While current crack detection methods struggle to assess bottom-up cracking effectively, posing safety hazards and financial burdens, this project proposes to use distributed fiber optic sensing (DFOS) to monitor bottom-up cracking of the rehabilitated concrete pavements using slab fracturing and asphalt overlay in real time. Through a comprehensive approach combining numerical simulations and laboratory experiments, this research aims to expand our understanding of crack formation mechanisms while assessing the effectiveness of DFOS for monitoring bottom-up cracks in pavements. Numerical simulations using finite element analysis replicate real-world pavement conditions and consider factors such as traffic loading and material properties. Laboratory experiments entail constructing pavement specimens with different layers, installing DFOS sensors to measure strain during crack emergence, and subjecting specimens to controlled loading conditions resembling real-world scenarios. Anticipated outcomes include providing effective pavement condition monitoring alternatives for rehabilitated concrete pavements using slab fracturing and asphalt overlay, contributing to safer and more sustainable management of transportation systems.]]></description>
      <pubDate>Mon, 29 Apr 2024 10:55:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2373771</guid>
    </item>
    <item>
      <title>Comprehensive Diagnostic System for Corrosion Assessment of Concrete Infrastructure</title>
      <link>https://rip.trb.org/View/2344530</link>
      <description><![CDATA[Concrete undergoes numerous physical and chemical changes during its service life that are induced by the transport of moisture and ingress of ionic species. Comprehensive non-destructive monitoring tools that enable the diagnosis and prognosis of concrete health are vital for managing, forecasting, and hence reducing the cost of maintenance and repair while improving infrastructure safety. Current structural health monitoring (SHM) tools are limited to the use of sensors that only interrogate parameters including displacement, strain, and temperature. Such sensors can identify whether damage has developed but cannot provide any indication of the "underlying chemical distress," which is often the root cause of the damage. To ensure the safety of reinforced concrete structures and determine their fitness for service, it is essential to develop a comprehensive SHM system that uses a suite of chemical sensors to monitor, forecast, and elucidate structural remediation protocols. From a mechanistic standpoint, steel corrosion is an electrochemical process, and, therefore, detection of steel corrosion necessitates the monitoring of chemical indicators relevant to the electrochemical process. The objective of the project is to build upon preliminary work to develop a comprehensive sensing system to enable real-time and "off-site" monitoring of the health of concrete infrastructure. Targeting External Sulfate Attack (ESA), a key contributor to concrete deterioration, this project integrates an optical fiber-based remote Raman probe with fiber optic distributed strain sensors. This advanced system is set to outperform traditional resistance measurement methods, offering in-depth, real-time monitoring of concrete integrity.]]></description>
      <pubDate>Tue, 27 Feb 2024 12:55:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/2344530</guid>
    </item>
    <item>
      <title>SBIR Phase II: Fiber Optic Sensors for Direct Pipeline Monitoring Under Geohazard Conditions</title>
      <link>https://rip.trb.org/View/2093161</link>
      <description><![CDATA[The project will develop, test and verify a mechanically, environmentally, and age-robust optical distributed and point monitoring sensor that can be permanently and cost effectively installed onto pipelines. These sensors will detect strain from geohazards, leaks, corrosion and 3rd party tampering using a commercial service.]]></description>
      <pubDate>Tue, 03 Jan 2023 13:53:29 GMT</pubDate>
      <guid>https://rip.trb.org/View/2093161</guid>
    </item>
    <item>
      <title>Distributed strain sensing for pipeline safety against fault moving and landslide</title>
      <link>https://rip.trb.org/View/2085763</link>
      <description><![CDATA[The research objective is to develop a robust distributed fiber optic strain sensing system for long-term monitoring structural performance of pipeline subjected ground movements at fault crossing and landslide sites.]]></description>
      <pubDate>Fri, 16 Dec 2022 14:15:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2085763</guid>
    </item>
    <item>
      <title>Distributed Fiber Optic Sensor Network for Real-time Monitoring of Pipeline Interactive Anomalies</title>
      <link>https://rip.trb.org/View/2085749</link>
      <description><![CDATA[The overarching goal of this research is to pave a path which may transform the current pipeline anomaly detection technologies to a distributed fiber optic sensor network for real-time detection, localization, and quantification of interactive anomalies of pipelines, thus improving the pipeline safety and management.]]></description>
      <pubDate>Fri, 16 Dec 2022 14:15:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2085749</guid>
    </item>
    <item>
      <title>2291 A Fatigue Assessment Framework for Steel Bridges using Fiber Optic Sensors and Machine Learning</title>
      <link>https://rip.trb.org/View/1897282</link>
      <description><![CDATA[The main goal of the proposed research is to develop a machine learning (ML)assisted structural health monitoring (SHM) approach that employs fiber optic sensors (FOS) to enable (a) the assessment of the fatigue life of steel bridge details and (b) the accurate detection of the presence of damage under normal traffic loading conditions. In more detail, the proposed research aims at:
-Constructing a monitoring system based on FOS to enable accurate strain quantification for efficient fatigue assessment and performance evaluation of steel bridge components. The FOS are chosen given their accuracy, low noise level, and durability. The developed monitoring system will be suitable for long-term field application under aggressive environmental conditions.
-Formulating an approach that utilizes data from the FOS for damage detection in steel bridge components. The approach should detect and localize the damage without requiring detailed finite element modeling of the structure or detailed vehicular loading data. These requirements ensure its applicability for automated damage detection for existing bridges without the need for intensive post-processing data analysis.
-Characterizing the effect of key operational parameters on the efficacy of the damage detection algorithm. These include the effect of loading conditions, temperature variations, type of damage, and boundary conditions.
The proposed project will include the design of an instrumentation system for field application and validating its damage detection capabilities using large-scale laboratory testing.]]></description>
      <pubDate>Tue, 14 Dec 2021 11:51:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/1897282</guid>
    </item>
    <item>
      <title>Combined Structural Health and Traffic Monitoring using Fiber Optic Distributed Acoustic Sensing</title>
      <link>https://rip.trb.org/View/1841547</link>
      <description><![CDATA[At present, study of the integration of structural monitoring and traffic monitoring is presently underserved in researchers. To our knowledge, no researcher has used acoustic emission measurements obtained from distributed optical fiber sensors to simultaneously monitor bridge health and traffic conditions from a single measurement while simultaneously incorporating both finite element modelling and an artificial neural network for data analysis.  
The combination of all of these elements into a single system would represent a path forward to an all-in-one bridge monitoring system. By combining traffic monitoring and health monitoring from a single data source, asset owners would stand to benefit from both increased data and reduced monitoring costs. If successfully executed, such a system would also have potential for future expansion to accommodate additional data collection and analysis tasks, as the structural dynamics model and artificial intelligence algorithm can be easily amended or expanded to accommodate such tasks in a variety of bridge and traffic conditions. This level of expandability and customizability greatly increases the future commercial viability and practical applicability. Accordingly, it is recommended that the viability of the proposed system be more thoroughly analyzed. 
Objectives: The proposed research seeks to investigate the viability of the use of Distributed Optical Fiber Sensors (DOFS) that measure acoustic emission (AE) for use as a combined bridge health monitoring and vehicle classification tool. An artificial neural network will be developed to process DOFS AE data to classify vehicle loading and categorize results. Categorized results will be compared against results generated by a structural dynamics FEM to serve as a method of determining the health of the structure.]]></description>
      <pubDate>Thu, 18 Mar 2021 12:06:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/1841547</guid>
    </item>
    <item>
      <title>Condition Evaluation of Precast Post-tensioned Concrete Girder Bridges During Fires from Distributed Fiber Optic Sensors</title>
      <link>https://rip.trb.org/View/1762370</link>
      <description><![CDATA[In the past few years, the research team has instrumented three full-scale concrete slab on steel beam composite floor specimens with distributed fiber optic sensors using pulse pre-pumped Brilliouin optical time domain analysis (PPP-BOTDA). Cost-effective single-mode optical fibers were used as distributed sensors for strain measurements when not sheathed with protective layers and for temperature measurements when sheathed with protective layers. Each specimen was prepared in the National Fire Laboratory and tested under combined mechanical and thermal loading by the National Institute of Standards and Technology. Technical challenges discovered during data process and analysis include: (1) uncertain interfacial bond condition between optical fibers and their surrounding concrete as fire gradually melts or burns off the protective layers of the fibers, (2) slow measurement process (e.g., 2 minutes) for the understanding of fire dynamics effect, and (3) interactive effect of multiple cracks on strain and temperature discrimination.

This project aims to further understand the behavior of interfaces between optical fibers and their surrounding concrete with or without the effect of protective layers, reduce measurement times using the concept of compressive sensing, and develop and validate the distributed sensing approach for monitoring of the prestress loss in grouted and non-grouted steel tendons in post-tensioned concrete girders under fire conditions. The scope of work includes (1) Effect of the protective layers and deployment schemes of a temperature sensor on potential binding of the optical fiber with its surrounding concrete at high temperatures, (2) Detectability of interactive concrete cracks from distributed strain sensors, (3) Rapid monitoring of the prestress loss in steel tendons in concrete girders, and (4) Implementation and validation of distributed fiber optic sensors in a large-scale two-girder supported bridge deck under combined dead load and fire conditions.]]></description>
      <pubDate>Thu, 07 Jan 2021 14:12:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/1762370</guid>
    </item>
    <item>
      <title>Sensor-assisted Condition Evaluation of Steel and Prestressed Concrete Girder Bridges Subjected to Fire – Phase III</title>
      <link>https://rip.trb.org/View/1685055</link>
      <description><![CDATA[The overarching goal of this multi-phase study is to develop and validate a post-fire condition evaluation method for steel- and prestressed concrete-girder bridges (overpasses or viaducts) based on material  and structural data, a fire scenario (e.g., a fuel tank on highway), and environmental factors (e.g., moisture and wind). The proposed method involves fire dynamics simulation underneath a bridge, thermomechanical analysis of the structure, and structural condition assessment against material strengths. One of the key challenges to achieve this goal is to measure strains in steel members on fire and detect concrete cracks in order to validate various computational models. Phases I and II of this study aimed to understand and validate the performance of distributed fiber optic sensors based on Brilliouin optical time domain analysis (BOTDA) for temperature and strain measurements in reinforced concrete (RC) bridges, and develop and validate a fire dynamics simulator and a thermomechanical model with measured data. In particular, the deployment scheme and data quality of distributed sensors embedded in concrete and attached on steel members are evaluated. The effects of multiple steel girders on the aerodynamics and heat distribution of a fire are investigated through fire dynamics and thermomechanical analysis. Phase III of this study aims to understand the performance and behavior of prestressed concrete girders under a fire and quantify the prestress loss over time using distributed fiber optic sensors such as BOTDA. Due to uncertain bonding between an optical fiber and concrete, strain measurements based on the transfer of strain from concrete to the optical fiber are less reliable particularly to determine the loss of prestress in tendon. Therefore, a new distributed fiber optic acoustic sensing system will be used to detect cracks developed in proximity of the concrete-tendon interface.]]></description>
      <pubDate>Thu, 30 Apr 2020 15:13:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1685055</guid>
    </item>
    <item>
      <title>Development of a System-Level Distributed Sensing Technique for Long-Term Monitoring of Concrete and Composite Bridges (C11.2019)</title>
      <link>https://rip.trb.org/View/1683657</link>
      <description><![CDATA[Long-distance distributed sensing of bridges using fiber optic sensors is achieved by the Brillouin scattering of nonlinear acoustic photons (laser light) inside an optical fiber. Such nonlinear scattering of incident photons can be exploited to obtain the change of state (due to temperature or stress) at different locations in an optical fiber over a long distance (e.g., from several to hundreds of miles). In this project, Brillouin Optical Time Domain Reflectometer (BOTDR) technique has been adopted for distributed sensing of mechanical and thermal strains of bridges. Figure 2 shows the schematic configuration of BOTDR for bridge monitoring and the conceptual description of multiphysical observation of structural behavior for health monitoring. The research team will develop a system-level distributed sensing technique and its design procedure for composite and concrete bridges, as well as developing structural health monitoring algorithms based on mechanical and electromagnetic measurements using fiber optic, video motion, and radar sensors. ]]></description>
      <pubDate>Fri, 07 Feb 2020 19:41:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/1683657</guid>
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