Category: 2022

POSTER 22-19: REMOTE BRIDGE HEALTH MONITORING FOR SCOURING USING COST-EFFICIENT SENSING TECHNOLOGY

REMOTE BRIDGE HEALTH MONITORING FOR SCOURING USING COST-EFFICIENT SENSING TECHNOLOGY

PI: Tien Yee

Co-PI(s): Jidong Yang, Metin Oguzmert, and Mahyar Amirgholy

Institution(s): Kennesaw State University & University of Georgia

Abstract

Scouring is a major concern for highway bridges and is known to be a common cause of road bridge failures in the United States. Bridges are often inspected for scouring periodically and after large storm events to determine the health and safe operation of bridges. The general practice of manual measurements is employed by GDOT personnel after the storm events to determine the extent of scouring on bridge piers. While manual measurements are good for assessment after storm events, however, there are two disadvantages to this practice. Firstly, manual measurements require that the GDOT inspection crew be on standby for deployment immediately after a storm event and depending on the number of personnel that is available, may not be able to quickly perform the inspection on the majority of the bridges. Secondly, without prior knowledge of the extent of scour depths during floods, the post-flood inspection may be a safety concern for GDOT engineers and inspection crews. Commercial instrumentations are often expensive and may not be easily customizable to fit the needs of GDOT. There is a need for a less expensive and safe alternative near real-time bridge health assessment due to scouring. The goal of this project is to firstly produce a cost-efficient system for remote bridge health monitoring using existing technology and secondly make use of the data collected from the system to optimize operations within GDOT bridge monitoring units. Currently, the research has produced a lab-tested system shown in the poster. This system is poised to be deployed in the field for data collection.

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POSTER 22-28: 5.9GHZ INTERFERENCE RESILIENCY FOR CONNECTED VEHICLE INFRASTRUCTURE

5.9GHZ INTERFERENCE RESILIENCY FOR CONNECTED VEHICLE INFRASTRUCTURE

PI: Billy Kihei

Co-PI(s): 

Institution(s): Kennesaw State University

Abstract

Currently, there are not enough Wi-Fi devices operating around U-NII-4 Channels 180 to 184 to understand the impact to Connected Vehicle (CV) applications. Therefore, further research is needed to deploy a density of real-world devices in the field to understand the impact of: Co-channel interference (within the 5.9GHz Safety Band), Adjacent channel interference (above and below the 5.9GHz Safety Band). Studies to date do not consider a saturation of real-world interference devices in the unlicensed Wi-Fi bands below and above the 5.9GHz Intelligent Transportation Systems (ITS) safety band. This is due to an unavailability of consumer Wi-Fi devices in the lower 40MHz of the previous 5.9GHz Dedicated Short Range Communications (DSRC) spectrum, and a low penetration of consumer Wi-Fi devices in the new Wi-Fi 6E spectrum. The objective of this project is to assess the resiliency of CV applications to interference by reporting real-world CV performance and develop methods for detecting and mitigating interference with GDOT deployed CV devices.

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POSTER 22-01: UAS-ASSISTED INSPECTION OF BRIDGES FOR CORROSION EFFECTS

UAS-ASSISTED INSPECTION OF BRIDGES FOR CORROSION EFFECTS

PI: Iris Tien

Co-PI(s): 

Institution(s): Georgia Institute of Technology

Abstract

New technologies, such as UAVs and machine learning, have been used to conduct imagery-based bridge inspections and efficiently evaluate damage on the bridge. However, corrosion detection is still an open problem, and corrosion detection algorithms have only proven adequate in certain environments and conditions. The main goal of this project is to explore the use of UAVs as a proof-of-concept to detect and characterize corrosion on bridges in Georgia. The first objective of this research is to investigate the use of UAVs for bridge inspections. The second objective of this research is to develop and evaluate automatic corrosion detection and evaluation algorithms. As part of this project, imagery data from two bridges, selected in collaboration with GDOT personnel, was collected using the Skydio 2+ drone. After the images were cleaned and labeled, they were used in varying computer vision and machine learning algorithms for corrosion detection. First, texture thresholding and color thresholding methods were implemented. Then, K-Means was investigated as an unsupervised machine learning algorithm using texture and color features. Finally, deep learning methods were investigated with automated featured extraction. It was found that the Skydio 2+ drone can be used to reach places that are hard for inspectors to reach, but the trees in Georgia limit where the drone can fly and how much of the bridge can be assessed. Therefore, pre-flight planning is recommended. Additionally, it was found that no corrosion segmentation technique as of yet works perfectly. K-Means segmentation, coupled with background removal, has the highest recall, but the mIoU is low. Texture thresholding performed with the second highest recall and an mIoU close to 90%. The deep learning techniques, SpotRust and FCN, have the lowest performance. This research shows that these methods must be developed further to be useful in supporting bridge inspections in Georgia.

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POSTER 22-02: FIELD EVALUATION OF WIRELESS ULTRASONIC THICKNESS MEASUREMENT WITH STEEL BRIDGE MEMBERS

FIELD EVALUATION OF WIRELESS ULTRASONIC THICKNESS MEASUREMENT WITH STEEL BRIDGE MEMBERS

PI: Yang Wang

Co-PI(s): 

Institution(s): Georgia Institute of Technology

Abstract

The objective of this project is to develop and implement a long-term ultrasonic thickness measurement system on steel members of in-service bridges using the Martlet wireless ultrasonic devices. Each Martlet wireless ultrasonic sensing device consists of an ultrasonic transducer, a Martlet motherboard with wireless communication, a pulser daughterboard for pulse excitation generation, and an ultrasonic daughterboard for signal filtering and amplification. The developed system is composed of the Martlet wireless sensing devices and a gateway server connecting to a 4G LTE network. It has the ability to collect ultrasonic thickness measurement data at predefined intervals and automatically upload the data into the cloud. The system has been validated at two bridges in Georgia.

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POSTER 22-17: NONDESTRUCTIVE/NONCONTACT INSPECTION PROTOCOLS AND TECHNOLOGIES FOR AGING MECHANICALLY STABILIZED EARTH AND MODULAR BLOCK RETAINING WALLS

NONDESTRUCTIVE/NONCONTACT INSPECTION PROTOCOLS AND TECHNOLOGIES FOR AGING MECHANICALLY STABILIZED EARTH AND MODULAR BLOCK RETAINING WALLS

PI: Marcel Maghiar

Co-PI(s): Gustavo Maldonado, and Soonkie Nam

Institution(s): Georgia Southern University

Abstract

The MSE walls have been built for several decades in the U.S. and became one of the most common types of retaining structures. As the MSE walls are aging, proper inspections and monitoring are necessary to prevent critical failures and to determine appropriate maintenance schedule and priority. Also, non-destructive/non-contact methods are getting more attention, especially in structure inspections, due to their convenience and improved accessibility of the technology. However, there are currently no established inspection guidelines which have been approved by either the FHWA or GDOT. This project provides GDOT with a better decision-making benefit as methods to be developed through this endeavor will offer a more thorough and systematic inspection leading to appropriate actions, and the redeployment of digital data collected in-situ can support other investigations for connected projects. As existing MSEWs and MBWs age, a trackable history of the condition and stability of each individual retaining wall will be an asset for those making decisions on preventive maintenance and emergency care of these critical structures. The team?s results of the proposed research study and the new technologies/applications developed will be readily applicable to other types of retaining walls and ancillary structures.

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POSTER 22-18: STRUCTURAL MONITORING OF STEEL-MEMBER BRIDGES WITH FATIGUE LIFE PROGNOSIS DUE TO DYNAMIC VEHICULAR LOADS

STRUCTURAL MONITORING OF STEEL-MEMBER BRIDGES WITH FATIGUE LIFE PROGNOSIS DUE TO DYNAMIC VEHICULAR LOADS

PI: Yang Wang

Co-PI(s): Ryan Sherman

Institution(s): Georgia Institute of Technology

Abstract

Standard procedures exist to calculate the remaining fatigue life of steel bridges. However, such procedures rely on conservative estimates of the live load stress range that do not account for system-level behavior. Data acquisition (DAQ) systems exist that are capable of measuring the true structural response of in-service bridge systems. Leveraging such systems with fatigue analysis procedures, allows the remaining fatigue life to be more accurately estimated, thereby often extending the service life of critical bridge systems. The outcome of this project is to provide a long-lasting impact on the GDOT bridge asset management program by aiding in decisions regarding the repair, retrofit, and replacement of fatigue-sensitive bridges. A structural monitoring system will be developed to collect live data. The data will be used to create a finite element model for dynamic behavior and an algorithm to estimate the remaining fatigue life.

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POSTER 22-20: QUALITY MANUAL FOR STEEL BRIDGE FABRICATION

QUALITY MANUAL FOR STEEL BRIDGE FABRICATION

PI: Ryan J. Sherman

Co-PI(s): Lauren Stewart

Institution(s): Georgia Institute of Technology

Abstract

In any fabrication process, an undesired and often unavoidable obstacle that fabricators and owners deal with is the detection and correction of nonconformances, which is defined as an alteration in the fabrication process that results in the materials or fabricated component not meeting the requirements agreed upon in the project specifications. The objective of this research project is to investigate academic literature, unpublished research, industry knowledge, and the results from proposed experimental investigations to determine the appropriate methods to systematically detect and correct nonconformances encountered during steel bridge fabrication. To accomplish this objective, extensive literature reviews of existing data and research will be conducted, and both small- and large-scale experimental testing will be conducted. The small-scale testing will focus primarily on material testing, and the large-scale testing will focus primarily on fatigue testing. This research will result in the first draft of a standardized GDOT Steel Fabrication Quality Manual (SFQM) and new experimental data that will benefit both GDOT and the structural steel industry.

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POSTER 22-21: PHASE III – INVESTIGATION AND GUIDELINES FOR BEST PRACTICES OF MASS CONCRETE CONSTRUCTION MANAGEMENT

PHASE III – INVESTIGATION AND GUIDELINES FOR BEST PRACTICES OF MASS CONCRETE CONSTRUCTION MANAGEMENT

PI: Yong K. Cho

Co-PI(s): Kimberly Kurtis, and Russell Gentry

Institution(s): Georgia Institute of Technology

Abstract

The Georgia Department of Transportation (GDOT) defines mass concrete as “any large volume of cast-in-place concrete with dimensions large enough to require that measures be taken to cope with the generation of heat and attendant volume change to minimize cracking?. If mass concrete overheats due to the exotherm, the concrete may self-destruct due to delayed ettringite formation (DEF) in the worst case or may experience early-age cracking due to thermal differentials, which is not a fatal problem, but such cracking could lead to long-term durability problems. Thus, a false choice of temperature reduction methods utilized by contractors would decrease the quality of the concrete or structure, which could be costly for GDOT to maintain the possibly resulting defects. This research aims to expand the applicability of decision-making tools to various concrete mixes, including accommodating temperature differential and cost implications while exploring emerging cement and SCM combinations. The research team will also identify a time-cost tradeoff among different thermal control methods to increase the net benefit of a mass concrete construction project. The specific scope of the work to be completed within this research project includes, 1) investigation of emerging cement and SCM combinations through simulation and lab tests, 2) validation, extension, and refinement of the nomograms developed from Phase II, 3) identification of time-cost tradeoff among thermal control methods, and 4) investigation of� alternative methods to avoid active cooling.

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POSTER 22-04: WHAT IS THE NEW NORMAL? AN ANALYSIS OF POST-COVID-19 COMMUTE AND WORK PATTERNS

WHAT IS THE NEW NORMAL? AN ANALYSIS OF POST-COVID-19 COMMUTE AND WORK PATTERNS

PI: Patricia Mokhtarian

Co-PI(s): Giovanni Circella

Institution(s): Georgia Institute of Technology

Abstract

This study aims to understand the post-COVID work and commute patterns of Georgia (adult) workers and investigates how the patterns are related to the workers’ characteristics relevant to travel behavior and demand. The research team designed an online survey to gather information on attitudes on various topics, job characteristics, work and commute patterns, vehicle ownership status, residential location, and sociodemographic traits. The survey was distributed to (1) an online opinion panel (OP) managed by Qualtrics and (2) the Georgia respondents who consented to be contacted again for a future survey when they participated in the 2017 National Household Travel Survey (NHTS) and/or the survey administered for GDOT Research Project (RP) 16-31. (Trimmed) sample weights were developed and applied to the working data (N = 1931) to make the sample as representative of Georgia workers as feasible with respect to key sociodemographic traits, employment status, working-from-home engagement, and residential location region. Key findings were obtained from the trimmed-weighted sample: (1) detailed work and commute patterns of Georgia workers and (2) comparisons among region and worker types with respect to many variables collected (e.g., attitudes, sociodemographic traits, commute distance/mode, vehicle ownership, residential location). This study concludes with potential uses of the collected data and policy implications.

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