Structural Engineering Commons^™

Performance And Economic Evaluation Of Asphalt-Based High Friction Surface Treatment (Hfst) Applications, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are recognized for enhancing friction between tires and road surfaces, with reduced road accidents being a key benefit. Epoxy-based HFSTs, though widely used, come with challenges like compatibility issues with existing pavements, higher installation and removal costs, and reduced durability tied to substrate quality. Recently, state agencies have increasingly focused on developing asphalt-based alternative binders for HFST applications as highlighted in the National Cooperative Highway Research Program (NCHRP) RFP #NCHRP 10-145. This study introduces asphalt-based HFSTs as an alternative to traditional epoxy-based treatments. Various aggregate types were examined for friction performance and the effect of …

Mitigating Frost Heave And Thaw Weakening In Roads Using Wicking Geotextile, Javad Galinmoghadam

Doctoral Dissertations

"Excess water is known to be the primary cause of soil and foundation problems. In cold regions, water-related problems are exacerbated by seasonal freezing and thawing cycles. Frost heave and thaw weakening is the leading cause of premature pavement failure and consume considerable budgets of the Department of Transportations in cold regions. The first step to designing mitigation measures is the ability to predict frost heave under different conditions. This study aims to introduce a new method for quantifying frost heave using a prediction model based on the state surface approach. This proposed model addressed many inconsistencies and limitations of …

Guest Editorial, Li Ai, Xiao Tan, Arslan Akbar, Guirong Yan

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Fitting Quality Of Nmr Relaxation Data To Differentiate Asphalt Binders, Rebecca M. Herndon, Kevin Lai, Magdy Abdelrahman, Klaus Woelk

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asphalt binder performance grades (PGs) are important metrics in designing pavements for effective transportation infrastructure. the PG system relies on the binder's stiffness and is determined through energy- and time-intensive physical testing. Physical properties, like stiffness, can also be determined by spin–lattice NMR relaxometry, a non-destructive chemical method. NMR relaxometry can quantify the molecular mobility of materials by determining relaxation times from exponential decays of excited nuclear magnetization. While relaxation times have been used to determine physical properties of materials, a quantitative relation to the PG grades of asphalt binder is yet to be established. in this study, T1 NMR …

Final Report - Qa/Qc Guidelines On Drone-Based Remote Sensing For Bridge Element Inspection, Genda Chen, Woubishet Z. Taffese, Ritesh Sharma, Zhenhua Shi

Project IM-4

Remote sensing of elevated infrastructure via robotic platforms has recently gained increasing interest in bridge inspection. Such automated bridge inspection can not only overcome accessibility and safety challenges but also improve objectivity and consistency of the measured data compared to current visual inspection practices. With the advent of advanced technologies, quality assurance (QA) and quality control (QC) for robot-based bridge inspection become imperative. This study aims (1) to understand actionable inspection activities and procedures in route planning, sensor preparation and measurement, ground truth selection, and statistical analysis; (2) to outline assessment matrices and best practices for drone-based images to achieve …

Enhancing Frp-Concrete Interface Bearing Capacity Prediction With Explainable Machine Learning: A Feature Engineering Approach And Shap Analysis, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study introduces a novel approach to predict the shear bearing capacity of FRP-concrete interfaces using explainable machine learning. Eight algorithms are employed: three standalone models (Artificial Neural Network, Support Vector Regression, and Decision Tree) and five ensemble learning models (Bagging, Random Forest, Adaptive Boosting, Gradient Boosting, and Extreme Gradient Boosting). Four scenarios with varying input features, including engineered features inspired by mechanics-based bearing capacity equations, are examined. Notably, the inclusion of engineered features such as the stiffness of the FRP strip (Kf) significantly enhanced prediction accuracy and efficiency, although the width correction coefficient (bf/bc) did not yield significant benefits, …

Anti-Corrosion Performance Of Magnesium Potassium Phosphate Cement Coating On Steel Reinforcement: The Effect Of Boric Acid, Fan Zhang, Jihui Qin, Kangyi Cai, John J. Myers, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

It has recently been found that magnesium potassium phosphate cement (MKPC) paste coating applied on the surface of steel reinforcement can effectively retard the onset of corrosion and suppress corrosion reactions. However, the fast-setting nature of MKPC—which is a merit in repair—can be problematic in a practical engineering process of coating the steel reinforcement with MKPC paste. To address this problem, boric acid (H₃BO₃) was added as a retarder in an MKPC formulation to prolong the setting time. This work investigated the impact of boric acid (at 5% by weight of MgO) on the anti-corrosion performance …

Semi-Annual Progress Report #15, Missouri University Of Science And Technology

Semi-Annual Progress Reports

No abstract provided.

2017-2024 Emerging Technologies And Milestone Achievements Toward Automated Bridge Inspection And Maintenance, Genda Chen

INSPIRE Archived Webinars

Main hardware and software systems developed in the INSPIRE University Transportation Center from 2017 to 2024 will be presented. Their characteristic parameters, operation procedures, performance metrics, advantages over the state of practice, and application limitations will be summarized. These systems include, but not limited to,

 Flying and climbing robots for high-quality data collection from remote sensing and nondestructive testing,

 Explainable artificial intelligence and machine learning for element segmentation and defect classification,

 3D reconstruction and digital twins for virtual inspection,

 Framework for the probability of detection for various defects and damage from in-situ sensors,

 Defect detection, …

Final Report - Mixed Reality For Beyond Visual Line-Of-Sight Bridge Inspection Using Robot-Assisted Nondestructive Evaluation, Genda Chen, Joel Runji

Project IM-5

To improve data consistency, work efficiency, inspector safety, and cost effectiveness during routine inspections, drones have been increasingly used in recent years to support imaging and scanning over the surface of various elements in a bridge for surface condition assessment. Most drones are operated manually within a visual line of sight and unable to inspect river-crossing bridges completely since not all elements can be viewed by a drone operator using a binocular. Even for autonomous drones with collision-avoidance features, physical interaction with a bridge for nondestructive evaluation (NDE) is currently impossible in practice. An alternative solution with robot-assisted remote nondestructive …

Final Report - Hyperspectral Imaging And Analysis For Steel Paint Condition Assessment, Hongyan Ma, Genda Chen, Pengfei Ma

Project SN-9

This project aimed to understand the durability of multiple coating settings that had been widely used in highway bridges. Coatings can prevent their substrate from being contacted by aggressive particles and thus corrosion to preserve structural components. However, the wide selection of coatings for steel girders or truss can greatly impact the serviceability of bridges. This project studied four types of top-coat materials (epoxy, Alkyd, acrylic, and polyurethane) and two types of under-coat materials (epoxy and acyclic). The coatings were configured as two-layer and three-layer systems to evaluate their difference in durability. The degradation process of the coatings was monitored …

Final Report - Probability Of Detection In Corrosion Monitoring With Fe-C Coated Lpfg Sensors, Genda Chen, Ying Zhou, Pengfei Ma

Project SN-8

This project aimed to develop and evaluate two statistical methods for determining the probability of detection (POD) in corrosion monitoring using Fe–C coated long-period fiber grating (LPFG) sensors. These methods, referred to as the Size-of-Damage-at-Detection (SODAD) method and the Random Parameter Model (RPM), addressed limitations in traditional POD models by considering the time dependency inherent in sensor data. The goal was to assess steel mass loss at 90% detection probability and establish the largest undetectable mass loss threshold at a 95% lower confidence bound. Both methods were assessed for computational efficiency, sensitivity to distribution assumptions, and robustness under varying model …

Final Report - An Interactive System For Training And Assisting Bridge Inspectors In Inspection Video Data Analytics, Genda Chen, Ruwen Qin, Mohammad Hossein Afsharmovahed, Kevin Lai, Ritesh Sharma

Project WD-4

This project aims to develop an interactive, web-based system to assist bridge inspectors in machine learning and video analytics for a rapid condition state assessment of bridge elements in accordance with the 2019 Manual for Bridge Element Inspection. Referred to BridgeNet, the system includes region-based convolutional neural network (RCNN) models for bridge element and defect segmentation and an inspection video analytic tool that is integrated into a unified graphical user interface (GUI). It provides users with an image-based testbed of modulated RCNN models. The BridgeNet has evolved in four phases: (1) backend and frontend framework setups, (2) Mask-RCNN-based bridge segmentation, …

Final Report - Bridge Inspection Robot Deployment Systems (Birds), Genda Chen, Son Nguyen, Alec Reven, Bo Shang

Project AS-4

This study aims to develop and evaluate Bridge Inspection Robot Deployment Systems (BIRDS) that support automated bridge inspection. BIRDS include uncrewed aerial vehicles (UAVs), structural crawlers, and/or their combination. A particular type of the BIRDS, which is a hybrid flying and traversing system called BridgeBot, is designed to aid in the inspection of steel and concrete girder bridges. BridgeBot has evolved in four prototypes (I-IV) for improved structural, mechanical, electronic, and control systems over the past five years. The first two prototypes built in Phases I and II were tested in laboratory to understand the feasibility of hybrid flying and …

Final Report - Robot-Assisted Underwater Acoustic Imaging For Bridge Scour Inspection, Genda Chen, Peter Ogunjinmi, Son Nguyen

Project AS-8

This report details the development and testing of an innovative robotic system for underwater mapping and bridge scour inspection, integrating a 3D sonar with a modified remotely operated vehicle (ROV). The system addresses limitations in traditional scour monitoring methods, such as safety concerns and poor visibility after flooding. The research approach included laboratory experiments, pool testing, and field trials at two bridge sites in Missouri, with procedures developed for both water surface and underwater deployments. The system effectively mapped underwater structures and scour conditions, especially in hard-to-reach areas, revealing critical scouring, exposed pier footings and debris accumulation. The water surface …

Asphalt-Binder Mixtures Evaluated By T1 Nmr Relaxometry, Rebecca M. Herndon, Jay Balasubramanian, Magdy Abdelrahman, Klaus Woelk

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asphalt pavements make up a majority of the essential transportation systems in the US. Asphalt mixtures age and degrade over time, reducing the pavement performance. Pavement performance critically depends on the aging of asphalt binder. the aging of asphalt binder during construction is traditionally modeled by rolling thin film oven (RTFO) testing, while aging during service life is modeled by pressure aging vessel (PAV) testing. Comparing these models to the aging of binders in actual pavements is limited because, to be used for current testing, binders must be separated from the pavement's aggregate by solvent extraction. Solvent extraction will, at …

Asphalt-Binder Mixtures Evaluated By T1 Nmr Relaxometry, Rebecca M. Herndon, Jay Balasubramanian, Magdy Abdelrahman, Klaus Woelk

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asphalt pavements make up a majority of the essential transportation systems in the US. Asphalt mixtures age and degrade over time, reducing the pavement performance. Pavement performance critically depends on the aging of asphalt binder. The aging of asphalt binder during construction is traditionally modeled by rolling thin film oven (RTFO) testing, while aging during service life is modeled by pressure aging vessel (PAV) testing. Comparing these models to the aging of binders in actual pavements is limited because, to be used for current testing, binders must be separated from the pavement's aggregate by solvent extraction. Solvent extraction will, at …

Nuclear Magnetic Resonance (Nmr) Assessment Of Bio And Crude Oil-Based Rejuvenation, Rebecca M. Herndon, Jay Balasubramanian, Magdy Abdelrahman, Klaus Woelk

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asphalt binders in pavements lose their stability through aging and eventually fail in the field. Using nuclear magnetic resonance (NMR) to monitor the primary longitudinal relaxation time of asphalt samples and the ratio of material that carries this primary relaxation time has been shown to indicate the impact of ultraviolet (UV) radiation on the aging of asphalt pavements. Longitudinal NMR relaxation was used to investigate two types of proposed asphalt rejuvenators, a bio-oil-based rejuvenator and a crude-oil-based rejuvenator. Two different binders with the performance grades (PG) 64-22 and 76-22 were considered for their interactions with the rejuvenators. After 72 h …

Final Report - Nondestructive Data Driven Motion Planning For Inspection Robots, Hung Manh La

Project AS-5

This report presents the development and implementation of autonomous navigation systems for steel bridge inspection robots, designed to enhance the efficiency and safety of bridge maintenance. The Advanced Robotics and Automation (ARA) lab has developed innovative climbing robots capable of operating in complex environments using a hybrid approach that combines mobile and inch-worm-inspired locomotion modes. A novel control and navigation framework has been proposed, featuring algorithms for surface detection, path planning, and mode switching based on 3D point cloud data. The effectiveness of these systems has been validated through experiments on steel bridge structures, demonstrating the potential for real-world application …

Final Report - Integration Of Aerial Manipulation, Haptics-Based Human-In-The- Loop Control, And Augmented Reality For Bridge Deck Hosing, Paul Oh, Blake Hament, Dongbin Kim

Project AS-9

This Year 5 and Year 6 report integrates the designs, analyses, and results of the previous years. These have culminated into the design, development and deployment of a hosing-drone. This drone carries and 3000 PSI (pounds per square inch) pressure washer often used to clean bridges. This accomplishment leverages the work in aerial manipulation, human-in-the-loop control, haptics, and augmented- and virtual-reality (AR/VR) executed in prior years. Additionally, this report presents results using a cable-driven parallel robot (CDPR) and telescopic mast. This robot provides another platform that has applications in bridge inspection, maintenance and repair.

Influence Of Aggregate Properties On Skid Resistance Of Pavement Surface Treatments, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Skid resistance is a critical aspect for traffic safety since it significantly influences vehicle control and minimizes the distance required for emergency braking. The surface characteristics of pavements play a pivotal role in determining skid resistance. To achieve the optimal skid resistance performance, the pavement must sustain a specific level of friction. Thus, it is advantageous to apply surface treatments in areas that require enhanced friction. This study investigates the impact of factors such as the aggregate source, size, morphological properties, and abrasion levels on the skid resistance and frictional characteristics of a high-friction surface treatment (HFST). A complete investigation …

The Effectiveness Of Waste Tire Pyrolysis Oils (Wtpos) As Rejuvenating Agents For Asphalt Materials, Ahmed S. El-Ashwah, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The continuous increase in solid waste materials, such as waste tires, underscores the critical importance of recycling them to mitigate environmental impact and promote sustainable resource management. This research study evaluated the effectiveness of utilizing waste tire pyrolysis oils (WTPOs) as recycling agents for asphalt materials. The chemical composition and thermal behavior of WTPO were analyzed using Fourier transform infrared (FT-IR) spectroscopy and thermogravimetric analysis (TGA). Mechanically, the prepared WTPO binders were assessed by measuring dynamic viscosity and changes in high- and intermediate-temperature performance grades. Additionally, the cracking susceptibility of the binders was evaluated using the Glover-Rowe (G-R) parameter. The …

Early Detection Of Pipeline Natural Gas Leakage From Hyperspectral Imaging By Vegetation Indicators And Deep Neural Networks, Pengfei Ma, Tarutal Ghosh Mondal, Zhenhua Shi, Mohammad Hossein Afsharmovahed, Kevin Romans, Liujun Li, Ying Zhuo, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt detection. This study explores the utility of Vegetation Indicators (VIs) to reflect vegetation health deterioration, thereby representing leak-induced stress. Despite the acknowledged potential of VIs, their sensitivity and separability remain understudied. In this study, we employed ground vegetation as biosensors for detecting methane emissions from underground pipelines. Hyperspectral imaging from vegetation was collected weekly at both plant and leaf scales over two months to facilitate stress detection …

Experimental Study On The Detection Of The Existence And Location Of Mimicked And Unexpected Interface Debonding Defects In An Existing Rectangular Cfst Column With Pzt Materials, Qian Liu, Bin Xu, Genda Chen, Weilong Ni, Zhixun Liu, Chun Lin, Zhiyou Zhuang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Interface bonding conditions between concrete and steel materials play key roles in ensuring the composite effect and load-carrying capacity of concrete–steel composite structures such as concrete-filled steel tube (CFST) members in practice. A method using both surface wave and electromechanical impedance (EMI) measurement for detecting the existence and the location of inaccessible interface debonding defects between the concrete core and steel tube in CFST members using piezoelectric lead zirconate titanate (PZT) patches as actuators and sensors is proposed. A rectangular CFST specimen with two artificially mimicked interface debonding defects was experimentally verified using PZT patches as the actuator and sensor. …

Final Report - Data-Driven Risk-Informed Bridge Asset Management And Prioritization Across Transportation Networks, Iris Tien, Yijian Zhang

Project RR-2

This project aims to transform inspection data into risk-informed decision-making, leading to two main advancements. First, a new method is developed to account for the combined effect of soil stress history and scour hole on laterally and axially loaded piles in sand and clay. The methodology is validated with results from field tests for no-scour scenarios and verified with numerical models for scour scenarios. Quantification of the soil effects is investigated through lateral pile deflection and load-settlement curves for lateral and axial behaviors, respectively. Stress history increases up to 34.1% and 61.1% in estimated pile settlement for sand and clay, …

Final Report - Health Inspection Of Concrete Pavement And Bridge Members Exposed To Freeze-Thaw Service Environment, Hongyan Ma, Genda Chen, Kangyi Cai, Rezwana Hafiz

Project SN-7

This project proposed an integrated approach for the non-destructive evaluation of the health status – represented by compressive strength – of any concrete, including well-cured (or intact) and degraded (or partially damaged) due to freeze-thaw cycling. To use this approach, no pre-recorded information (e.g., mixture proportions of concrete, curing and maintenance history, and service history) is needed. Instead, several conventional non-destructive testing methods (NDTs), assisted by hyperspectral camera, can be employed to generate a dataset that informs a pre-trained artificial intelligence (AI) to predict strength. As the core of this approach, the dedicated AI was trained through this project. To …

Final Report - Smart Sounding System For Autonomous Evaluation Of Concrete And Metallic Structures, Anil K. Agrawal, Deepak Kumar

Project IM-3

Recent research by the authors has shown that the sounding, such as chirp signal, can be generated by electronic speakers, and their magnitude and frequency can be controlled. Unlike mechanical impact hammers, the electronic sounding is consistent and can be designed with controlled frequency characteristics to excite defects in concrete decks. Another significant limitation of mechanical impact hammers is that the bottom of a deck cannot be conventionally sounded, and determination of precise location of the damaged area is a challenge. To address these limitations, a “smart sounding system” has been developed that can be used to inspect the underdeck …

Final Report - Autonomous Ultrasonic Thickness Measurement By A Magnet-Wheeled Robot, Yang Wang, Hung Manh La, Yu Otsuki, Son Thanh Nguyen

Project SN-6

This project develops a compact ultrasonic thickness sensing device that is integrated with a steel-climbing bicycle robot for autonomous thickness measurement of steel bridge members. With wireless communication capability, the ultrasonic sensing device can perform high-voltage pulse excitation, filtering and amplification of the received ultrasonic signal, and high-speed analog-to-digital conversions (up to 80 MHz). After successful validations of the device, it is integrated into a bicycle-like robot with two magnetic wheels controlled by two independent steering actuators that navigates on various steel surfaces (flat, curved, rough, concave, and convex). Along with the wireless ultrasonic sensing device, the robot carries a …

Predicting Flexural-Creep Stiffness In Bending Beam Rheometer (Bbr) Experiments Using Advanced Super Learner Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

BBR test is commonly used to assess the low-temperature performance grade (PG) of asphalt binders, with the flexural-creep stiffness being a critical parameter calculated through this test. However, it has notable limitations that demand attention. The significant amount of asphalt binder needed for test specimens increases costs and resource consumption. Additionally, the complex and time-consuming specimen preparation process hinders testing efficiency and introduces result variability, affecting the accuracy and reliability of PG determinations. In recent years, machine learning (ML) has emerged as a promising substitute for predicting various engineering values. In this study, the primary focus was on harnessing super …

Final Report - A Field Deployable Wall-Climbing Robot For Bridge Inspection Using Vision And Impact Sounding Techniques, Jizhong Xiao, Ejup Hoxha, David Kirakosian

Project AS-6

This project developed two wall-climbing robots and two omni-directional ground robots for automated data collection on both horizontal and vertical surfaces of concrete structures. These robots are equipped with non-destructive evaluation (NDE) sensors, including ground penetrating radar (GPR), impact sounding (IS) and impact echo (IE) devices. Utilizing a vision-based positioning system powered by simultaneous localization and mapping (V-SLAM), the robots tag NDE data with real-time pose information, significantly accelerating the data collection process and enhancing the accuracy of defect mapping. While effective at detecting shallow defects, impact sounding is highly sensitive to ambient noise and unsuitable for identifying deeper flaws. …