Engineering Commons^™

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Publications

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R² (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Data

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R² (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

Alternative Supplementary Cementitious Materials In Ultra-High Performance Concrete, Craig Newtson, Seyedsaleh Mousavinezhad, Gregory J. Gonzales, William K. Toledo, Judit M. Garcia

Publications

Ultra-high performance concrete (UHPC) is an emerging material with remarkable mechanical and durability properties that contains large amounts of cementitious materials. Silica fume is a main supplementary cementitious material (SCM) in UHPC, however, it is more expensive than cement and other SCMs, so it is often substituted with inexpensive class F fly ash. Unfortunately, future availability of fly ash is uncertain as the energy industry moves toward renewable energy. Fly ash shortages create an urgent need to find cost-effective and environmentally-friendly alternatives for fly ash. This study investigated replacing cement, fly ash, and silica fume in UHPC mixtures with ground …

A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal

Data

Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …

Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli

Data

Arkansas produces the most of the rice in the United States. About 20% of poddy is rice husk (RH), which is burnt under controlled conditions to produce rice rusk ash (RHA). The RHA is considered an environmental hazard and a significant challenge for rice millers. However, RHA is rich in pozzolanic material, which is mainly silica. In this study, RHA is used to stabilize poor soils. Another commonly used stabilizer, hydrated lime (HL), has also been evaluated for comparison purposes. Thus, this study aimed to determine the optimum percentages of RHA, HL, or a combination of these two agents by …

Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang

Publications

The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …

Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt

Data

Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …

Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang

Data

The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …

Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan

Data

Performance prediction models are used by state agencies to predict future trends in distress indices, hence, determining the required maintenance and/or rehabilitation treatment as well as the deterioration rate and remaining pavement service life. However, most of these models are based on a limited number of parameters and cannot predict the performance distress indices reliably. Such limitation resulted in having, most of the time, a maximum prediction period of five years. As a solution and coping with the ever-increasing size of pavement data, machine learning techniques have become a promising alternative. The objective of this study was to develop a …

Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D

Publications

Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …

Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D

Data

Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …

Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt

Publications

Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …

Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras

Electrical and Computer Engineering Faculty Publications

In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …

Exploratory Analysis Of Machine Learning For Images: Methods And Applications, Meenu Ajith

Electrical and Computer Engineering ETDs

This research focuses on implementing four different applications of machine learning on images. The various categories of digital images considered for these applications are grayscale, RGB, and infra-red images. The first framework uses an unsupervised learning strategy for detecting fire and smoke from an infra-red image dataset. This problem was solved using a classical machine learning algorithm since the dataset was small and unlabeled. Next, a semi-supervised deep learning model was used for facial expression recognition. Here we detect emotions from a moderately large dataset containing labeled and unlabeled grayscale images. The third application focused on single image superresolution, which …

Mechanizing The Removal Of Soil Between Peach Trees Planted On Berms, Coleman Scroggs

All Theses

Armillaria root rot (ARR), primarily caused by the soilborne fungus Desarmillaria tabescens, has become the number one cause for peach tree decline in the Southeastern United States. Research has shown that planting peach trees on shallow berms and excavating the soil around the root collar two years after planting lessens the effects of ARR. However, berms make orchard operations such as pruning, thinning, and harvesting more cumbersome and cause cultural concerns as channels of water at their base can lead to erosion and the slope of the berms leads to herbicide and fertilizer runoff. The objective of this research was …

Sub-Bandgap Photon-Assisted Electron Trapping And Detrapping In Algan/Gan Heterostructure Field-Effect Transistors, Andrew Gunn

All Theses

We have investigated photon-assisted trapping and detrapping of electrons injected from the gate under negative bias in a heterostructure field-effect transistor (HFET). The electron injection rate from the gate was found to be dramatically affected by sub-bandgap laser illumination. The trapped electrons reduced the two-dimensional electron gas (2DEG) density at the AlGaN/GaN heterointerface but could also be emitted from their trap states by sub-bandgap photons, leading to a recovery of 2DEG density. The trapping and detrapping dynamics were found to be strongly dependent on the wavelength and focal position of the laser, as well as the gate bias stress time …

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

Pressure-Induced Phase Transition And Electronic Structure Changes In Equiatomic Fev, Homero Reyes Pulido

Open Access Theses & Dissertations

Classical molecular dynamics methods can accurately describe a broad set of many-atomssystems. Although more economical, the results given by this framework lack the precision capable of density functional theory (DFT). Therefore, the structural stability of the B2 phase of a body-centered-cubic iron-vanadium (FeV) alloy using DFT on the electronic structure level is analyzed to verify and further explain classical results obtained by our group in this same alloy. Using Quantum Espresso and Phonopy for the computational simulations, the plotted band structure, electronic density of states (eDOS), phonon dispersions, charge density, and Fermi surfaces for various compressed unit cells are presented. …

Development Of Balanced Mix Design Quality Control Specifications Based On The Acceptance Limits Of Hma Performance Tests, Lucas Tameirao Abrantes

Open Access Theses & Dissertations

With the augmented use of recycled materials, recycling agents, modified binders, andwarm mix asphalt additives, several highway agencies including the Texas Department of Transportation (TxDOT), have considered methods to improve the durability and long-term performance of asphalt concrete (AC) mixes. The need for performance tests that could consistently evaluate the rutting and cracking potentials of AC mixes became crucial as the popularity of the Balanced Mix Design (BMD) concept has increased over the years. A concern now is related to the practicality of these tests for routine use in the process of quality control and quality assurance during the field …

Miner-Town: Self-Driving Robotics Testbed For Vehicle-To-Grid Simulation, Carlos Adolfo Cortes Pliego

Open Access Theses & Dissertations

Autonomous vehicles and Vehicle-to-Grid (V2G) technology bring promising implications in boosting energy efficiency, helping the environment, improving our productivity, and have the potential to stabilize the grid during peak times and reduce car accidents. However, implementing and testing these complex novel technologies in the real world comes with high risks and investment. For these reasons, there is the need to research, test, and validate these theories in a compact and controlled environment at minimal cost. This thesis presents a modular autonomous vehicle testbed for the exploration of Vehicle-to-Grid and charging activities in pedestrian filled environments such as a University campus. …

Multi-Sensor Signatures From Ultrasonic Wire Embedding Used In Hybrid Additive Manufacturing, Patrick Steven Gutierrez

Open Access Theses & Dissertations

Additive Manufacturing (AM) has matured such that its products are used in applications ranging from prototypes to end-use parts; however, to expand the adoption of AM, the inclusion of multiple manufacturing technologies has become a focus area especially when the result is a 3D printed part with an embedded electrical system. The W.M. Keck Center for 3D Innovation has developed the Foundry Multi3D system consisting of two material extrusion AM machines, a robotic arm, and a CNC machine equipped with a laser soldering tool, solder micro-dispensing tool and an ultrasonic wire embedding (USWE) tool. The focus of this paper is …

Krs And Kar Review Of Models As A Legal Contract Document, Bryan Gibson, Pam Clay-Young, Rachel Catchings, Chris Van Dyke

Kentucky Transportation Center Research Report

State departments of transportation (DOTs) are expanding the use of electronic engineering data (EED) throughout highway projects — from design and construction through asset management. Included under the umbrella of EED are technologies such as building information modelling (BIM), digital terrain models (DTMs), and 3D models and plan sets. The Kentucky Transportation Cabinet’s (KYTC) Digital Project Delivery (DPD) Initiative is spearheading the transition to EED in the state. While digital delivery promises to streamline project development and management it does not come without hurdles. This report discusses methods for agency wide implementation of EED and highlights best practices for managing, …

Femtosecond Laser Surface Processing To Create Self-Organized Micro- And Nano-Scale Features On Composite And Ceramic Materials, Nate Koeppe

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Femtosecond laser surface processing (FLSP) is applied to a range of materials in this thesis. The materials studied were a carbon fiber reinforced polymer (CFRP), a thermosetting polymer, silicon nitride (Si₃N₄), and ceramic alumina. The CFRP is a composite material consisting of a thermosetting polymer and carbon fibers. The CFRP are referred to as a composite and the thermosetting polymer is referred to as a resin in this thesis. Alumina can exist in many different forms. The alumina used is 0.5 mm thick nonporous alumina sheets purchased from McMaster-Carr, and will be referred to as alumina …

Piezoelectric Point-Of-Care Biosensor For The Detection Of Sars-Cov-2 (Covid-19) Antibodies, Debdyuti Mandal, Mustahseen M. Indaleeb, Alexandra Younan, Sourav Banerjee

Faculty Publications

It is always challenging to diagnose a disease using a biosensor reliably, and quickly with high sensitivity and selectivity, simultaneosuly. Recently the world experienced a global pandemic caused by a novel coronavirus (COVID-19). Although the vaccines are available, COVID-19 resulted a huge threat to the entire world with high mortality rates. Irrespective of a specific disease, there is a constant need for a cheaper and faster in-vitro, lab-on-a-chip sensor with high sensitivity and selectivity. Such sensors will not only facilitate the disease detection but will expedite and vaccine development process through detection of its corresponding antibodies when developed. In this …

Controlled Manipulation Of Droplets On Fibers: Fundamentals And Printing Applications, Yueming Sun

All Dissertations

In this dissertation, the drop interactions with a single fiber is discussed under an application angle for the development on new Drop-on-Demand (DOD) printhead using a fiber-in-a-tube platform[1] to print highly viscous materials[2]. To control the drop formation and manipulation on fiber, one needs to know how the fiber wetting properties and the fiber diameter influence drop formation. And then, one needs to know the effects of fiber movement in the device on drop formation. These two questions constitute the main theme of this dissertation.

Before this study, it was accepted that the liquids could not form axisymmetric droplets if …

Act5 Eit System : A Multiple-Source Electrical Impedance Tomography System, Omid Rajabi Shishvan

Legacy Theses & Dissertations (2009 - 2024)

This dissertation describes the design and implementation of Adaptive Current Tomograph 5 (ACT5) with a focus on the digital processing and data ow in the instrument. ACT5 is an electrical impedance tomography (EIT) instrument that produces images of the complex impedivity distribution within the body by injecting currents through and measuring voltages on electrodes applied to the skin. ACT5 is a parallel-drive EIT system with a dedicated current source for each electrode, capable of driving all electrodes simultaneously and measuring the induced voltages on them. It can support up to 48 electrodes with a frequency range of 5 kHz to …

Design And Implementation Of A Novel Eit/Ecg System With An Adaptive Current Source Act-5 / Narrative Competence And Cognitive Mapping As A Culturally Sustaining Pedagogy In The Education Of Emergent Bilinguals, Ahmed Abdelwahab

Legacy Theses & Dissertations (2009 - 2024)

Electrical Impedance Tomography (EIT) is a promising medical imaging technique used to detect the body's internal electrical characteristics based on electrical measurements made on its surface. EIT systems, particularly those that use parallel, multiple source architectures, require current sources with very high output impedance. This is a usual challenge for EIT as the practical current sources come with finite output impedance, which is highly degraded as the operation frequency gets wider. To overcome this challenge and maintain the high output impedance requirement, sources often use complex analog circuits which require manual or electronically-controlled adjustments.

Effects Of Imu Sensor Location And Number On The Validity Of Vertical Acceleration Time-Series Data In Countermovement Jumping, Dianne Althouse

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Many devices are available for measuring the height of a CMJ. An inertial measurement unit (IMU) measures linear acceleration, orientation, and angular velocity. As an alternative to using IMU estimates of flight time, CMJ height could be estimated by integrating the IMU time-series signal for vertical acceleration to derive CMJ take-off velocity in order to track whole-body center of mass (WBCoM) movement, yet this approach would require valid IMU acceleration data. Thus, the purpose of this study was to quantify the effects of IMU sensor location and number on the validity of vertical acceleration estimation in CMJ. Thirty young adults …

Student Training For Motor Performance Assessment In Industry, Jaime Ramos-Salas, Miguel Pineda

Electrical and Computer Engineering Faculty Publications

Energy used by electric motors in the USA According to the US Department of Energy [1], electric motors consume more than 50 percent of all electrical energy in the USA and more than 85 percent of industrial production electrical energy [2]. Furthermore, during the estimated life of an electric motor, approximately 20 years, its initial purchase price is less than 2 percent of the total cost of owning and operating it [3]. 2- The main objective of this work is to share our experience of training university students for performing electric motors energy assessments to local industries with a limited …

Lifetime Maximization In Underwater Wireless Communication Networks, Kazi Yasin Islam, Iftekhar Ahmad, Daryoush Habibi, Jiong Jin, Muhammad Waqas

Research outputs 2022 to 2026

The rise in demand for underwater wireless communication networks (UWCN) has been driven by the emergence of new applications including unmanned underwater vehicles, deep-sea exploration, maritime and underwater archaeology research, and diver communications. For various applications, underwater network lifetime must be long, since unlike terrestrial sensor networks, it is a major job to change/recharge node batteries in underwater environments. In this paper, we introduce a solution where critical nodes in a UWCN are periodically recharged by small renewable energy sources. Further, a caching mechanism is introduced to relieve critical nodes of heavy workload when their residual energies run low. By …