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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Mississippi Summer Transportation Institute- 2027</title>
      <link>https://trid.trb.org/View/2732467</link>
      <description><![CDATA[The Mississippi Summer Transportation Institute (MSTI) Program aims at introducing a group of motivated pre-college students (9th to 12th grade) to the transportation industry. During the two-week program, students will participate in academic and enhancement activities designed to improve their skills in Science, Technology, Engineering, and Mathematics (STEM) and leadership.]]></description>
      <pubDate>Tue, 21 Jul 2026 16:46:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732467</guid>
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    <item>
      <title>Physics Informed Neural Network (PINN) enabled Predictive Resilience Framework for Maritime and Multimodal Levee Infrastructure</title>
      <link>https://trid.trb.org/View/2732360</link>
      <description><![CDATA[The performance and resilience of levee systems are governed by complex
hydro-mechanical interactions influenced by transient seepage, soil stratification, and environmental loading.
Conventional monitoring approaches, while effective in capturing field conditions, lack predictive capability and
often fail to integrate subsurface characterization with real-time system response. This study proposes a Physics-Informed Neural Network (PINN) enabled predictive resilience framework for maritime and multimodal levee
infrastructure, integrating multi-source sensing, geophysical imaging, and physics-based modeling. The
framework leverages Internet of Things (IoT) based sensor networks, including IMU derived tilt and displacement measurements, and
environmental variables such as rainfall, temperature, and soil moisture. To enhance subsurface characterization,
Electrical Resistivity Imaging (ERI) and Multichannel Analysis of Surface Waves (MASW) are incorporated to
capture spatial variability in moisture distribution, stiffness profiles, and potential seepage zones. These datasets
are fused with UAV based LiDAR point cloud models to develop high-resolution, temporal geospatial conditional
representations of levee geometry and deformation. The integrated dataset is utilized to calibrate finite element
method (FEM) based seepage and stability models, enabling accurate representation of coupled hydromechanical
behavior. The PINN architecture embeds governing equations of transient flow and unsaturated soil
mechanics into the learning process, allowing physically consistent prediction of pore pressure, volumetric
moisture content, and deformation fields. A hybrid physics-guided, data-driven digital twin will be developed to
continuously assimilate field and geophysical data, providing real-time predictions and identifying anomaly
thresholds indicative of instability. The proposed framework advances geotechnical asset management by
enabling predictive failure assessment, risk-informed decision-making, and proactive maintenance strategies,
thereby enhancing the resilience of critical maritime and multimodal infrastructure systems under extreme
environmental conditions.]]></description>
      <pubDate>Tue, 21 Jul 2026 16:41:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732360</guid>
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      <title>Flood-resilient Transport System Through Integrated Modeling, ML &amp; Immersive AR/VR </title>
      <link>https://trid.trb.org/View/2732359</link>
      <description><![CDATA[Extreme rainfall events increasingly disrupt urban transportation systems by overwhelming drainage infrastructure and causing localized road flooding that impedes last-mile freight delivery, delays emergency response, and disrupts the broader multimodal supply chain. These disruptions limit access to essential services, delay emergency response, and threaten public safety. Building on the research team's previously developed framework (F25-26), this project advances a data-driven approach for high-resolution prediction of urban road flooding in Jackson, Mississippi, integrating geospatial databases, process-based H-H modeling (aligning with rigorous U.S. Army ERDC methodologies), and machine learning (ML) and artificial intelligence (AI) techniques to identify flood-prone road and railway segments. The ML-based surrogate models will maintain computational efficiency, enable timely identification of vulnerable transportation networks, and support emergency response by feeding into JSU Water Lab’s broader web-based-visualization interfaces. This project introduces an interactive K–12 STEM module, age-appropriate hands-on activities along with STEM curriculum module designed for upper-level Civil Engineering undergraduate and graduate students at JSU. This initiative transforms research outcomes into the classroom to modernize workforce training using integrated Augmented Reality (AR) and Virtual Reality (VR) and will be tested with summer student exchange programs. Students can explore and 3D print several transportation infrastructure components, such as culverts, bridges, and urban drainage systems, and evaluate their performance under simulated flood conditions, and experience AR/VR based immersive simulators. Using AR/VR tools, including the Meta Quest platform, available in the PI lab, future transportation engineers will visualize flood scenarios in immersive 3D environments built from existing topographical assets in Unity or Unreal Engine. By combining advanced predictive modeling with experiential learning, the project promotes advanced STEM engagement, and high-tech workforce development, aligning with broader goals of improving multimodal transportation system resilience. While the primary focus is on urban road and rail flooding, these transportation corridors serve as critical connectors to Mississippi's inland waterway freight network, including facilities linked to the Pearl River system and regional multimodal freight movements. Roadway disruptions during extreme rainfall events can delay freight access to ports, intermodal terminals, water-dependent industrial facilities, and affect supply-chain resilience. By identifying flood-vulnerable roadway and railway segments, the proposed framework will support more reliable connectivity between surface transportation infrastructure and maritime freight operations]]></description>
      <pubDate>Tue, 21 Jul 2026 16:34:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732359</guid>
    </item>
    <item>
      <title>Monitoring Soil Resistivity in Highway Slopes Stabilized with Vetiver Grass</title>
      <link>https://trid.trb.org/View/2678201</link>
      <description><![CDATA[The intensity of the heaviest downpours has risen by roughly 20% over the past century, and this trend is expected to persist. Fluctuations in temperature, precipitation, sea levels, and coastal storms caused by climate change will increase the vulnerability of infrastructure across the United States. Southern states like Mississippi, Alabama, Texas, and Louisiana face greater challenges due to the abundance of expansive clay soil. During the wet season, the rainwater infiltrates into the soil and triggers the volume expansion. In drying periods, the soil shrinks significantly, and desiccation cracks are formed within the soil. Highway slopes built on expansive soil are, therefore, prone to rainfall-induced failure. The current study investigates the role of Vetiver grass, a nature-based solution, in improving the soil moisture condition of highway slopes. Vetiver is a deep-rooted long grass system that can draw out a lot of moisture when planted in the soil. It improves the soil moisture condition and adds additional shear strength to the soil. The study selected a highway slope near Jackson, Mississippi, where a section was stabilized with Vetiver grass. Another section was considered as a control section where no Vetiver was planted. Electrical resistivity imaging (ERI) tests were done seasonally to monitor the soil moisture profile along the slope depth. Resistivity values along the depth for both the planted and control sections were compared to evaluate the performance of Vetiver grass. It was observed that the planted section has higher resistivity to a certain depth, denoting lower moisture content and reduced perched zone, compared to the control section. The study highlights Vetiver grass as a climate-resilient and proactive solution for slope stabilization, which can be a game changer in addressing the challenges posed by climate change.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:49:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2678201</guid>
    </item>
    <item>
      <title>Improvement of Mechanical Properties and Erosion Resistance in Soils Using Biopolymers for Sustainable Geotechnical Applications</title>
      <link>https://trid.trb.org/View/2678404</link>
      <description><![CDATA[The application of biopolymers in geotechnical engineering presents a promising approach for enhancing soil stability and erosion resistance while promoting sustainable construction practices. This study investigates the effects of biopolymer treatment on the mechanical properties and bridge scour of Creek and Third Spot soils collected from a bridge site in Jackson, Mississippi. Xanthan gum and guar gum were selected as stabilizing agents, with their optimal concentrations and moisture content evaluated for soil treatment. Mechanical performance and erosion resistance were assessed through unconfined compressive strength (UCS) tests, triaxial tests, and pocket erodometer tests. The results demonstrated that biopolymer treatment significantly improved soil strength, with guar gum exhibiting superior performance in UCS enhancement. The addition of 1% guar gum increased the UCS of Creek and Third Spot soils to approximately 3,500 kPa and 5,100 kPa, respectively. Additionally, biopolymer-treated soils exhibited increased cohesion, with Third Spot soil treated with 1% xanthan gum achieving a cohesion value of 78.5 kPa, compared to untreated soil with zero cohesion. Furthermore, erosion resistance was enhanced, as biopolymer-treated soils exhibited a reduction in erodibility classification from Very High Erodibility to High or Medium Erodibility. These findings underscore the potential of biopolymer-based soil treatment as an effective and sustainable solution for improving erosion resistance in bridge foundation soils.]]></description>
      <pubDate>Fri, 12 Jun 2026 15:59:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2678404</guid>
    </item>
    <item>
      <title>Pipeline Investigation Report: Atmos Energy Corporation Natural Gas-Fueled Home Explosions and Fires, Jackson, Mississippi, January 24, 2024, and January 27, 2024</title>
      <link>https://trid.trb.org/View/2686632</link>
      <description><![CDATA[​This report discusses the January 2024 natural gas-fueled explosions and fires at two separate homes in Jackson, Mississippi, which occurred 3 days apart, collectively resulting in one injury, one fatality, and three destroyed homes. Safety issues identified in this report include compression coupling leaks, insufficient leak management program, inadequate distribution integrity management program, ineffective public awareness program, and absence of natural gas detection alarms in buildings. As part of this investigation, the National Transportation Safety Board issued safety recommendations to the Department of Transportation Office of Inspector General, the Pipeline and Hazardous Materials Safety Administration, and Atmos Energy Corporation and reiterated recommendations to the Pipeline and Hazardous Materials Safety Administration and to 50 states, the Commonwealth of Puerto Rico, and the District of Columbia.]]></description>
      <pubDate>Fri, 10 Apr 2026 10:52:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686632</guid>
    </item>
    <item>
      <title>Demonstration of Buckle Up Phone Down in Jackson, Mississippi, and Sioux Falls, South Dakota</title>
      <link>https://trid.trb.org/View/2685590</link>
      <description><![CDATA[The Buckle Up Phone Down (BUPD) program was created in 2017 by the Missouri Department of Transportation (MoDOT) in response to an increase in crash fatalities. MoDOT recognized that unrestrained motorists and cell phone use while driving were contributing to the problem, and existing seat belt and distracted driving laws in the State provided little support for enforcement-centered countermeasures. These factors influenced BUPD’s design which features grassroots efforts to spread the program and messaging focused on personal responsibility. The statewide program has garnered much support from public and private sectors since its inception. Due to the growing interest in the program and lack of a formal evaluation, the National Highway Traffic Safety Administration (NHTSA) requested to learn more about the program, its essential elements, and the feasibility of implementing the program. The Missouri BUPD program was studied to assist with the demonstration of similar programs in two locations (Jackson, Mississippi, and Sioux Falls, South Dakota). It is important to note that this was not a replication of Missouri's Buckle Up Phone Down program. Instead, demonstration programs integrated key elements of the Missouri model program to design the leadership structure, program material, and publicity and outreach efforts. Implementation Teams designed BUPD programs within 3 months and implemented programs over 6 months (October 2022 – March 2023). Descriptions of both demonstration programs along with qualitative insights, lessons learned, and suggested steps to implement a BUPD program are provided in this report. A separate evaluator conducted a formal evaluation of this demonstration program.]]></description>
      <pubDate>Mon, 30 Mar 2026 10:00:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685590</guid>
    </item>
    <item>
      <title>Evaluation of Buckle Up Phone Down in Jackson, Mississippi, and Sioux Falls, South Dakota</title>
      <link>https://trid.trb.org/View/2685591</link>
      <description><![CDATA[The Buckle Up Phone Down (BUPD) program offers a potential non-enforcement approach to changing driver seat belt and cellphone use behavior. This report presents the results from process and outcome evaluations examining the implementation and effectiveness of an adaption of BUPD in two demonstration cities, Sioux Falls, South Dakota, and Jackson, Mississippi, where it was carried out with support from a separate demonstration contractor. The Process Evaluation outlines how implementation teams executed BUPD in each demonstration city and includes lessons learned through its implementation. The Outcome Evaluation observed real-world seat belt and cellphone use behaviors of drivers in the two demonstration cities and two matched control cities to assess the overall effectiveness of these adaptations of the BUPD initiative as implemented in Jackson and Sioux Falls. BUPD was implemented in the demonstration cities with as much fidelity as possible given resource and time constraints. However, no significant increase in seat belt use or decrease in cellphone use was found. It remains possible that other BUPD implementations could successfully influence driver behavior.]]></description>
      <pubDate>Mon, 30 Mar 2026 09:47:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685591</guid>
    </item>
    <item>
      <title>Fragility Curves for Highway Embankment Slope Stability under Extreme Rainfall</title>
      <link>https://trid.trb.org/View/2592033</link>
      <description><![CDATA[Highway embankment slopes are subject to potential failure due to extreme rainfall patterns. This study uses a fragility framework to examine the failure probability of a highway slope consisting of Yazoo clay in the northern part of Jackson, Mississippi, USA. A finite-element model of the slope is calibrated with available site data. Total rainfall depths between 47 mm and 630 mm are considered in the application of the model under different high-to-low intensity and short-to-long duration categories for return periods up to 1,000 years. Uncertainties in the rainfall patterns are incorporated through Monte Carlo simulation. The effects of extreme rainfall are integrated by applying the intensity and frequency of rainfall events that are greater than those of typical design considerations. Fragility curves, the continuous failure probability functions corresponding to a wide range of rainfall depths, are constructed using simulation outputs for different limit states. Rainfall duration is identified as the key factor affecting the embankment’s fragility. Low-intensity and long-duration rainfalls are found to be more detrimental to the slope compared to high-intensity and short-duration rainfalls. This study revealed that the major limit state is only exceeded by post-200-mm rainfall depths, with an increasing exceedance likelihood at greater rainfall depths. Limit states showed higher exceedance probability from higher frequency rainfalls due to the long rebound period of Yazoo clay. The findings from this study may be utilized in the design of new embankments within the same region and in safety assessments of existing embankment slopes under a range of rainfall conditions.]]></description>
      <pubDate>Tue, 30 Sep 2025 08:34:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2592033</guid>
    </item>
    <item>
      <title>Improved Road Flood Predictability and Disruption Response Through the Synergistic Integration of Geospatial Databases, Process-Based Modeling, and Machine Learning</title>
      <link>https://trid.trb.org/View/2536176</link>
      <description><![CDATA[Major flood events can have devastating impacts on communities, ecosystems, and infrastructure. Heavy rainfall in urban areas often overwhelms existing infrastructure, resulting in localized street or section flooding. Flooded roads hinder access to essential services and pose significant challenges for emergency management. Predicting these floods in near-real-time and with high resolution is difficult due to limited data and the computational cost of detailed models. The research team has already developed and tested a framework (Bhattarai et al., 2024). This project will test the modeling framework around the Jackson, Mississippi, downtown and surroundings. For instance, events like floodwater beneath the railroad bridge on Monument Street near Mill Street in Jackson (reported on Wednesday, January 24, 2024, and similar events). The project will compile information on flooded road and railway networks from local and regional news portals and X (formerly Twitter). Using location keywords (Jackson’, ’Jackson downtown’, ’Jackson MS’) and flood-related terms (’flood’, ’flooding’, ’road flood’, ’urban flood’, ’flash flood’, ’road closure’, ’rainfall’), the research team will identify flooding dates and affected road locations for the recent time and geolocate flooded locations using QGIS, that will serve as training-testing data for the machine learning model. Then the project will develop and test machine learning models (base learner models, such as random forest, support vector machines, and ensemble of these base learners). The research team will use datasets of covariates from other available hydrodynamic models, satellite rainfall estimates, traffic cameras (if available), flood-control infrastructure databases, and basin characteristics to predict flood inundation at street-level resolution. The research team believes these machine learning-based models offer significant improvements in computational efficiency while maintaining accuracy and consistency. In a nutshell, the research team will identify the most susceptible road and rail networks to critical urban facilities.]]></description>
      <pubDate>Thu, 10 Apr 2025 14:38:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2536176</guid>
    </item>
    <item>
      <title>IoT Sensor Fusion for Low-Cost Cloud Based Monitoring for Resilient Levees and Embankments</title>
      <link>https://trid.trb.org/View/2536170</link>
      <description><![CDATA[The performance and longevity of geo-infrastructure assets such as levees and highway embankments depend on geotechnical (embankment, foundations, slopes) components, both influenced by soil conditions, hydraulic loads, and disruptions due to weather. Continuous, data-driven monitoring is essential for reliable water resource management and disaster resilience. This research advances Geotechnical Asset Management (GAM) using advanced Internet of Things (IoT)-based inertial measurement unit (IMU) sensors installed onsite combined with periodic aerial LiDAR point-cloud data collection techniques. IoT-based IMU sensors will track multi-directional displacements, while accelerometers and vibration sensors will capture performance data under various conditions. An earth dam and highway embankment site in Jackson, Mississippi, and a Levee section owned by the United States Army Corps of Engineers (USACE) will serve as test locations. A 3D geospatial model combining drone-mounted LiDAR will track structural stability and environmental impacts. Periodic assessments will detect instability, settlement, and deformation, enabling proactive maintenance to prevent failures and minimize disruptions. Enhanced monitoring will ensure reliable, connected, and risk-mitigated infrastructure to support national economic competitiveness. Collected data will be transmitted to the Amazon Web Services (AWS) cloud for remote monitoring of the embankment, dam and levee system. In addition, the analytical tools in the cloud platform will be used to analyze the data and identify threshold points based on the performance criteria to create an early detection of failure under extreme conditions. This project will develop a data-driven, scalable solution to enhance safety, efficiency, and resilience in water management infrastructure while strengthening investments, thus enabling US economic strength and global competitiveness.]]></description>
      <pubDate>Wed, 09 Apr 2025 18:28:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2536170</guid>
    </item>
    <item>
      <title>Development of a Highway Slope Failure Warning System Using Field Instrumentation</title>
      <link>https://trid.trb.org/View/2344425</link>
      <description><![CDATA[Rainfall-induced slope failure is a major problem for highways made of highly plastic clay in the southern United States. Alternative wet-dry cycles and seasonal moisture variation lead to recurring shrink-swell of soil. In Mississippi, sustained perched water conditions within highway slopes due to increased rainfall have exacerbated this problem. Real-time monitoring of soil moisture content and matric suction can aid highway authorities in detecting overall structural health and early slope failure. This study aims to develop a protocol for an early warning system for highway slope failures made of highly plastic clay based on field instrumentation data. A slope in Jackson, Mississippi, was instrumented with moisture sensors, water potential probes, and rain gauges. The data obtained from field instrumentation, including moisture content, matric suction, and rainfall, were analyzed to develop an early detection protocol. The analysis conducted based on the field-instrumentation data revealed the presence of a perched water zone, and a trend of slope movement associated with it was predicted. This finding was verified by the profiles through electrical resistivity imaging, where the lower resistivity meaning the existence of water within the soil profile clearly indicated the presence of the perched water zone. A slope movement trend was observed from the inclinometer data. The comprehensive analysis of the instrumentation data led to the development of a protocol that can aid highway authorities in detecting slope failure at an early stage using field instrumentations.]]></description>
      <pubDate>Thu, 09 May 2024 09:24:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2344425</guid>
    </item>
    <item>
      <title>A Transformative Approach to Stabilize Highway Slope Using Vetiver Grass</title>
      <link>https://trid.trb.org/View/2291253</link>
      <description><![CDATA[The rainfall pattern in Mississippi has been affected by climate change, leading to increased precipitation that can cause the failure of highway slopes made of highly plastic clay soil. This soil is highly expansive and experiences repeated shrink-swell behavior, which softens the soil, reduces its shear strength, and makes it vulnerable to failure. To address this problem, vetiver grass was used as a nature-based solution to stabilize a highway slope along I-20 in Jackson, Mississippi. The grass’s deep and fibrous roots hold the soil in place, extract water, and thus act as a drainage medium. Monitoring equipment, such as rain gauges and moisture sensors, was installed to track rainfall, moisture content, and matric suction. The study showed that the vetiver grass reduced the perched water zone, reinforced the slope with increased suction, and prevented slope movement. This transformative and climate-resilient approach provides an effective solution for highway slope repair.]]></description>
      <pubDate>Thu, 21 Dec 2023 16:35:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2291253</guid>
    </item>
    <item>
      <title>Mapping of Slope Failures on Highway Embankments using Electrical Resistivity Imaging (ERI), Unmanned Aerial Vehicle (UAV), and Finite Element Method (FEM) Numerical Modeling for Forensic Analysis</title>
      <link>https://trid.trb.org/View/2111970</link>
      <description><![CDATA[Highway Embankment Fill Slope is one of the significant components of transportation geo-infrastructures assets. Embankmets failure is a common problem that occurs due to various geotechnical, climatological, and environmental contributing parameters. Major influential factors include high temperature, high rainfall volume, and type of soil or a combination of all the above. For instance, when a slope built on high swell-shrinkage clay soil fails abruptly, it is due to the weakened self-retaining ability of the soil due to excess pore water pressure from high rainfall events. In Mississippi, rainfall is very intense, and lately, it is often characterized by aggressive showers. This rainfall generates significant soil strength losses that can endanger the safety and durability of embankments. Most embankments in the Jackson metro areas are constructed using Yazoo clay which is a typical High Swell-Shrinkage Clay Soil. These embankments have been found to experience shallow to deep failures a few years after construction due to the shrink-swell cycles during seasonal variations. These frequent failures have caused a significant maintenance problem for the Mississippi Department of Transportation (MDOT). Therefore, methods and approaches to evaluate embankment failures have been subject to careful examination by the MDOT by employing multiple investigations means, including Non-Destructive Testing (NDT) methods. To this end, in this study, Unmanned Aerial Vehicle (UAV), Electrical Resistivity Imaging (ERI), and Finite Element Method (FEM) numerical modeling were used to analyze shallow failure mechanisms within slopes. Several failed slopes located in the Jackson metro area in Mississippi were considered as references. The objective of the current study is to highlight the differences between pre and post-monitoring, evaluative, and analytic actions regarding embankments experiencing failure. During this study, four failed embankments were investigated using ERI and UAV to identify and locate the failed geometry, including slip surfaces. To better understand the failure mechanism, the identified embankments failure slip surfaces were numerically modeled using the FEM software package Plaxis 2D. Soil-strength parameters at failure were extracted through back calculation, and failure/slip surface depth was numerically characterized. The finding of this study helps post-embankments failure forensic evaluations significantly in terms of understanding failure mechanisms, identifying contributing failure parameters, better managing the decision-making process, and selecting an optimized stabilization technique.]]></description>
      <pubDate>Tue, 28 Mar 2023 09:56:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2111970</guid>
    </item>
    <item>
      <title>Coupled Hydro-Mechanical Analysis of Highway Slope on Expansive Soil Subjected to Rainfall</title>
      <link>https://trid.trb.org/View/1890263</link>
      <description><![CDATA[Because of intensive precipitation and the presence of high-plastic Yazoo clay in central Jackson in Mississippi, shallow highway slope failures are a reoccurring phenomenon. Annually, the majority of highway slopes in central Mississippi experience shallow slope failures. The major objective of the current study is to evaluate the performance of two repaired highway slopes in the Jackson Metroplex neighborhood in Mississippi. The highway slope ratios are 3H:1V (Terry Road) and 6H:1V (McRaven Road). Soil boring and CPT testing were conducted as part of site investigations. Vertical slope inclinometers and precipitation gauge were also installed at the site slopes to record and detect displacement along the slope and real precipitation, respectively. One year after monitoring the slops, consecutive shallow slope movements were observed in late 2019. Based on the field monitoring results, the slopes became fully saturated. Impacting factors and potential failure conditions were verified with back analysis using the 3D Finite Element Method in the Plaxis. Based on the 3D coupled flow-deformation analysis results, the progressive precipitation infiltrated in the top soil which significantly impacted the reduction in soil matric suction and creates a perched water zone, which reduced the factor of safety closed to 1.0. Based on the field and numerical observations, the development of the perched water zone as a result of continuous precipitation led to slope surficial layer movements.]]></description>
      <pubDate>Thu, 18 Nov 2021 12:14:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/1890263</guid>
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