<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <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" />
    <description></description>
    <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>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
    </image>
    <item>
      <title>Linking Landslide Triggering and Runout Hazard with Surface Deformations for Optimized Infrastructure Systems Resiliency</title>
      <link>https://rip.trb.org/View/2726550</link>
      <description><![CDATA[Landslides are one of the most significant geohazards impacting North Carolina's transportation network, causing fatalities, property loss, and long-term economic disruption. These events are frequently triggered by extreme precipitation from hurricanes and tropical storms, which have historically produced hundreds to thousands of debris during a single event. For example, Hurricane Helene (2024) triggered more than 2,000 reported landslides across the Southern Appalachians, resulting in widespread road closures, bridge damage, and tens of billions of dollars in direct and indirect losses. As the frequency and intensity of extreme precipitation events increase, the risk of cascading infrastructure failures is expected to grow. Current North Carolina Department of Transportation (NCDOT) Geotechnical Asset Management (GAM) tools primarily operate reactively— tracking known unstable sites and coordinating post-disaster repairs. Therefore, there is a critical need for proactive capabilities to anticipate landslide hazards before they disrupt the network.

The objective of this project is to create a robust, scalable, and computationally efficient framework to predict landslide triggering and runout at a regional scale, supporting optimized maintenance, emergency response, and risk-informed investment decisions. This work will integrate the North Carolina Geological Survey (NCGS) Post-Helene Landslide Inventory, surface deformation mapping, and AI enhanced triggering predictions. The research will pursue four main objectives: (1) consolidate and curate a high-quality georeferenced dataset of landslide and debris flow events in North Carolina; (2) develop machine-learning models informed by physics to predict triggering susceptibility based on rainfall thresholds, slope geometry, and hydrologic conditions; (3) link surface deformation signals to slope stability through finite-element-based surrogate models; and (4) compute landslide runout using depth-averaged Material Point Method (DA-MPM) simulations that account for three-dimensional topographic effects and infrastructure exposure.

The approach follows a hierarchical and computationally efficient workflow. Regional-scale data-driven models will rapidly screen the entire state for slopes with high triggering potential. For these critical sites, limit equilibrium analysis (LEA) using existing NCGS models will identify likely failure surfaces and factors of safety. The outputs will serve as inputs to physics-based DA-MPM simulations that predict debris flow runout, impact zones, and potential consequences for NCDOT-managed assets. This strategy maximizes coverage while focusing on high-fidelity simulations where they are most needed, thereby balancing predictive power with computational cost.

The anticipated products include trained machine-learning models, enhanced infinite-slope analysis incorporating AI training, a verified and validated DA-MPM module, and geographic information system (GIS)-integrated hazard/risk maps. Integration into NCDOT's existing GAM system will enable decision-makers to: (i) develop watchlists of critical slopes, (ii) anticipate maintenance and debris removal needs, (iii) coordinate detour planning and emergency response, and (iv) communicate risk more transparently to stakeholders. Training workshops will be held with NCDOT and NCGS engineers and geologists to ensure usability and gather feedback for future system enhancements.

This project represents the first step toward a real-time, data- and physics-informed landslide early warning and infrastructure risk management system. By combining machine learning, geotechnical modeling, and large-deformation simulation, this work will strengthen North Carolina's landslide risk assessment and improve transportation resiliency, reduce lifecycle maintenance costs, and protect the safety and mobility of the traveling public.]]></description>
      <pubDate>Thu, 09 Jul 2026 09:02:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2726550</guid>
    </item>
    <item>
      <title>Investigation of Using Higher Fines Backfill Materials in the Design and Construction of Mechanically Stabilized Earth Walls in Georgia
</title>
      <link>https://rip.trb.org/View/2719309</link>
      <description><![CDATA[The main objectives of this research project are: (1) examine the impact of gradation and fine content on the permeability, density, and shear strength of backfill materials, as well as soil-reinforcement interactions; (2) conduct a cost comparison analysis between Mechanically Stabilized Earth (MSE) wall design cases using higher fines backfill materials and current Georgia Department of Transportation (GDOT)-approved materials; and (3) perform Finite Element (FE) simulations to determine MSE wall deformation for various backfill materials.
]]></description>
      <pubDate>Thu, 25 Jun 2026 09:44:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2719309</guid>
    </item>
    <item>
      <title>Advanced InSAR–UAV-LiDAR Flood-Deformation Risk Monitoring for Efficient Mobility</title>
      <link>https://rip.trb.org/View/2669656</link>
      <description><![CDATA[El Paso’s critical transportation corridors face compounding risks from ground deformation and flash flooding that can severely disrupt efficient mobility, impede traffic flow, and challenge infrastructure reliability. Such infrastructure disruptions compromise public safety by delaying emergency response access and increase collision risk on compromised roadways. Despite advances in satellite monitoring and hydrologic modeling, no integrated system currently provides transportation agencies with rapid and actionable, near-real-time alerts for combined flood-deformation hazards. This project is designed to support uninterrupted mobility directly by developing and demonstrating a unified monitoring framework that fuses millimeter-precision Interferometric Synthetic Aperture Radar (InSAR) deformation maps with Unmanned Aerial Vehicle–Light Detection and Ranging (UAV-LiDAR) terrain models and Synthetic Aperture Radar (SAR)-derived soil-moisture indices to deliver actionable risk assessments. The research addresses a core challenge in maintaining efficient mobility: predicting when and where infrastructure vulnerabilities will coincide with flood conditions. Using validated Persistent Scatterer (PS) and Small Baseline Subset (SBAS) InSAR processing chains, high-resolution UAV-LiDAR surveys, and machine learning algorithms trained on historical events, the proposed system will provide transportation agencies with advanced warning, which enables proactive response and traffic management. The project will produce a composite flood-deformation risk index with demonstrated 90% accuracy in hazard detection. An edge-computing prototype will be deployed in partnership with the Texas Department of Transportation (TxDOT) to operationalize the fusion algorithms, enabling 24-hour processing turnaround and secure web-based risk visualization. Through formal partnerships with TxDOT and El Paso Water, the system will integrate real-time flow gauge data and infrastructure databases to enhance model calibration and validation. The project includes comprehensive technology transfer components, such as Docker-containerized software, training workshops for state Department of Transportation (DOT) engineers, and a commercialization brief outlining licensing pathways for rapid deployment across additional corridors.  ]]></description>
      <pubDate>Sun, 15 Feb 2026 16:40:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2669656</guid>
    </item>
    <item>
      <title>Understanding Moving/Damage Mechanism of Vehicles under Tornadoes for Enhancing Vehicle/Driver Safety
</title>
      <link>https://rip.trb.org/View/2627651</link>
      <description><![CDATA[Tornadoes have caused catastrophic damage to buildings and vehicles. Although considerable research has been conducted on the performance of buildings under tornadoes, the performance of motor vehicles (e.g., cars, pickups, vans, and box trucks) under tornadoes was rarely studied. Unfortunately, about 15% of tornado fatalities during 1975–1995 were attributed to the moving or damage of motor vehicles and about 9% during 1985-2015. To protect motor vehicles from being damaged by tornadoes and accordingly to reduce tornado fatalities, the objective of this project is to understand the moving/damage mechanism of motor vehicles (e.g., sliding, flipping and lofting) under tornadoes using systematic computational fluid dynamics (CFD) simulations, which will be verified and validated by the PI’s large-scale laboratory tornado simulator. To achieve the stated research objective, three research tasks have been planned. The proposed research will answer the following five research questions. 1) What tornado intensity can cause a vehicle to slide, flip and loft, respectively? 2) What role does atmospheric pressure drop at tornado center play in initiating each vehicle motion? 3) What role does turbulence in tornadic wind field play in initiating each vehicle motion? 4) Does internal pressure inside a motor vehicle play any role in vehicle moving? and 5) What potential modifications can be made to motor vehicles in order to defer the initiating of each vehicle motion? The research findings can not only help regular vehicles in the parking lot or on the road experience less damage, but also can be integrated into autonomous vehicles for them to make informed decisions and then take proper actions to reduce the tornado-induced damage. In addition, research findings can be used to improve tornado safety recommendations for drivers on the road.
]]></description>
      <pubDate>Fri, 21 Nov 2025 14:07:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2627651</guid>
    </item>
    <item>
      <title>Evaluating Ballast Performance with Freeze/Thaw Cycles</title>
      <link>https://rip.trb.org/View/2573189</link>
      <description><![CDATA[In seasonally cold regions, railroad tracks are subjected to ice formation under sub-freezing conditions and ice thawing under above-freezing conditions due to significant seasonal temperature fluctuations, posing challenges for the maintenance of ballasted railway tracks and operation safety. Currently, little attention has been given to the impact of ice formation and thawing on the permanent deformation of railroad ballast and incidents due to track stiffness variation have not been reported. This proposed research project will investigate the effect of ice formation and thawing on the permanent deformation of ballast through large-scale triaxial cyclic testing, utilizing a newly developed freezing system to simulate frozen conditions. The results will demonstrate the potential track support variation when ballast is subject to freeze-thaw cycles, under the same loading cycles. The rate of permanent deformation will be related to track settlement and help predict track geometry degradation and optimize track maintenance for enhanced track safety.]]></description>
      <pubDate>Mon, 14 Jul 2025 20:12:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2573189</guid>
    </item>
    <item>
      <title>Feasibility of InSAR for Continuous Monitoring of Ground Deformation and Performance Tracking of Geotechnical Assets</title>
      <link>https://rip.trb.org/View/2487308</link>
      <description><![CDATA[In Minnesota, ground movements (e.g., landslides, land subsidence, etc.) have led to significant damage and disruption to the state’s highway network. These geohazards can lead to lane closures, traffic delays, and emergency repairs. The objective of this research is to develop an automated warning system that can alert Minnesota Department o Transportation (MnDOT) staff of areas where abnormal ground deformation (e.g., landslides, subsidence, and sinkholes) is occurring along Minnesota interstate highways, allowing them to proactively intervene. While predicting these types of events beforehand is difficult, continuous, and accurate monitoring of ground deformation along roads is crucial to identify higher risk areas before they develop into major failures.]]></description>
      <pubDate>Mon, 19 May 2025 11:57:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2487308</guid>
    </item>
    <item>
      <title>Hydro-mechanical analysis of tunneling in saturated ground using an efficient sequential coupling technique (UTI-UTC 22)
</title>
      <link>https://rip.trb.org/View/2543417</link>
      <description><![CDATA[This project aims to enhance the understanding and simulation of the complex interactions between hydraulic and mechanical processes during tunnel excavation in saturated soils. The research focuses on developing an efficient sequential coupling technique to model pore water pressure dissipation and ground deformation, which are critical in ensuring tunnel stability and safety. By leveraging high-order finite difference methods and validated numerical simulations, the project enables detailed analysis of soil behavior under varying stress and seepage conditions. The methodology is designed to accurately capture the temporal and spatial evolution of ground responses during tunneling without incurring the computational cost of fully coupled models. Results from this study provide practical insights for the design and risk assessment of tunneling operations in soft, water-bearing ground conditions, contributing to safer and more efficient underground construction practices.
]]></description>
      <pubDate>Wed, 07 May 2025 18:01:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543417</guid>
    </item>
    <item>
      <title>Mapping Urban Excavation Induced Deformation in 3D via Multiplatform InSAR Time-Series (UTI-UTC 27)
</title>
      <link>https://rip.trb.org/View/2543420</link>
      <description><![CDATA[This project explores the use of advanced Interferometric Synthetic Aperture Radar (InSAR) techniques to map three-dimensional ground deformations caused by urban excavation activities, particularly tunneling. By integrating time-series data from multiple SAR platforms—including UAVSAR, Sentinel-1, and COSMO-SkyMed—the study constructs a comprehensive deformation field that captures vertical and horizontal displacements over time. These remote sensing datasets are validated and fused with ground-based measurements, such as total station and leveling surveys, to improve accuracy and spatial resolution. The resulting 3D deformation models enable precise monitoring of subsidence and uplift phenomena associated with underground construction, offering valuable insights into the effects of excavation on surrounding infrastructure. The research supports the development of more resilient and data-informed urban planning, tunneling design, and risk management strategies.
]]></description>
      <pubDate>Wed, 07 May 2025 17:45:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543420</guid>
    </item>
    <item>
      <title>Physical model to study tunnel squeezing under true-triaxial stress state (UTI-UTC 30)
</title>
      <link>https://rip.trb.org/View/2543423</link>
      <description><![CDATA[This project develops a novel physical modeling framework to investigate the phenomenon of tunnel squeezing in weak or highly stressed rock masses under true-triaxial stress conditions. Tunnel squeezing—characterized by excessive and time-dependent ground deformation around the tunnel perimeter—poses significant challenges to safe and cost-effective tunnel construction. To simulate this behavior, a miniature tunnel boring machine (TBM) is integrated into a true-triaxial apparatus capable of replicating realistic in-situ stress states. The model allows for controlled excavation in synthetic clay-rich rock analogs and incorporates real-time measurement of displacement, strain, and support system response. Experimental data are complemented with analytical and numerical analyses to evaluate failure mechanisms and the interaction between the TBM, tunnel liner, and surrounding ground. The research aims to provide a deeper understanding of tunnel-ground interactions under squeezing conditions and guide the development of robust tunneling strategies and support systems for use in challenging geological environments.
]]></description>
      <pubDate>Wed, 07 May 2025 17:23:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543423</guid>
    </item>
    <item>
      <title>Using InSAR time series analysis to characterize tunnel-induced ground surface deformation (UTI-UTC 40)
</title>
      <link>https://rip.trb.org/View/2543430</link>
      <description><![CDATA[This research project utilizes Interferometric Synthetic Aperture Radar (InSAR) time-series analysis to monitor and characterize ground surface deformation resulting from underground tunneling activities. The primary goal is to enhance the detection and quantification of tunneling-induced settlements and deformations in urban environments. By leveraging satellite radar data from platforms such as Sentinel-1 and COSMO-SkyMed, the study applies Persistent Scatterer (PS) and Small Baseline Subset (SBAS) techniques to detect subtle surface changes over time. These geospatial insights are correlated with construction timelines and geotechnical information to validate the extent and distribution of deformation caused by tunnel boring machines (TBMs). The project demonstrates the viability of integrating InSAR analytics with ground-based measurements to support risk assessment, construction planning, and early warning systems for infrastructure protection in densely built-up areas.
]]></description>
      <pubDate>Wed, 07 May 2025 16:45:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543430</guid>
    </item>
    <item>
      <title>Mechanical Characterizations of Joints in Segmented Tunnel Liners Due to Flexural and Thrust Jack Loading (UTI-UTC 43)
</title>
      <link>https://rip.trb.org/View/2543433</link>
      <description><![CDATA[This project investigates the mechanical behavior of joints in segmented tunnel liners subjected to flexural and thrust jack loading conditions commonly encountered during tunnel construction and operation. Utilizing both experimental testing and numerical modeling, the research aims to understand the load-deformation response and failure mechanisms at segment joints, particularly under combined loading scenarios. The study is based on data and specimen segments from the Chesapeake Bay Tunnel expansion, with testing conducted to evaluate performance under controlled thrust and bending loads. Analytical models are developed and calibrated to replicate observed behaviors, contributing to more accurate predictions of joint behavior. The outcomes of this project will inform the design and construction of more resilient and efficient segmental tunnel linings, supporting improved safety and performance in underground transportation infrastructure.
]]></description>
      <pubDate>Wed, 07 May 2025 15:59:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2543433</guid>
    </item>
    <item>
      <title>Field Performance of Pavements Made with High-Modified Hot Mix Asphalt Mixtures</title>
      <link>https://rip.trb.org/View/2468830</link>
      <description><![CDATA[The objectives of this research project are to: (1) measure the mechanical response to traffic loads of the High-Modified Hot-Mix Asphalt over rubblized concrete base on a portion of the I-215 west belt project near Salt Lake City, Utah, (2) measure the deformation of rubblized base and existing base due to traffic loads (3) document the short-term performance of the pavement system, and (4) verify the models and assumptions used to design this pavement section by comparing the predictions to actual measurements. At the conclusion of this project, Utah Department of Transportation (UDOT) pavement and materials engineers will have a better understanding of the behavior, and thus the applicability, of high modified hot-mix asphalt mixtures to high-value roads.]]></description>
      <pubDate>Mon, 02 Dec 2024 19:25:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2468830</guid>
    </item>
    <item>
      <title>Measuring Field Performance of High-Modified Hot-Mix Asphalt Material over Rubblized Base</title>
      <link>https://rip.trb.org/View/2442177</link>
      <description><![CDATA[High-modified hot-mix asphalt mixtures (High-Mod HMA) have the potential to transform the way pavements are designed, constructed, and maintained. Trial sections have demonstrated the ability of this mix to resist rutting, cracking, and maintain a state of good repair while significantly reducing the cost of construction. A new application of this mix is being planned in Utah. This application involves rubblizing the existing concrete pavement and applying a 6-inch-thick layer of High-Mod HMA on top. This transformative approach to pavement construction repurposes existing materials while leveraging it to provide support to the new structure. However, the design specifies a relatively thin HMA layer for an interstate highway section, making it essential to properly understand and verify its actual behavior to allow for potential nationwide implementation. The expectation for the system is that the rubblized base will provide sufficient stiffness to support the pavement structure, and despite the likelihood of high strains in the asphalt mixture, the high binder content and polymer modification in the new High-Mod HMA will produce a strain-tolerant system. This proposal seeks to measure actual strains and deformation in this pavement and use those values to verify design assumptions and improve the development of a transformative pavement systems.]]></description>
      <pubDate>Sun, 20 Oct 2024 12:40:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2442177</guid>
    </item>
    <item>
      <title>Change: A Resilient Approach for Enhancing Asphalt Pavement Performance under Natural Events</title>
      <link>https://rip.trb.org/View/2363912</link>
      <description><![CDATA[Pavements are strong structures but are subjected to large traffic loading and different atmospheric conditions. Asphalt pavements face problems related to their physical and mechanical characteristics. One of the biggest challenges that asphalt pavement must overcome is its high thermal susceptibility, the relatively low durability and not enough climate resiliency. These problems can result in problems such as permanent deformation at high temperatures, and the expansion-contraction phenomenon trigger the appearance of thermal cracking shortening the durability and resilience of the asphalt pavements. A new recycled-aerogel composite for construction materials, named “RaC”, was developed in the Advanced Pavement Laboratory at Arizona State University (ASU). This novel product includes recycled materials such as crumb rubber particles, oil, fibers, and/or material in the form of aerogel particles or fibers. The recycled-aerogel composite is combined with asphalt binder or asphalt mixtures to yield modified material with improved characteristics. RaC solves shortcomings of asphalt pavements such as high-temperature deformation and thermal cracking making longer-lasting transportation infrastructures. This technology decreases the consumption of raw materials and energy fitting the concept of circular economy. The objective of this project is to thrive in extending the life of asphalt by using recycled materials to make asphalt pavement more durable and provide guidelines for the proper utilization of this new technology.]]></description>
      <pubDate>Fri, 05 Apr 2024 12:15:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2363912</guid>
    </item>
    <item>
      <title>Incorporating Traffic Speed Deflection Devices Measurements into Pavement Management and Design</title>
      <link>https://rip.trb.org/View/2335042</link>
      <description><![CDATA[Traffic speed deflection devices (TSDDs) that measure surface deflection at traffic speeds are used by several highway agencies in the United States and other countries to provide data to help with management of the highway network. For example, these data can be used for assessment of pavement structural condition, selection of pavement treatments, and other purposes. In comparison with traditional pavement deflection measurement (e.g., falling weight deflectometers), TSDDs provide a means for acquiring extensive amounts of data in a short period of time that can be effectively used in pavement management and design.

Recognizing that no widely accepted practices for incorporating the measurements obtained by TSDDs into pavement management and design are currently available, research is needed to identify the deflection-based measurements that are required for pavement structural assessment and other applications and develop a guide that presents procedures for incorporating these measurements into pavement management and design practices.

The objective of this research is to develop a guide for incorporating TSDDs measurements into pavement management and design. The procedure contained in the guide shall be consistent with current practices for management and design of asphalt, concrete, and composite pavements.]]></description>
      <pubDate>Mon, 05 Feb 2024 16:20:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/2335042</guid>
    </item>
  </channel>
</rss>