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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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    <language>en-us</language>
    <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>Crash prediction under limited CV coverage: an ensemble deep learning model integrating multi-source traffic data</title>
      <link>https://trid.trb.org/View/2633648</link>
      <description><![CDATA[This study presents a comprehensive crash prediction framework that integrates traditional microwave vehicle detection systems (MVDS) with emerging connected vehicle (CV) data to improve proactive traffic safety management. While MVDS data provide consistent, infrastructure-based traffic measurements, their spatial coverage and behavioral resolution are limited. In contrast, CV data offer high-resolution, continuous vehicle trajectories that capture detailed driving behavior, but suffer from low and uneven market penetration. To fully leverage the strengths of both sources, an ensemble deep learning model was developed, utilizing MVDS data for macroscopic, segment-level traffic patterns and CV data for microscopic, vehicle-level dynamics. Importantly, rather than relying on segment-level aggregated CV metrics, this study directly utilizes individual vehicle trajectories to preserve temporal and spatial fidelity, enabling the model to capture detailed behavior that often precedes crashes. Three modeling configurations, MVDS only, CV only, and MVDS + CV data, were evaluated across different crash types and roadway segment types. Results demonstrate that integrated data source model consistently outperforms single-source models, achieving higher sensitivity and lower false alarm rates, particularly for rear-end and sideswipe crashes. Furthermore, model performance was evaluated under varying CV market penetration rates. While CV-only model showed limited performance under low coverage (<1%), it exhibited strong and stable results at 4 % penetration or higher, with sensitivity exceeding 0.79. These findings highlight the potential of CV data to support scalable crash prediction without relying on infrastructure-based sensors, especially as CV adoption expands. The proposed approach offers a robust and adaptable solution for enhancing roadway safety across diverse traffic environment.]]></description>
      <pubDate>Tue, 10 Mar 2026 09:56:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633648</guid>
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    <item>
      <title>Interim Traffic Monitoring System on U.S. 59 (Eastex) Freeway: Year One Report</title>
      <link>https://trid.trb.org/View/2570739</link>
      <description><![CDATA[Monitoring freeway traffic conditions in construction zones is difficult. A 17.7 kilometer (11 mile) section of U.S. 59 (Eastex) Freeway from I-610 North Loop to Beltway 8 North in Houston, Texas is under construction and was chosen for this demonstration project. The selected sensor technologies were the Doppler Radar and side-fire microwave ranging. Wooden utility poles installed near the freeway lanes provided sensor placements. Mobility of the sensor is paramount. At report time, the equipment had been purchased, an electrical contractor chosen, and equipment was being installed.]]></description>
      <pubDate>Tue, 26 Aug 2025 14:34:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2570739</guid>
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    <item>
      <title>Status Report on Operations from September 1996 to August 1997: Final Report</title>
      <link>https://trid.trb.org/View/2549175</link>
      <description><![CDATA[Four alternative (to loop detection) sensor types were tested in freeway construction areas in Houston, Texas. The Whelen Doppler radar units, once attuned to the local conditions, appear to render acceptable speed measures. The side fire microwave ranging sensor (R TMS from EIS) appears to be very suspectable to creating multiple reflections when exposed to hard vertical surfaces (as found in concrete median barriers, abbreviated as CMB). The TraffiCam is a visual imaging device known primarily as an inexpensive, publicly available VIVDS product. Based on the performance of the unit tested, the software and hardware requires substantial improvements before utilization as an acceptable freeway alternative detector. The SmartSonic sensors were installed in an advantageous position for passive monitoring of two lanes of traffic, one sensor per lane. The short-term test indicated that occlusion occurs in sonic as well as VIVDS devices. The Sonic sensor would work best when positioned directly over the lane. The many calibration parameters and expansive range limits may confuse the operator before acceptable volume and speed measures for three length vehicle classes.]]></description>
      <pubDate>Wed, 25 Jun 2025 14:47:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2549175</guid>
    </item>
    <item>
      <title>Expressway Data De-Noised Approach Based on Wavelet Analysis</title>
      <link>https://trid.trb.org/View/2203887</link>
      <description><![CDATA[Compared with traditional collection methods using detectors or sensors, floating-car data collection has advantages such as a broad coverage area, low cost installation and maintenance costs and little influence from external sources. Therefore, floating-car data are being broadly applied in traffic relative studies. Traffic original data usually contain some random components, which disturb the distinction of traffic status. The original data must be de-noised in order to filter these random components. This paper presents wavelet analysis to de-noise the original data from floating-car data collection. In this paper, the data from RTMS (Remote Traffic Microwave Sensor) collection are treated as true data. Traffic original data, from various ring mainlines of Beijing on various days, are processed through wavelet threshold de-noising. The experiment results show that de-noised data are better than the original data in terms of evaluation indexes. For example, mean squared error (MSE) of the de-noised data can drop as low as 6.36% and the correlation coefficient can be increased by more than 1.18%.]]></description>
      <pubDate>Mon, 05 Aug 2024 10:47:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2203887</guid>
    </item>
    <item>
      <title>A Real-Time Proactive Intersection Safety Monitoring and Visualization System Based on Radar Sensor Data</title>
      <link>https://trid.trb.org/View/2037232</link>
      <description><![CDATA[Aiming to provide a safe driving environment, transportation agencies have begun monitoring traffic flow, collecting traffic data, and conducting safety analyses by using proactive roadside sensing technologies for decades. These sensing technologies consist of radar sensors, Lidar, and video cameras. However, those safety analyses at an intersection are restricted by a limited data collection time or specific conflict types in a specific traffic scenario. Consistent data collection requires consistent power supplies and/or manual operations and maintenance. In addition, a data processing algorithm in a safety analysis system is developed for only a specific conflict scenario. These restrictions prevent transportation agencies from widely deploying safety applications at any targeted intersection for long-term monitoring. To overcome such limitations, this Innovations Deserving Exploratory Analysis (IDEA) product developed a proactive intersection safety monitoring and visualization system that can be implemented at any kind of intersection for any type of safety and operation analysis under a long-term data collection period. The product, the Intersection Proactive Safety Visualization (IPSV) system, employs a 24GHz Microwave Doppler radar sensor.]]></description>
      <pubDate>Wed, 12 Oct 2022 16:35:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2037232</guid>
    </item>
    <item>
      <title>Fine-Grained Traffic Flow Prediction of Various Vehicle Types via Fusion of Multisource Data and Deep Learning Approaches</title>
      <link>https://trid.trb.org/View/1890118</link>
      <description><![CDATA[Both road users and road administrators are keen to know traffic flow of fine-grained vehicle type. Successful prediction on the traffic flow of heavy, medium and small vehicle could contribute to the improvement of travel safety and efficiency. However, the classification on vehicle type is always not accurate enough using in practice. It could cost a lot to identify from the additional video cameras to cover the full-length of large-scale freeway with high-resolution to capture vehicles clearly. In this paper, empirical data are cleaned, normalized, compensated, filled, decoded and filtered with help of the fusion of vehicle detector data, remote microwave sensors data and toll collection data. The traffic flows of fine-grained heavy, medium and small vehicles are successfully reconstructed. Improved deep belief network (DBN) are then proposed to forecast traffic flow of different types of vehicles in 30-, 60- and 120-minutes time interval. Random-selected road segments on a ring way around a city are trained with data accumulated three months and predict data in the next month. According to prediction error analysis, the proposed method performs better in estimation and forecasting, with respect to the existing methods, especially for longer time prediction and heavy vehicle prediction. It would benefit traffic control to prevent freeway congestion escalation, protect the traffic infrastructure via heavy vehicle control, reduce the road risk, prompt quick emergency response and eventually contributes to more applications for intelligent transportation system (ITS).]]></description>
      <pubDate>Mon, 28 Mar 2022 10:29:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/1890118</guid>
    </item>
    <item>
      <title>CFRP lamella stay-cable and its force measurement based on microwave radar</title>
      <link>https://trid.trb.org/View/1894267</link>
      <description><![CDATA[Carbon Fiber Reinforced Polymer (CFRP) has the advantageous characteristics such as light weight, high strength, high corrosion and fatigue resistances, low creep, and high damping, etc. It is suitable to be used in bridge structures as cables, which can effectively solve the problems of easy rusting, heavy weight, low tensile strength, and low fatigue performance of steel cables. This paper firstly illustrates the advantageous properties of CFRP lamella compared with CFRP rod in terms of cable anchoring, and then investigates the performance of wedge-shaped clamp anchorage for CFRP lamella cable by finite element analysis and static tensile test. Finally, the process of measuring the cable force of CFRP lamella stay-cable with non-contact microwave cable force measurement technology is introduced. The finite element analysis and experiment show that the wedge-shaped clamp anchorage can effectively anchor the CFRP lamella stay-cable with a relatively high anchorage efficiency, and the maximum stress of the CFRP lamella stay-cable is at the free section instead of the anchorage section, and the failure pattern is mainly the fiber explosion of the free section. The results of microwave cable force measurement are consistent with those of the traditional pressure sensor and strain gauge methods. The non-contact microwave cable force measurement technology is easy and fast to operate, and it is suitable for measuring the force of CFRP cable.]]></description>
      <pubDate>Fri, 03 Dec 2021 11:22:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1894267</guid>
    </item>
    <item>
      <title>Innovative Materials and Advanced Technologies for a Sustainable Pavement Infrastructure</title>
      <link>https://trid.trb.org/View/1867280</link>
      <description><![CDATA[It is widely acknowledged that early detection of material damage and timely rehabilitation can lead to a significant reduction in the lifecycle cost of asphalt pavements. This research investigates the capabilities of damage detection and healing of graphite nanoplatelet (GNP)-taconite modified asphalt materials. The first part of the research is concerned with the application of GNP-taconite modified asphalt materials for damage detection using electrical conductivity. It is shown that, as compared to conventional asphalt materials, the GNP-taconite modified asphalt materials exhibit an improved electrical conductivity due to the electron hopping mechanism. Based on the mathematical analogy between the elastostatic field and the electrostatic field, a theoretical model is derived to relate the change of electrical conductivity to the damage extent of the material. Although, in principle, the material damage can be accessed using the electrical conductivity, the practical application of this method is complicated by the fact that the conductivity is influenced by the moisture content. The second part of the research investigates the damage healing capability of GNP-taconite modified asphalt materials heated by microwave. GNP-taconite modified asphalt materials can effectively absorb the heat generated by the microwave, and the rising temperature can effectively heal the microcracks in the binder. This damage-healing mechanism is verified by a set of semi-circular beam tests. Finally, microwave heating technology is applied to the tack coat system. It is shown that, with microwave heating, the GNP-taconite modified asphalt material can effectively improve the bond strength of the interface of the tack coat system.]]></description>
      <pubDate>Wed, 28 Jul 2021 13:45:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1867280</guid>
    </item>
    <item>
      <title>The left-behind human detection and tracking system based on vision with multi-model fusion and microwave radar inside the bus</title>
      <link>https://trid.trb.org/View/1718332</link>
      <description><![CDATA[Left-behind humans inside the car or bus have caused a lot of accidents, so it is essential to detect the humans in vehicle. Current human detection methods rely on wearable devices, oxygen sensors, and special seat designs in vehicles, but those sensors cannot adapt to ever-changing environments. To solve those problems and especially to improve passengers’ safety on the bus, the authors propose a method to accomplishing human detection by fusion vision and microwave radar information in various environments in vehicle. For vision information, the authors use different networks to extract human and human face features, and fusion of the detection results in different models to improve human detection accuracy. The human detection model is MobileNet-V2, and the human face detection model is MTCNN. A new matching schedule and tracking objects management rule based on the Kernelized Correlation Filter tracker are designed to track the human and human face detection boxes. The microwave radar information is used to detect moving objects. Finally, the fusion vision and microwave radar detection results are implemented. Experiments show that the authors' method has improved the human detection accuracy in vehicle, and this method can be used for detection of left-behind children on the school bus.]]></description>
      <pubDate>Wed, 22 Jul 2020 14:40:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/1718332</guid>
    </item>
    <item>
      <title>Advanced Camera Lowering Device for ITS Maintenance</title>
      <link>https://trid.trb.org/View/1659693</link>
      <description><![CDATA[The California Department of Transportation (Caltrans), in an effort to satisfy mandated Intelligent Transportation System (ITS) performance goals and consistency with MAP-21 performance management targets, is deploying an increasing number of Closed-Circuit TV (CCTV) cameras to monitor traffic and conditions on California’s roadways. These CCTV cameras are typically mounted along the highway on top of high poles and need to be accessed periodically for service and repair to keep these sophisticated systems functional. Many of these Caltrans camera system sites are difficult to access due to traffic hazards, roadside obstacles, and greater pole heights. Challenging access sites like these require additional time, cost, and exposure to unsafe conditions, which can contribute to delayed or deferred camera maintenance and repairs. Caltrans is expanding their application of pole-mounted Camera Lowering Devices (CLDs) systems in an effort to facilitate access to these problematic camera sites. Caltrans commonly deploys Halo-style CLD products. This research introduces Caltrans to the use of a detachable type of CLD product that offers additional benefits, such as eliminating the potential of binding, reducing communication cabling requirements, allowing the mounting of ancillary items such as antennas and microwave vehicle detection systems (MVDS), and supporting the retrofitting of existing camera poles. This research project supports the deployment and evaluation of both an internal and external MG2 CLD systems on Caltrans highways. This report documents the installation, training, and performance of these research MG2 systems in association with Caltrans District 3 Maintenance and Transportation Management Center (TMC) personnel. These MG2 CLD systems have proven to be easy to use, performed effectively, and provide significant cost and safety benefits to Caltrans maintenance when accessing ITS camera systems on the highway. Based on the successful deployment of these MG2 CLD systems, it is the recommendation of this report that Caltrans consider the qualification and expanded use of the MG2 CLD systems in the future.]]></description>
      <pubDate>Thu, 31 Oct 2019 17:02:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1659693</guid>
    </item>
    <item>
      <title>Microwave Technique for Liquid Water Detection in Icing Applications</title>
      <link>https://trid.trb.org/View/1631230</link>
      <description><![CDATA[The partial melting of ingested ice crystals can lead to ice accretion in aircraft compressors, but accurately measuring the relatively small fraction of liquid water content in such flows is challenging. Probe-based methods for detecting liquid water content are not suitable for deployment within turbofan engines, and thus alternatives are sought. Recent research has described approaches based on passive microwave sensing. We present here an approach based on active microwave transmission and reflection, employing a vector network analyzer. Utilization of both transmission and reflection provides additional data over and above emission or transmission only, and permits a more controllable environment than passive sensing approaches. The paper specifically addresses the question of whether such an approach is viable within the context of representative icing wind tunnel and engine flow conditions. A quasi-thermal equilibrium approach is presented herein to estimate the melting ratio during microwave analysis of samples at 0 °C. Experimental results using microwaves in the 2.45GHz region are presented, and post-processing methods investigated. This is followed by an investigation of detection limits for ice accretion in the sub-gram range. The results indicate the potential of the technique, with a number of avenues evident for further research.       ]]></description>
      <pubDate>Thu, 27 Jun 2019 14:41:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1631230</guid>
    </item>
    <item>
      <title>Comparison of Different Radar Technologies and Frequencies for Road Pavement Evaluation</title>
      <link>https://trid.trb.org/View/1563124</link>
      <description><![CDATA[Experimental asphalt pavement field measurements have been performed with a commercial Ground Penetrating Radar (GPR) system and with three dedicated, new prototype radars operating at 1–2 GHz, 12–18 GHz and 32 GHz frequency. The aim of these measurements is to find the surface or near-surface permittivity of worn asphalt and to investigate the suitability of various radar technologies for this task. The experiments were supplemented by drill core samples extracted at selected interesting locations on a test road. As expected, there is hardly any correlation between the results of the four different radars along the same test track, and drill core results complicate the situation further. Taking 10 and 90 percentile cumulative probabilities, the commercial GPR data has the smallest εr′ span from 5 to 5.6, the 1–2 GHz prototype system indicates εr′ between 4.5 and 5.5, the authors' 12–18 GHz system 4.5 to 6.5 and the 32 GHz fixed frequency reflectometer 2.5–4.5. Only the 32 GHz measurements show clearly different mean permittivity values for the visually different pavement surfaces. Test results, however, suggest that extracting air void variation from highly inhomogenous asphalt pavement needs stochastic approach instead of trying to do some deterministic calibrations with pavement cores.]]></description>
      <pubDate>Mon, 26 Nov 2018 16:55:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1563124</guid>
    </item>
    <item>
      <title>Statistical Analysis of SSMIS Sea Ice Concentration Threshold at the Arctic Sea Ice Edge during Summer Based on MODIS and Ship-Based Observational Data</title>
      <link>https://trid.trb.org/View/1509884</link>
      <description><![CDATA[The threshold of sea ice concentration (SIC) is the basis for accurately calculating sea ice extent based on passive microwave (PM) remote sensing data. However, the PM SIC threshold at the sea ice edge used in previous studies and released sea ice products has not always been consistent. To explore the representable value of the PM SIC threshold corresponding on average to the position of the Arctic sea ice edge during summer in recent years, the authors extracted sea ice edge boundaries from the Moderate-resolution Imaging Spectroradiometer (MODIS) sea ice product (MOD29 with a spatial resolution of 1 km), MODIS images (250 m), and sea ice ship-based observation points (1 km) during the fifth (CHINARE-2012) and sixth (CHINARE-2014) Chinese National Arctic Research Expeditions, and made an overlay and comparison analysis with PM SIC derived from Special Sensor Microwave Imager Sounder (SSMIS, with a spatial resolution of 25 km) in the summer of 2012 and 2014. Results showed that the average SSMIS SIC threshold at the Arctic sea ice edge based on ice-water boundary lines extracted from MOD29 was 33%, which was higher than that of the commonly used 15% discriminant threshold. The average SIC threshold at sea ice edge based on ice-water boundary lines extracted by visual interpretation from four scenes of the MODIS image was 35% when compared to the average value of 36% from the MOD29 extracted ice edge pixels for the same days. The average SIC of 31% at the sea ice edge points extracted from ship-based observations also confirmed that choosing around 30% as the SIC threshold during summer is recommended for sea ice extent calculations based on SSMIS PM data. These results can provide a reference for further studying the variation of sea ice under the rapidly changing Arctic.]]></description>
      <pubDate>Tue, 19 Jun 2018 09:34:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1509884</guid>
    </item>
    <item>
      <title>Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors</title>
      <link>https://trid.trb.org/View/1487058</link>
      <description><![CDATA[Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks.]]></description>
      <pubDate>Tue, 28 Nov 2017 09:19:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1487058</guid>
    </item>
    <item>
      <title>3D Microwave Camera for Concrete Delamination and Steel Corrosion Detection (SN-4)</title>
      <link>https://trid.trb.org/View/1482775</link>
      <description><![CDATA[Corrosion of embedded steel reinforcement in concrete leads to concrete cracking and delamination, followed by increased salt and moisture permeation and further damage. Invisibility of the embedded rebar in combination with physical inaccessibility in elevated bridges presents a challenge in the assessment of RC bridge elements. Wideband (3D) microwave synthetic aperture radar (SAR) imaging techniques that can be integrated into a robot or UAV offer a potential practical solution to overcome this challenge.
Microwave SAR imaging acquires wideband data over a 2D spatial grid by raster (or electronic) scanning a reflectometer - real-time images. Our recently-developed microwave camera can produce 3D SAR images at 30 image frames per second (see https://youtu.be/mK_zU-GHxRA). This 45-N microwave camera operates at a frequency range of 20-30 GHz and has an aperture size of 130 x 165 mm. Similar but lighter systems can be designed with aperture size and frequency range optimized for imaging of concrete in bridges and pavements. When mounted on a robot or UAV, microwave cameras can cover a wide area of infrastructure as SAR imaging has been for terrain mapping and remote sensing.  However, the position tracking accuracy requirement must be more stringent for SAR imaging in NDE applications. The higher accuracy can be achieved in multiple ways (e.g. a more precise positioning device (laser) and a small optical camera). A recent study of concrete specimens with relatively high moisture and high chloride levels indicated great potential of 3D imaging to detect corrosion of the embedded steel bars in concrete. The 2D slice of a 3D image showed two corroded steel bars, embedded at 25 mm deep. 
Approach and Methodology: Microwave signals can propagate through concrete and be reflected by steel reinforcing bars, delamination and voids. They are attenuated by moisture, ionic solution, and corrosion by-products. The principle of microwave SAR imaging in NDE applications has been well-documented. A wideband antenna is used to scan a bridge element surface following a 2D grid of certain step (sub-Nyquist sampling rate for reduced measurement time). Using a uniquely-designed and patented reflectometer, the collected reflected data (reference to aperture of the antenna) is then fed to a custom 3D SAR imaging algorithm. The resulting image resolution depends upon the overall scanned area dimension, the wavelength inside materials, and the standoff distance. Higher frequencies (or shorter wavelength) render images with higher 3D resolution depending on the operation frequency, bandwidth and the permittivity of the material.

Overall Objectives: This project aims to develop and optimize a 3D microwave camera for bridge inspection on a robot or UAV platform, quantify its performance for steel corrosion evaluation and concrete delamination detection in RC bridge elements, and build a microwave camera prototype that can be installed on a UAV for field applications.

Scope of Work in Year 1: (1) Prepare concrete specimens with embedded reinforcing bars, (2) Evaluate corrosion rate or mass loss of rebar in 3.5wt.% NaCl solution with EIS tests over time, (3) Periodically take the specimens out of the solution and scan them (for processing 3D images) at various relative humidity levels (measured) to quantify the effect of moisture on delamination, and (4) Optimize critical design parameters of 3D microwave cameras for high fidelity and spatial resolution.

Scope of Work in Year 2: (1) Use laboratory-designed imaging probes and especially-prepared concrete specimens (with delamination and cyclically-corroded rebar) to determine optimal operating frequency, bandwidth, scanning approach (i.e., uniform vs. non-uniform and mono-static vs. bi-static) for each type of damage in order to optimize these critical design parameters for producing images with high fidelity and spatial resolution, (2) Perform numerical full-wave electromagnetic simulations to corroborate and further optimize findings in the previous task, (3) Evaluate and investigate the trade-off between a UAV and a climbing robot platform for microwave imaging system installation, and (4) Investigate commercially-available systems for providing critical geometrical information for the imaging system needed for proper SAR image production. 

Scope of Work in Year 3: (1) Perform experimental laboratory optimization for determining optimal frequency, bandwidth and scanning configuration and the influence of these parameters on such an imaging system characteristics for concrete delamination detection and steel rebar corrosion evaluation in reinforced concrete (RC), (2) Perform limited and pertinent numerical electromagnetic simulations by which to also electromagnetically-optimize those measurement parameters for corroborating and further enhancement of the measurement parameters determined in (1), (3) Design and build a suitable antenna with operational frequency bandwidth that spans from several hundred MHz to a few GHz (e.g., 250 MHz – 4 GHz) since the conflicting penetration depth and resolution criteria must be optimized, (4) Design a transceiver system for the imaging system to incorporate the antenna into it (as a single antenna or a linear array fashion), (5) Investigate issues related to a mobile platform movement and its effects on SAR image data collection and determine methods by which to account for, reduce or remove any such unwanted effects, and (6) Begin performing in-field measurements of some bridges.


]]></description>
      <pubDate>Thu, 14 Sep 2017 21:48:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1482775</guid>
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