Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
1556 The University of Texas at Arlington (143444)
Principal Investigator: Seyed Mohsen Shahandashti,mohsen@uta.edu,(817) 272-0440
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 249,874
Exceeds $250,000 (Is it flagged?): No
Start and End Dates: 2/16/23 - 8/31/24
Restricted Research: YES
Academic Discipline: Department of Civil Engineering
Department, Center, School, or Institute: none
Title of Contract, Award, or Gift: Slope Repair and Maintenance Management Planning
Name of Granting or Contracting Agency/Entity:
Texas Department of Transportation (TxDOT)
Program Title: none
Note:
(SAM Category 1.1.1.) UTA will create a database compiling data (e.g., engineering soil characteristics, rainfall intensities, slope geometry, and slope repair history) that are required for assessing and predicting conditions of roadside slopes and ultimately recommending proper repair methods. We will collect data from a variety of data sources, including but not limited to past maintenance and construction project documents and site investigations (e.g., Soil test borings) and public data sources. We will create a process of geospatial data integration to create the geo-referenced database for assessing conditions of roadside slopes along highway corridors of the TxDOT Houston District. UTA will perform the slope failure susceptibility analysis using the data collected to identify and visualize critical slope segments that are susceptible to rainfall-induced failures. UTA will collect information on mechanically stabilized and vegetated slopes in the corridors to calibrate and update the locations of critical slope segments that are highly sensitive to rainfall. UTA will implement a decision support system to recommend rapid, resilient, and sustainable repair methods to prevent recurring failures. The recommendations will be based on the slope condition data, results of slope susceptibility analysis, and the extensive information collected by PI Shahandashti about the characteristics of slope repair methods through TxDOT RTI Research Projects 0-6957 and 5-6957. These projects received the 2019 AASHTO High-Value Research “Sweet Sixteen” Award. Figure 4 provides the list of repair methods investigated in TxDOT RTI Projects 0-6957 and 5-6957. The decision support system for recommending repair methods will also consider various criteria, such as repair cost, rapidity of repair, impact on traffic, and requirement of skilled labor.
Discussion: No discussion notes