Engineering Commons^™

Moisture Affinity Of Hdpe/Phase-Change Material Composites For Thermal Energy Storage Applications, Sandra K. Boetcher, Thomas B. Freeman, Rafael M. Rodriguez, Kashif Nawaz

Publications

Moisture adsorption can degrade the structural integrity of thermal energy storage devices and can negatively impact the capacity and charging/discharging behavior. Steady-state and transient experiments are conducted at various operating temperatures to evaluate the moisture affinity of organic phase-change material (PCM) shape stabilized with high-density polyethylene (HDPE).

Improvement On Pdp Evaluation Performance Based On Neural Networks And Sgdk-Means Algorithm, Fan Deng, Houbing Song, Zhenhua Yu, Liyong Zhang, Xi Song, Min Zhang, Zhenyu Zhang, Yu Mei

Publications

With the purpose of improving the PDP (policy decision point) evaluation performance, a novel and efficient evaluation engine, namely XDNNEngine, based on neural networks and an SGDK-means (stochastic gradient descent K-means) algorithm is proposed. We divide a policy set into different clusters, distinguish different rules based on their own features and label them for the training of neural networks by using the K-means algorithm and an asynchronous SGDK-means algorithm. Then, we utilize neural networks to search for the applicable rule. A quantitative neural network is introduced to reduce a server’s computational cost. By simulating the arrival of requests, XDNNEngine is …

Durability Of Concrete Produced With Alternative Supplementary Cementitious Material, Craig Newtson, Brad Weldon, Judit Garcia, Seyedsaleh Mousavinezhad, William Toledo

Publications

Historically, Class F fly ash has been chosen as a supplementary cementitious material (SCM) in concrete for its ability to mitigate alkali-silica reaction (ASR). However, future availability of fly ash is uncertain because the energy industry has been investing in renewable energy production and removing coal burning generating stations from operation. Consequently, there is a growing need to find new, cost effective and environmentally friendly alternatives to fly ash. This study investigated a locally available natural pozzolan mined from a pumicite deposit near Espanola, NM for its ability to mediate ASR. Concrete and mortar mixtures included SCM contents ranging from …

Analyzing The Effect Of Delta Airlines' Fleet Upgrade On Operations At Atlanta-Hartsfield Jackson International Airport, Carlos Alberto Castro, Shlok Misra

Publications

Commercial aviation has seen a growth in terms of passengers traveled and flights operated in the past decade (BTS, 2020). To cope up with this growth, airlines adopt various strategies such as network expansion and fleet upgrades. Airlines adopt fleet upgrade strategies to modernize their fleet, reduce costs, expand network coverage, and improve customer loyalty and experience. Research suggests that change in wake turbulence categorization and aircraft performance can directly impact the movements and delays at an airport. For this study, Delta Airline's fleet upgrade program and its effect on operating parameters at Atlanta-Hartsfield Jackson International Airport were analyzed. The …

Student Engagement In Aviation Massive Open Online Courses (Moocs), Jennifer M. Edwards, Haydee M. Cuevas, Felix Brito, Mark Friend, Maryjo O. Smith

Publications

As online training in the aviation industry continues to expand, understanding how learners engage in open online courses may help inform course design. Currently little is known about student engagement in aviation Massive Open Online Courses (MOOCs) and more information is needed about those who utilize, but do not complete them. Datasets from two aviation MOOCs were cluster-analyzed to determine subpopulations based on activity (discussions, videos, quizzes). Differences were examined for days of activity and completion. Survey data revealed differences in demographics and learning goals. Three significantly different subgroups were found for each MOOC. Engagement patterns were similar between corresponding …

Zero-Bias Deep Neural Network For Quickest Rf Signal Surveillance, Yongxin Liu, Jian Wang, Dahai Liu, Houbing Song, Yingjie Chen, Shuteng Niu

Publications

The Internet of Things (IoT) is reshaping modern society by allowing a decent number of RF devices to connect and share information through RF channels. However, such an open nature also brings obstacles to surveillance. For alleviation, a surveillance oracle, or a cognitive communication entity needs to identify and confirm the appearance of known or unknown signal sources in real-time. In this paper, we provide a deep learning framework for RF signal surveillance. Specifically, we jointly integrate the Deep Neural Networks (DNNs) and Quickest Detection (QD) to form a sequential signal surveillance scheme. We first analyze the latent space characteristic …

Systematic Review And Regression Modeling Of The Effects Of Age, Body Size, And Exercise On Cardiovascular Parameters In Healthy Adults, Aseem Pradhan, John Scaringi, Patrick Gerard, Ross Arena, Jonathan Myers, Leonard A. Kaminsky, Ethan Kung

Publications

Purpose

Blood pressure, cardiac output, and ventricular volumes correlate to various subject features such as age, body size, and exercise intensity. The purpose of this study is to quantify this correlation through regression modeling.

Methods

We conducted a systematic review to compile reference data of healthy subjects for several cardiovascular parameters and subject features. Regression algorithms used these aggregate data to formulate predictive models for the outputs—systolic and diastolic blood pressure, ventricular volumes, cardiac output, and heart rate—against the features—age, height, weight, and exercise intensity. A simulation-based procedure generated data of virtual subjects to test whether these regression models built …

Plaque Contact Surface Area And Flow Lumen Volume Predict Stroke Risk In Extracranial Carotid Artery Stenosis, Ryan Gendey, Ethan Kung, Veena Mehta, Adam Brown, Matthew Bridges, Ravi Veeraswamy

Publications

The standard indication for intervention in asymptomatic disease is currently percent stenosis in the internal carotid artery as measured by the NASCET method, which remains limited in discriminating power. CT angiography (CTA) is widely used to calculate NASCET stenosis but also offers the opportunity to analyze carotid artery plaques from a morphological perspective that has not been widely utilized. We aim to improve stroke risk stratification of patients with carotid artery stenosis using plaque 3D modeling and image analysis. Patients with CTAs appropriate for 3D reconstruction were identified from an NIH designated stroke center database, and carotid arteries were segmented …

General Aviation Flight Safety During The Covid-19 Pandemic, Douglas D. Boyd

Publications

BACKGROUND/OBJECTIVE: The COVID-19 virus has caused over 582,000 deaths in the United States to date. However, the pandemic has also afflicted the mental health of the population at large in the domains of anxiety and sleep disruption, potentially interfering with cognitive function. From an aviation perspective, safely operating an aircraft requires an airmans cognitive engagement for: 1) situational awareness, 2) spatial orientation, and 3) avionics programming. Since impaired cognitive function could interfere with such tasks, the current study was undertaken to determine if flight safety for a cohort of single engine, piston-powered light airplanes was adversely affected during a period …

Exploring Traffic Safety Problems And Challenges Of Older Roads’ Users In Louisiana: Causes And Countermeasures, Hany Hassan Ph.D, Saba Doulabi

Publications

It is well established that older pedestrians and drivers with 65 years and above are among the most vulnerable road users. As the number and proportion of older road users (as drivers and pedestrians) grows in many countries, as well as their share in pedestrians’ and drivers’ crashes and injuries, it behooves transportation researchers to further investigate the safety and mobility challenges of older road users. This study aims mainly to provide a comprehensive investigation of older pedestrians’ and drivers’ safety challenges. To this end, a three-fold research approach is designed to thoroughly examine older road users’ safety challenges as …

Calculating Pile Downdrag: Experimental And Numerical Investigations, Hai Lin, Shengli Chen, Hussein Alqrinawi

Publications

Piles can be exposed to significant settlement (i.e., downdrag) and compressive force (i.e., dragload) if embedded in consolidating ground. Downdrag has been included in the design of piles, but there is uncertainty about how downdrag and dragload are efficiently considered in the pile design due to the differences in the existing design methods (e.g., AASHTO and FHWA). Although several field monitoring programs were successfully conducted on pile downdrag, fully instrumented pile model tests are still needed to investigate the responses at the soil-pile interface to improve the design of pile downdrag. This research focused on investigating the downdrag and skin …

Developing Notification And Enforcement Systems To Communicate And Administer Bridge Load Postings, Hany Hassan, Hisham Abdu Kunnah

Publications

State and local law enforcement agencies in the US strive to enforce weight restrictions on trucks and heavy vehicles travelling on public roads as a matter of public safety and as a way of safeguarding vital transportation infrastructure. This research aimed to identify plausible notification systems that can effectively communicate bridge load postings to dispatchers and drivers, investigate and suggest possible approaches to communicate potential detour routes, and identify corresponding enforcement methods required to successfully administer bridge load postings. This report discusses the current practices of bridge load posting notification and enforcement systems. Also, it presents an overview of the …

An Innovative Thermo-Energy Harvesting Module For Asphalt Roadway Pavement, Seyed Amid Tahami, Samer Dessouky

Publications

The importance of green technologies for generating renewable energy and sustainable development is widely accepted. Road surfaces are exposed to solar radiation that generates thermal gradients and heat flow in the pavement layers. The heat stored can be harvested providing an untapped source of renewable energy. This report presents the design, construction, and assessment of an improved thermoelectric energy prototype for harvesting heat energy from roadway pavements. To accomplish this, various prototype designs were simulated using Finite Element (FE) analysis, followed by design construction and laboratory testing of the most promising prototypes to evaluate their power harvesting capabilities. The main …

Urban Transportation Infrastructure And Cyclist And Pedestrian Safety, Hatim Sharif, Samer Dessouky

Publications

The goal of this project was to perform a comprehensive evaluation of crash causes and risk factors to identify the root causes of crashes involving bicyclists and pedestrians in San Antonio, TX. The research included the development of a database of bicycle and pedestrian crash reports in the target area, calculation of crash counts and rates, identifying road segments and intersections with highly concentrated bicycle and pedestrian crashes, and the development of effective safety countermeasures. Several variables and factors were analyzed, including driver characteristics such as age and gender, road-related factors, and environmental factors such as weather conditions and time …

Coupling Novel Soil Moisture-Suction Sensors And Uav Photogrammetry Technology To The Performance Of Highway Embankments, Navid Jafari, Anand Puppala, Xinbao Yu, Surya Sarat Chandra Congress

Publications

The movement of water plays a critical role in the mechanical performance and service life of transportation infrastructure, especially for pavement subgrades and highway embankments consisting of high-plasticity, expansive soils that saturate and ultimately lead to infrastructure distress. Shallow slides along highway embankments are ubiquitous across Region 6 because long-term wetting and drying cycles considerably weaken these compacted soils. In the aftermath of heavy rains, pore-water pressures increase to a critical threshold such that a failure occurs. The implications of embankment failures range from repeated maintenance repairs to long-term road closures. A comprehensive approach to model highway embankments comprising of …

Rapid Repair Of Cracks On The Embankment Slopes Using Bio-Cement, Hai Lin, Guantao Cheng

Publications

This research explored the feasibility of using Microbially Induced Carbonate Precipitation (MICP) to improve fine-grained soil mechanical properties, seal the soil cracks, and assess the improvement of MICP on slope stability. The conducted research tasks include (1) direct shear tests to investigate the mechanical behavior and biogeochemical reactions of low-plasticity silt treated by MICP, (2) cyclic wetting-drying tests to assess the feasibility of using MICP to seal and waterproof the soil cracks, and (3) SLOPE/W modeling of a slope treated by MICP. Direct shear tests were used to evaluate the shear responses of the low-plasticity silt under different overburden pressures …

Aessa Young Professionals Forum Webinar “Technologies And Skills That Will Gearup The Aerospace Industry Post Pandemic” - A Global Perspective With An Emphasis On South Africa October 2021, Linda Vee Weiland

Publications

A webinar presentation for AeSSA Young Professionals.

Assessment Of Conventional And Air-Jet Wheel Deflectors For Drag Reduction Of The Drivaer Model, Sandra K. S. Boetcher, Kaloki L. Nabutola

Publications

Aerodynamic drag is a large resistance force to vehicle motion, particularly at highway speeds. Conventional wheel deflectors were designed to reduce the wheel drag and, consequently, the overall vehicle drag; however, they may actually be detrimental to vehicle aerodynamics in modern designs. In the present study, computational fluid dynamics simulations were conducted on the notchback DrivAer model—a simplified, yet realistic, open-source vehicle model that incorporates features of a modern passenger vehicle. Conventional and air-jet wheel deflectors upstream of the front wheels were introduced to assess the effect of underbody-flow deflection on the vehicle drag. Conventional wheel-deflector designs with varying heights …

Viability And Application Of Mounting Personal Pid Voc Sensors To Small Unmanned Aircraft Systems, Cheri Marcham

Publications

Small Unmanned Aerial Systems in Emergency Response

Current sUAS Uses

• Search and rescue
• Thermal imaging
• Evaluating structural stability
• Spread of wildfires
• Storm damage

Multifunctional Corrosion Control System As A Sustainable Approach For Reinforced Concrete Elements, Homero Castaneda, Miladin Radovic, Brendy Rincon, Oladis Troconis, Arturo Montoya, Changkyu Kim, Loreto Dacio

Publications

Corrosion inhibitors can be utilized to decrease the corrosion kinetics and therefore increase the durability of reinforced concrete structures. Recently, a green synthesized organic compound, 1-benzyl-4-phenyl-1H-1,2,3-triazole (BPT), was shown to be a successful green organic corrosion inhibitor for mild steel. Studies suggested that the BPT adsorbs chemically onto the steel and acts as a mixed inhibitor, suppressing both the anodic and cathodic corrosion kinetics of steel. In addition, microcapsules have shown to be an efficient way for a controlled inhibitor release in reinforced concrete structures. On the other hand, geopolymers (GPs) comprised of a long range of covalently bonded alumino-silicates, …

Efficient, Low-Cost Bridge Cracking Detection And Quantification Using Deep-Learning And Uav Images, Chao Sun, Xiangyu Meng, Joshua O. Ogbebor, Shaopan Guo

Publications

Many bridges in the State of Louisiana and the United States are working under serious degradation conditions where cracks on bridges threaten structural integrity and public security. To ensure structural integrity and public security, it is required that bridges in the US be inspected and rated every two years. Currently, this biannual assessment is largely implemented using manual visual inspection methods, which is slow and costly. In addition, it is challenging for workers to detect cracks in regions that are hard to reach, e.g., the top part of the bridge tower, cables, mid-span of the bridge girders, and decks. This …

Autonomous Vehicle Communication Strategies Modeled In Virtual Reality, Nick N. Ferenchak Ph.D

Publications

We sought to better understand how autonomous vehicle (AV) communication strategies impact human road users’ perceptions and behaviors. More specifically, we explored the impact of different external human-machine interface (eHMI) designs on understanding, task load, comfort, trust, acceptance, and reaction time. To accomplish this, we created virtual reality (VR) scenarios where human participants interacted with AVs. Participants experienced biking, driving, and pedestrian simulators and were brought back after initial testing to explore acclimation and learning effects. In terms of perceptions, the presence of an eHMI was the strongest predictor of understanding, comfort, trust, and acceptance outcomes in the statistical models …

Development Of Novel Ultra-High Performance Engineered Cementitious Composites (Uhp-Ecc) For Durable And Resilient Transportation Infrastructure, Gabriel A. Arce, Marwa Hassan, Daniel E. Game

Publications

The objective of this study was to develop novel UHP-ECC materials utilizing readily available ingredients in Region 6 for the construction and repair of transportation infrastructure. Phase one of this study focused on the development of ultra-high strength cementitious matrices by evaluating the effects of ingredient selection and mixture proportioning on the materials’ compressive strength. Variables evaluated included the mass ratios of silica fume to fly ash (SF/FA), supplementary cementitious materials to cement (SCMs/C), and ordinary sand to microsilica sand (OS/MS). Phase two of the study focused on the development of UHP-ECC materials. To this end, based on the knowledge …

Deep Reinforcement Learning-Based Project Prioritization For Rapid Post-Disaster Recovery Of Transportation Infrastructure Systems, Yongcheol Lee, Kunhee Choi Ph.D, Pedram Ghannad

Publications

Among various natural hazards that threaten transportation infrastructure, flooding represents a major hazard in Region 6's states to roadways as it challenges their design, operation, efficiency, and safety. The catastrophic flooding disaster event generally leads to massive obstruction of traffic, direct damage to highway/bridge structures/pavement, and indirect damages to economic activities and regional communities that may cause loss of many lives. After disasters strike, reconstruction and maintenance of an enormous number of damaged transportation infrastructure systems require each DOT to take extremely expensive and long-term processes. In addition, planning and organizing post-disaster reconstruction and maintenance projects of transportation infrastructures are …

A Cdzntese Gamma Spectrometer Trained By Deep Convolutional Neural Network For Radioisotope Identification, Sandeep K. Chaudhuri, Joshua W. Kleppinger, Ritwik Nag, Kaushik Roy, Rojina Panta, Forest Agostinelli, Amit Sheth, Utpal N. Roy, Ralph B. James, Krishna C. Mandal

Publications

We report the implementation of a deep convolutional neural network to train a high-resolution room-temperature CdZnTeSe based gamma ray spectrometer for accurate and precise determination of gamma ray energies for radioisotope identification. The prototype learned spectrometer consists of a NI PCI 5122 fast digitizer connected to a pre-amplifier to recognize spectral features in a sequence of data. We used simulated preamplifier pulses that resemble actual data for various gamma photon energies to train a CNN on the equivalent of 90 seconds worth of data and validated it on 10 seconds worth of simulated data.

Federated Variational Learning For Anomaly Detection In Multivariate Time Series, Kai Zhang, Houbing Song, Yushan Jiang, Lee Seversky, Chengtao M. Xu, Dahai Liu

Publications

Anomaly detection has been a challenging task given high-dimensional multivariate time series data generated by networked sensors and actuators in Cyber-Physical Systems (CPS). Besides the highly nonlinear, complex, and dynamic nature of such time series, the lack of labeled data impedes data exploitation in a supervised manner and thus prevents an accurate detection of abnormal phenomenons. On the other hand, the collected data at the edge of the network is often privacy sensitive and large in quantity, which may hinder the centralized training at the main server. To tackle these issues, we propose an unsupervised time series anomaly detection framework …

Contributory Factors Of Fatigue Among Collegiate Aviation Pilots: An Ordinal Regression Analysis, Flavio A. C. Mendonca, Julius Keller, Daniel Kwasi Adjekum

Publications

Fatigue is a pervasive safety hazard in aviation affecting several aspects of a pilot's’ ability to safely perform their jobs. Several factors can contribute to fatigue, including inadequate sleep, stress, long work hours, excessive workload, and inadequate nutritional habits. In addition to flight training, some factors including academic, social, part-time work, and emerging time management skills are unique for Title 14 Code of Federal Regulations (CFR) Part 141 collegiate aviation pilots. By utilizing the Collegiate Aviation Fatigue Inventory (CAFI-II) at eight flight programs (n = 422), the current study examined factors such as fatigue training received, time spent working/studying and …

Learning To Detect: A Data-Driven Approach For Network Intrusion Detection, Zachary Tauscher, Yushan Jiang, Kai Zhang, Jian Wang, Houbing Song

Publications

With massive data being generated daily and the ever-increasing interconnectivity of the world’s Internet infrastructures, a machine learning based intrusion detection system (IDS) has become a vital component to protect our economic and national security. In this paper, we perform a comprehensive study on NSL-KDD, a network traffic dataset, by visualizing patterns and employing different learning-based models to detect cyber attacks. Unlike previous shallow learning and deep learning models that use the single learning model approach for intrusion detection, we adopt a hierarchy strategy, in which the intrusion and normal behavior are classified firstly, and then the specific types of …

A Ranking Method To Prioritize Vfr Airports To Be Provided Instrument Approach Procedures, Marcelo Soares Leão, Fábio Rodrigues Paukoski Fernandes, Gustavo Ortegal Leal, Leila Halawi

Publications

The primary purpose of this work is to investigate the necessity of a more comprehensive and systematic method to prioritize airports to be provided with instrument approaches and landing procedures in the Brazilian air transportation landscape. First, an overview of the main contributors to risks associated with the approach and landing phases is provided, covering the most critical aspects of unstable approaches and controlled flight into terrain (CFIT) events. Second, considering the emergence of Terrain Awareness and Alerting Systems (TAWS), the role of its contribution to safety is discussed and the certification context related to the design, installation, and operation …

Residential Water Meters As Edge Computing Nodes: Disaggregating End Uses And Creating Actionable Information At The Edge, Nour A. Attallah, Jeffery S. Horsburgh, Arle S. Beckwith Jr., Robb J. Tracey

Publications

We present a new, open source, computationally capable datalogger for collecting and analyzing high temporal resolution residential water use data. Using this device, execution of water end use disaggregation algorithms or other data analytics can be performed directly on existing, analog residential water meters without disrupting their operation, effectively transforming existing water meters into smart, edge computing devices. Computation of water use summaries and classified water end use events directly on the meter minimizes data transmission requirements, reduces requirements for centralized data storage and processing, and reduces latency between data collection and generation of decision-relevant information. The datalogger couples an …