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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.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>
    <image>
      <title>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Assessing Residual Strength of Post-Tensioned Elements with Corrosion-Induced Tendon Failure</title>
      <link>https://rip.trb.org/View/2652073</link>
      <description><![CDATA[The research team will assess the residual strength of post-tensioned (PT) bridge elements with corrosion-induced tendon failures to support the Texas Department of Transportation's (TxDOT) maintenance and evaluation efforts. The research team will develop recommendations for assessing structural capacity and identifying effective maintenance strategies. Experimental testing will be conducted in two phases to evaluate corrosion-induced bond degradation and tendon corrosion effects near the anchor points. These tests will evaluate bond degradation, stress redistribution, and failure mechanisms for strand configurations that are either centrally aligned or offset to one side of the tendon. The research team will also perform an analytical study using finite element modelling to simulate corrosion scenarios and validate structural performance. The research team will develop practical guidelines for Receiving Agency engineers, including assessment methodologies and maintenance recommendations.]]></description>
      <pubDate>Fri, 09 Jan 2026 16:32:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652073</guid>
    </item>
    <item>
      <title>Multi-Sensory System for Railway Track Defect Detection </title>
      <link>https://rip.trb.org/View/2646942</link>
      <description><![CDATA[Railway transportation is essential for moving passengers and freight across the U.S., but accidents continue to pose serious safety and economic risks. In 2022 alone, there were about 950 rail-related fatalities and 6,400 injuries nationwide. While human error and reckless behavior are major contributors, defective track infrastructure is a significant and preventable cause of accidents. Railway tracks are complex systems consisting of steel rails, crossties, fasteners, and ballast, all subject to heavy loads, temperature fluctuations, and environmental impacts. These stresses lead to issues such as broken rails, cracked or spalled crossties, loose or missing fasteners, geometry defects, and cross-level variations. Extreme weather conditions can further cause rail buckling or fracture. Failures in these components can trigger derailments, collisions, hazardous material spills, and major service disruptions. Although manual inspections and specialized vehicles are used, many defects go undetected between inspection cycles. Traditional manual inspections, although reliable for identifying visible rail defects, are labor-intensive and limited in scalability. To improve efficiency, various nondestructive testing (NDT) technologies, such as infrared imaging, acoustic emission, ultrasonic, and electromagnetic techniques, have been used primarily for internal defects. As surface defects become more prevalent, various methods have also been developed for detecting surface-level flaws, which can be broadly categorized into three approaches: static monitoring where sensors at fixed locations provide localized coverage; inspection trolleys which integrate sensors generally in the laboratory setting; and onboard sensing systems which enable real-time detection ahead of moving trains but suffer from high cost with varying imaging quality under different weather and lighting conditions. The primary objective of this project is to develop a comprehensive but low-cost multi-sensory system for railway track defect detection. The system will integrate binocular stereovision cameras, Global Navigation Satellite System / Global Positioning System (GNSS/GPS), and IMU sensors. The scope of this project includes development of a multi-sensory system including controller and field data acquisition, development of real-time data fusion and detection algorithms, and recommendations for system deployment on railway tracks. ]]></description>
      <pubDate>Mon, 05 Jan 2026 23:04:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2646942</guid>
    </item>
    <item>
      <title>Damage Progression of Highway Bridges and Operational Vibration-Waveforms
</title>
      <link>https://rip.trb.org/View/2627353</link>
      <description><![CDATA[The dynamic response of civil structures has long been utilized in damage detection. Techniques such as vibration-based damage identification, usually focused on experimentally determining modal parameters, have shown promising applications in detecting damage on bridges. A major drawback of most current damage-detection techniques, including the current video-based approach using drones, is their inability to explain the cause or the condition under which certain types of damage occur at different locations on the bridge. In this work, a nondestructive vibration-based approach, operational response and waveform analysis (ORWA), will be used to determine a cause and possible prevention solutions to the local damage occurring on bridges. In ORWA, damage on a bridge is correlated to the structural motions that are generated by the operational crossing traffic. By identifying the type and speed of vehicles that can put the bridge in deformation modes that can cause detrimenttal damage when they cross the bridge, new mitigation, maintenance, and (potentially) traffic rules can be developed to reduce these effects. In a previous work supported by the Iowa Department of Transportation, the initial idea of ORWA was presented and tested on a single-span highway bridge. A modified form of ORWA was developed and used finite element analysis to correlate traffic vibration waveforms with the modal response of the bridge. In this work, ORWA will be enhanced to include a camera-based system that would be integrated and synched with the vibration waveform measurements. The newly developed ORWA will be tested and validated on two bridges in Iowa.

]]></description>
      <pubDate>Wed, 19 Nov 2025 14:42:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2627353</guid>
    </item>
    <item>
      <title>Simplified Calculation of Liner and Soil Deformations in Tunnels Subjected to Internal Explosions (UTI-UTC 34)
</title>
      <link>https://rip.trb.org/View/2543427</link>
      <description><![CDATA[This project aims to develop a simplified analytical framework for evaluating the structural response of tunnel liners and surrounding soil systems subjected to internal explosive loads. By applying a single-degree-of-freedom (SDOF) model integrated with Winkler foundation principles, the research provides a practical and efficient method for estimating deformation behavior without the need for full-scale numerical simulations. The framework accounts for varying explosive intensities, tunnel geometry, and material properties to predict the extent of structural damage and ground-structure interaction. Validation is conducted through comparisons with experimental data and higher-fidelity simulations. The outcomes of this project contribute to improving the design and resilience assessment of underground transportation tunnels, especially in scenarios involving accidental or intentional explosive threats.
]]></description>
      <pubDate>Wed, 07 May 2025 17:05:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543427</guid>
    </item>
    <item>
      <title>Topological Data Analysis and Track Geometry Data</title>
      <link>https://rip.trb.org/View/2446876</link>
      <description><![CDATA[Rail geometry defects constitute a major cause of accidents in the United States. Geometry related accidents are often very severe and damaging. While rail geometry-caused derailments continue to increase according to Federal Railroad Administration (FRA) safety data, track quality analysis remains effectively unchanged. The use of TQI or track quality index takes a narrow view of track assessment by focusing on quality without considering safety. The bipartite analysis of track quality and safety results into two maintenance types: routine and corrective maintenance respectively. This report shows how to create a hybrid index that combines both element of safety and geometry quality to predict only one maintenance regime based on track condition. It is an initial step towards the big picture of creating indices that will be iterated based on maintenance savings and defect probability thresholds. This study employs a linear and nonlinear dimension reduction technique that expresses the probability distribution of observations based on the similarity or dissimilarity in their embedded space whilst also maximizing the variance in data. This study found application in principal component analysis (PCA) and T-Stochastic neighbor embedding (TSNE) for separating geometry defects from higher dimensional space to lower dimensions. Results show that while both techniques effectively reduces track geometry data, PCA yields a potential defect probability threshold in spite of TSNE being a better geometry defect predictor.
This study employs a linear and nonlinear dimension reduction technique that expresses the probability distribution of observations based on the similarity or dissimilarity in their embedded space whilst also maximizing the variance in data.
]]></description>
      <pubDate>Tue, 29 Oct 2024 15:25:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/2446876</guid>
    </item>
    <item>
      <title>Fast and Efficient Welding Inspection of Structural Steel Using Adaptive Phased Array Ultrasonic NDT</title>
      <link>https://rip.trb.org/View/2342179</link>
      <description><![CDATA[The purpose of this study is to conduct a comprehensive assessment towards a technical guideline and recommendations for fast and efficient ultrasonic non-destructive testing (NDT) methodology and procedure for full inspection of welding and weldment in steel structures based on phased array ultrasonic testing (PAUT) technique. The study aims to provide information toward understanding the potential types of defects and flaws in weldment of steel structures, the significance of effect of flaws on quality of the welding and importance of their detection and assessment. The current ultrasonic NDT techniques will be evaluated for their performance in required welding inspection. Ultimately, the goal is to study the advanced PAUT technique as a potential NDT method for efficient and accurate welding inspection in steel structures for GDOT.  ]]></description>
      <pubDate>Wed, 21 Feb 2024 08:16:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2342179</guid>
    </item>
    <item>
      <title>Understanding Causes of Concrete Culvert Pipe Joint Separation</title>
      <link>https://rip.trb.org/View/2244263</link>
      <description><![CDATA[Nearly 80% of culverts in Minnesota are concrete pipes. The most common distress affecting these culverts is joint separation between culvert segments. This may allow water and soil to seep through the pipe, which can lead to loss of soil support; this type of distress may ultimately result in roadway settlement and failure of the pipe. However, the cause of joint separation is unclear, so mitigation and construction practices that would minimize this problem have yet to be proposed. Thus, the purpose of this research is to determine the likely causes of joint separation in concrete culverts. The research will include a field survey of concrete pipes that exhibit joint separation, and correlations between joint separation and relevant site and structural conditions will be established. The field observation data will be supplemented by detailed geotechnical and live load test data from ten concrete culverts examined as part of an existing MnDOT implementation project related to live load distribution in reinforced concrete culverts. Computational models of the culverts will be developed to examine how the structure responds to traffic live loading, differential settlement, freeze-thaw of water in the joint, or swelling of freezing fine soils (e.g., silts and clays).]]></description>
      <pubDate>Tue, 12 Sep 2023 12:02:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2244263</guid>
    </item>
    <item>
      <title>Assessment of Nondestructive Examination and Condition Monitoring Technologies for Defect Detection in Non-Metallic Pipe</title>
      <link>https://rip.trb.org/View/2093146</link>
      <description><![CDATA[The project will quantify the ability of several NDE methods for detection, sizing and characterization of defects, damage, and anomalies that may occur in non-metallic pipe.]]></description>
      <pubDate>Tue, 03 Jan 2023 13:53:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2093146</guid>
    </item>
    <item>
      <title>Multi-modal NDE Assisted Probabilistic Pipeline Performance Evaluation under Interactive Anomalies</title>
      <link>https://rip.trb.org/View/2085761</link>
      <description><![CDATA[The proposed project will focus on multi-modal non-destructive evaluation (NDE) and probabilistic performance evaluation of aging pipelines under interactive threats. This study will utilize the experimental testing and numerical analysis to generate more realistic defect shapes and colony profiles, which will be used for characterization and validation of interactive defect NDE.]]></description>
      <pubDate>Fri, 16 Dec 2022 14:15:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/2085761</guid>
    </item>
    <item>
      <title>Structural Monitoring of Steel-Member Bridges with Fatigue Life Prognosis due to Dynamic Vehicular Loads </title>
      <link>https://rip.trb.org/View/2055938</link>
      <description><![CDATA[This project will develop an integrated hardware and analytical framework that enables real-time bridge structural monitoring and remaining fatigue life estimation.  PI Wang has over 20 years of experience in structural dynamics and wireless structural monitoring.  His research group has co developed a modular wireless sensing device that can perform high-rate data acquisition. The Martlet smart wireless sensing system is particularly designed for civil structural applications.  Building blocks of this system are individual wireless sensing units.  With solar power, each wireless unit can collect data from various analog sensors, such as strain gages, string potentiometers, accelerometers, etc.  Cost of the wireless system is only a fraction of conventional cabled sensing systems.  The system is also capable of routing data through cellular network.  
This project will develop an integrated hardware and analytical framework that enables real time bridge structural monitoring and fatigue life prognosis.]]></description>
      <pubDate>Thu, 03 Nov 2022 10:06:09 GMT</pubDate>
      <guid>https://rip.trb.org/View/2055938</guid>
    </item>
    <item>
      <title>Repair of Bridge Deck Fascias</title>
      <link>https://rip.trb.org/View/1993817</link>
      <description><![CDATA[The deck fascia on bridges deteriorates more quickly than other portions of the bridge. This causes the fascia concrete to become debonded from the reinforcement and over time concrete can spall off the fascia. These spalled pieces of concrete can fall onto traffic lanes or pedestrian walkways posing a safety risk to the public. The current maintenance strategy has limitations. The current practice is not to patch these areas, overhead patches can spall off posing a safety risk, and there is not a method to anchor false decking in these area. Delaminated concrete can be removed to prevent debris from falling unexpectedly, but when reinforcement is left exposed it leads to increased degradation of the bridge deck fascia and traffic barrier. Over time continually scaling these areas can cause the traffic barrier to become undermined without any option for repair. These current methods lead to the need for continual scaling in these areas.]]></description>
      <pubDate>Thu, 14 Jul 2022 12:38:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/1993817</guid>
    </item>
    <item>
      <title>A Review of Protocols Used for Evaluating Defective Asphalt Materials and Pavements</title>
      <link>https://rip.trb.org/View/1905101</link>
      <description><![CDATA[This project will evaluate the current practices and procedures used by the Department to evaluate defective asphalt material. Defective material is defined in Section 334 and 337 of the FDOT Standard Specifications for Road and Bridge Construction. For dense graded mixtures (including dense graded friction courses), material is considered defective if the air voids, density, asphalt binder content, or percent passing the #200 sieve fall outside of the master production ranges defined in Section 334. For open graded friction course mixtures, material is considered defective if the asphalt binder content, percent passing the 3/8-inch sieve, percent passing the #4 sieve, or percent passing the #8 sieve fall outside of the master production ranges defined in Section 337.]]></description>
      <pubDate>Fri, 21 Jan 2022 11:49:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/1905101</guid>
    </item>
    <item>
      <title>The Feasibility of Promoting Local Rail Vibrations Using Electromechanical Impedance Method</title>
      <link>https://rip.trb.org/View/1890169</link>
      <description><![CDATA[The mission of this project is to serve the rail industry by improving infrastructure safety and reliability with minimized risks of internal rail defects and rail thermal buckling. The team will develop an electromechanical impedance (EMI) measurement system to promote local rail vibrations, which were recently found to be promising tools for both rail structural integrity inspection and RNT estimation.

The local rail vibrations are the vibrational modes that are easy to promote, highly localized, and immune from boundary conditions. The fundamental mechanism of this phenomenon is deeply rooted from guided wave propagation in rails. Previously, local rail vibrations were promoted by impulse excitation, such as impactor and pulse laser, which lack a control flexibility on input energy and frequency. The team proposes to investigate the usage of EMI method for a consistent local rail vibration promotion, and successfully conducted preliminary numerical simulation to prove its feasibility. The proposed mission will be accomplished by developing an innovative capability of consistent excitation and detection of local rail vibrations, and advancing the state-of-the-art of rail defect detection rail neutral temperature (RNT) measurement.]]></description>
      <pubDate>Thu, 04 Nov 2021 14:50:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1890169</guid>
    </item>
    <item>
      <title>Earthquake-Induced Damage Classification of Bridges Using Artificial Neural Networks</title>
      <link>https://rip.trb.org/View/1762371</link>
      <description><![CDATA[Fragility analysis is currently used to develop a probabilistic seismic demand model with an assumed lognormal distribution and then determine the probability of exceeding certain seismic demand thresholds for various states of damage. Due to the complexity in probability calculations, the seismic demand is often defined by one intensity measure of the earthquake ground motion such as peak ground acceleration, and its lognormal distribution has been repeatedly demonstrated inaccurate as the level of damage increases.

This study aims to develop artificial neural networks (ANNs) for a near real-time evaluation of the regional structural damage of a highway bridge network after a catastrophic earthquake. Bridge responses to the earthquake are treated as the earthquake-induced ground motion classifiers for structural damage states. The input and output layers of an ANN represent intensity measures of a ground motion and their corresponding damage state, respectively. To achieve this objective, the scope of work includes: (1) Select representative bridges along a major highway, (2) Collect and organize a big data set of ground motions, (3) Model the representative bridges and evaluate their damage states based on a damage index under the ground motions through time history analysis, (4) Label the ground motions with corresponding damage states and develop a balanced set of training and test data, (5) Train the ANN with the training dataset and evaluate the overall accuracy of damage prediction using unseen test dataset, (6) Optimize the ANN architecture for robust and accurate performance by ranking the importance of various intensity measures, comparing two structural damage indices, and considering varying numbers of hidden layers and neurons, and (7) Evaluate the performance of the ANNs for existing bridges along an emergency designated route with practical considerations of three intensity measures availed in the American Association of State Highway and Transportation Officials (AASHTO) Guide Specifications for Load and Resistance Factor Design (LRFD) Seismic Bridge Design.]]></description>
      <pubDate>Thu, 07 Jan 2021 14:07:40 GMT</pubDate>
      <guid>https://rip.trb.org/View/1762371</guid>
    </item>
    <item>
      <title>SPR-4526: Predictive Analytics for Quantifying the Long-Term Cost of Defects During 
Bridge Construction</title>
      <link>https://rip.trb.org/View/1739234</link>
      <description><![CDATA[Inspecting bridges during construction and in service, and ensuring quality construction prior to acceptance and proper maintenance, are critical to the lifecycle performance of the structure. The goal of this project is to develop predictive analytics that would allow a more effective asset management. This approach will be demonstrated using concrete bridge decks as an illustrative example. The project will provide the knowledge and tools needed to estimate the costs associated with the consequences of defects occurring during construction (i.e., substandard quality), and weigh those against cost and expected performance of additional measures that can be taken to reduce such defects (e.g., improved inspection procedures).]]></description>
      <pubDate>Wed, 16 Sep 2020 11:23:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1739234</guid>
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