University(ies):
Georgia Institute of Technology
Project Description:
The objective is to assist Georgia Department of Transportation (GDOT) in developing the most effective policies and strategies for implementing a set-aside program and to assist GDOT in implementing the most appropriate policies and strategies for reducing the burden of overconcentration on non-DBEs.
Posters:
Web Links:
Project Details:
PI:
Thomas Boston, Catherine Ross, Sarah Smith, Jon Schmid
Participating University:
Georgia Institute of Technology
Type:
Policy/Workforce
Project Description:
The objective of this project is to provide the Georgia Department of Transportation (GDOT) planners and local stakeholders a framework for determining how traffic impact analysis (TIA) project expenditures in River Valley, Heart of Georgia Altamaha, and Central Savannah River Valley are expected to impact the economic, environment and quality of life in the areas.
Posters:
Web Links:
Project Details:
Field Validation of a Drive-By Bridge Inspection System with Wireless BWIM + NDE Devices
PI:
Xi Liu, Xinjun Dong, Yang Wang, Nasim Uddin, Laurence J. Jacobs, Jin-Yeon Kim
Participating University:
Georgia Institute of Technology, University of Alabama Birmingham
Type:
Asset Management
University(ies):
Georgia Institute of Technology
Project Description:
In this project, a wireless sensor network will be investigated for installation on a heavy truck to record the dynamic response of the truck as it crosses a bridge mounted with BWIM+NDE devices. The sensors installed in the vehicle include accelerometers to measure vibration and gyroscopes to capture vehicle pitching motion. As the instrumented vehicle approaches the bridge, BWIM+NDE system wirelessly establishes communication with wireless sensors on the vehicle to synchronize time and initiate data collection. As the truck crosses the bridge, the wireless sensors on the truck transmit vibration and pitching data to the wireless BWIM+NDE server for automatic integration with bridge response data. Experimental validation of the proposed wireless system will be performed both in the lab and in the field.
Presentation:
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Publications:
Web Links:
Project Information Forms:
Zhu, D., Dong, X. and Wang, Y. “Substructure model updating through iterative minimization of modal dynamic residual,” Proceedings of SPIE, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security, San Diego, California, USA, March 10-13, 2014.
Kane, M., Zhu, D., Hirose, M., Dong, X., Winter, B., Häckell, M., Lynch, J.P., Wang, Y. and Swartz, A. “Development of an extensible dual-core wireless sensing node for cyber-physical systems,” Proceedings of SPIE, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security , San Diego, California, USA, March 10-13, 2014.
Dong, X., Chen, S., Zhu, D., Kane, M., Wang, Y. and Lynch, J.P. “High-speed heterogeneous data acquisition using Martlet – a next-generation wireless sensing device,” Proceedings of the Sixth World Conference on Structural Control and Monitoring (6WCSCM), Barcelona, Spain, July 15-17, 2014.
Zhu, D., Dong, X. and Wang, Y. “Substructure finite element model updating of a space frame structure by minimization of modal dynamic residual,” Proceedings of the Sixth World Conference on Structural Control and Monitoring (6WCSCM), Barcelona, Spain, July 15-17, 2014.
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University(ies):
Georgia Institute of Technology
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PI: Baabak Ashuri
Co-PI(s):
Institution(s): Georgia Institute of Technology
Abstract
One of the main challenges that state departments of transportations (state DOTs) face in their design-build (DB) projects is to ensure that the design-build team upholds the highest standard of care in making complex engineering decisions involving multidisciplinary works. It is crucial to understand the underpinnings of engineering-related problems during both the design and construction phases and identify an effective approach to address these issues in the alternative delivery environment. This research aims to help the Georgia DOT (GDOT) Office of Innovative Delivery clearly define its expectations for the new position of project chief engineer (PCE). The overarching goal of this research project is to identify best practice guidance for defining GDOT?s expectations from the design-build team in proactive management of design-related issues. This study identifies gaps between GDOT?s expectations and the industry understanding of the PCE’s roles and responsibilities. Several emerging challenges related to the successful implementation of the new PCE position are discussed in the context of the dynamic design-build transportation market. The research team conducted content analysis and interviewed various professional groups, including state DOT officers, highway contractors, design consultants, owner’s representatives, legal experts, and insurance experts. To further discuss any issues related to insurability, the research team conducted a separate set of interviews with the insurance experts. The results show that, overall, interviewees agree that the PCE will add value for large and complex projects requiring multidisciplinary parties. The PCE requires a unique set of skills both in design and construction, and, therefore, finding an appropriate pool of candidates for the PCE position may be challenging for design-build teams. Several recommendations are made to enhance the description of the PCE role and responsibilities, in order to minimize any gaps in the understanding of the design-build industry professionals to fulfill this position. Not limited to the PCE position introduced by GDOT, the findings contribute to the DB and public-private partnership (P3) market to better understand the engineering decision-making process for the large and complex DB and P3 projects.
Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.
PI: Seth Wenger
Co-PI(s):
Institution(s): Georgia Southern University
Abstract
Georgia Department of Transportation (GDOT) must frequently consult with federal and state agencies to identify measures to avoid, minimize and mitigate impacts to imperiled aquatic organisms. Some of these measures, such as restrictions on in-water work during the reproductive season, impose substantial costs on GDOT projects. We developed an assessment of the sensitivities of the various imperiled taxa, and developed a system to provide flexibility for GDOT to employ the most effective measures for a given project, location and species. We also developed a template for a programmatic agreement that streamlined a system for evaluating GDOT projects and believe it will provide substantial cost savings for GDOT while improving outcomes for federally and state protected freshwater species.
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PI: Susan Burns
Co-PI(s): Dr. Susan Burns
Institution(s): Georgia Institute of Technology
Abstract
The objectives of this study were to evaluate the performance of stormwater best management practices (BMPs) used for stormwater quantity and quality control. Three field sites were tested to quantify hydraulic conductivity, infiltration, and solids removal efficiency. Removal efficiencies ranged from 12% to 35% of infiltrated runoff for VFS ranging from 15 ft. to 75 ft. long with slopes varying from 2% to 6%. For suspended solids removal, the VFS has the potential to remove between 21% and 43% when their design lengths range from 15 ft. to 75 ft long with slopes varying from 2% to 6%. It is recommended that partial credit be given for solids removal in filter strips that are shorter than the required 15 feet, and that filter strip designs incorporate the shallow grassed highway shoulder.
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PI: Rami J. Haddad
Co-PI(s):
Institution(s): Georgia Southern University
Abstract
Natural disasters cause devastating effects on transportation networks by causing significant damage and obstruction on frequently traveled roads. This report describes the design and implementation of an automated Unmanned Aerial Vehicle (UAV) based damage management using convolutional neural networks (CNNs). This system utilizes image processing and deep learning techniques to assess damages to the state’s transportation system. The assessed damages are automatically geo-tagged to an ArcGIS map compatible with the Georgia Department of Transportation (GDOT) GIS standards. This UAV-based intelligent disaster management system enables the GDOT to optimize its disaster management and recovery efforts. Additionally, this system provided live streaming of the UAV’s video feed to an RTMP server, enabling the first responders to assess damages. The system is composed of hardware and software components. In addition to the UAV platform, a customized application was developed using Python and MATLAB software to automate and centralize the operation of this system. The application included managing, sampling, classifying, and ArcGIS map tagging of the UAV-generated video streams. The simulation results of this system, using a library of images, have shown that the system could classify clear vs. damaged roads with an accuracy of over 99%. However, when the classification categories increased to six, damaged roads, clear roads, blocked roads, boat in roads, fallen power lines, and flooded roads, the average classification accuracy dropped to 74.1%. This was mainly due to the relatively small size of the library of disaster-related images.
Please comment below with any statements or questions you may have. Also let GTI if you would be interested webinars or presentations on similar topics.
