Engineering Commons^™

Framework Of Internal Damage Identification In Inhomogeneous Medium Interweaving Wave Scattering Model And Deep Learning, Suyun Ham, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David

Publications

The primary objective of this project is to investigate the framework of internal damage identification in inhomogeneous media (IHM) using deep learning techniques and wave scattering. The study focuses on two main steps: 1) analyzing the wave response pattern in homogeneous media (HM) and 2) characterizing the wave response variation (WRV) in IHM with different aggregate sizes and random distributions. The WRV patterns are then classified and used to predict internal damage using a convolutional neural network (CNN). The accuracy of the finite element (FE) model is verified using laboratory tests with artificial internal crack models of varying depths. The …

Identifying Wrong-Way Driving Entry Points On Interstate Highways Using Land-Use Impact Assessment And 911 Calls, Farman Mia, Samer Dessouky

Publications

The research aims to provide insight into the initiation event of Wrong-way Driving (WWD) on highways. The intense severity of a WWD accident is encouraging the authorities to install mitigation systems that will ensure safety for motorists on highways. The WWD events are mostly resulting of intoxicated driving, where the unconscious driver takes the wrong way to enter the highway and place other motorists into life-threatening danger. This research attempted to explore from basic knowledge of WWD occurrence to examine the origin and driving philosophy of intoxicated drivers from land-use impact and mathematical modeling point of views. To identify the …

Automated Vehicle Impacts On Underserved Populations, Kate Kyung Hyun, Stephen Mattingly, Katie Kam

Publications

This research report describes the scenario framework created to determine the potential role automated vehicles (AVs) have in benefiting and adversely impacting the following underserved populations: people with disabilities and impairments (visually, hearing, physically, intellectually) and with autism spectrum disorder, younger and older populations, immigrants, low income, indigenous, rural, female and LGBTQ+, vulnerable road users (cyclists, pedestrians, low speed riders and drivers), and minority races. After presenting a literature review, three chapters explain the 3 modules of the framework: (1) scenario construction, (2) scenario factors, and (3) GIS methodology for evaluating community level AV impacts. Module 1 describes the use …

Monotonic And Cyclic Behavior Of High Strength Reinforcing Steel (Hsrs) After High Temperature Exposure, Himan Hojat Jalali, Moein Ebrahimi, Khaled Abuhishmeh, Mohammadamin Soltanianfard

Publications

Conventional reinforced concrete transportation structures in North America often use Grade 40 ksi-60 ksi reinforcing steel. The introduction of high strength reinforcing steel (HSRS) with higher yield strength in the reinforced concrete industry has led to many economic and workability advantages such as construction time saving, reduced labor cost and steel consumption which in turn alleviates congestion of reinforcement, savings in transportation and deliveries that finally results in lower carbon emission. Despite these benefits, many states, including those in Region 6, have not widely adopted the use of higher strength reinforcing steels in practice due to lack of knowledge and …

Green Mobility In Texas: Comparative Environmental Impacts And Lifecycle Cost Analysis Of Hybrid, Electric, And Hydrogen Fuel Cell Cars, Raghava R. Kommalapati, Hongbo Du, Md Jobair Bin Alam

Publications

Compared to gasoline/diesel cars and battery electric cars (BECs), hydrogen fuel cell cars (HFCCs) are relatively new. Two main advantages of HFCCs over electric vehicles are no special requirements for heavy batteries and long charging time. There is no HFCC in Texas; thus, exploring the use of electricity or hydrogen produced from renewable energies for personal cars and mitigating vehicle emissions is critical for sustaining a long-term decarburization strategy for megacities like Houston and Dallas. This project addressed this critical gap and developed environmental impacts and cost assessments for hybrid gasoline cars, BECs, and HFCCs in Texas under several possible …

Smart3pm: Smart Pavement Monitoring, Management, And Maintenance, Damien Stephens, Mena Souliman, Mukul Shirvaikar, Samer Dessouky

Publications

An application specific multi-platform smartphone application can utilize on-board accelerometer, gyroscope, and GPS sensors, along with software derived signals from the same sensors, to sample vibrational and geolocation datasets to capture pavement distresses such as potholes when mounted in a standardized configuration in a vehicle. Several observations were made with regard to the signals obtained from the accelerometer, gyroscope, and GPS sensors, and it was determined that the raw sensor outputs are capable of sampling statistically significant datasets which can be used to distinguish pavement distress from normal driving conditions. Furthermore, an approximate sensor noise margin is established, and a …

Design Of 3d Printable Eco-Concrete By Utilizing Rheology Modifiers For Sustainable Infrastructure, Maryam Hojati, Muhammad Saeed Zafar

Publications

In recent years, 3D printing technology has gained significant momentum across various industries within the construction sector, 3D printing has emerged as a promising technique; however, there are challenges associated with designing suitable construction materials and adjusting their properties for the 3D printing process. One of the key considerations in this regard is the rheological properties, encompassing parameters such as viscosity, yield stress, and thixotropy. These properties play a pivotal role in shaping the characteristics of 3D-printed concrete, both in its fresh and hardened states, including buildability, extrudability, and mechanical performance. Researchers have traditionally relied on chemical admixtures, such as …

Development Of A Web Application For Traffic Accident Mapping And Analysis, Susan Bogus Halter, Su Zhang, Arian Golrokh Amin

Publications

It is widely accepted that road traffic safety is a significant public health issue. One of the effective ways to improve road traffic safety is analyzing crash data to understand where traffic accidents occur, identify associated spatial and temporal patterns, and determine causation. In the State of New Mexico, locations of traffic accidents are currently visualized using a variety of static maps. Although these statics maps are easier to create and producers can control how users view the data, users cannot customize these maps to meet their special needs. That being said, new maps need to be created for any …

Motorcycle Crash Analysis, Hatim Sharif, Samer Dessouky

Publications

The Fatality Analysis Reporting System database shows that, in stark contrast to the 34 percent decline in non-motorcyclist crash–related fatalities, motorcyclist crash–related fatalities were up 86 percent with only three year-to-year declines since 1997, while non-motorcyclist crash–related fatalities had 13 year-to-year declines since 1997. At the national level, the rate of motorcyclist fatalities per vehicle mile traveled is 29 times higher than the rate among passenger car occupants, with overall injury rates approximately five times higher among motorcyclists than passenger car occupants. Given the frequency of motorcycle crashes and their staggering toll in terms of loss of life and economic …

Bridge Inspection Training And Enhanced Operations Using Augmented Reality, Fernando Moreu, Ali Mohammadkhorasani, Kaveh Malek

Publications

This research project focused on the innovative application of Augmented Reality (AR) headsets to enhance bridge inspection processes and inspection training. The study encompassed the visualization of 3D point cloud data, utilized the Eye-Tracking features of AR headsets for inspection quantification, evaluate the applicability of AR in the bridge inspection training and instruction of an AR virtual menu for the in-field bridge inspection. The primary tasks included establishing a database connection for AR headset, designing an AR menu tailored for bridge inspection, devising an evaluation method based on Eye-Tracking capabilities, and integrating AR into bridge inspection training. Once the technical …

Deep Reinforcement Learning-Based Digital Twin For Risk Improved Decision Making In Transportation Construction, Yong-Cheol Lee, Anisha Deria

Publications

Organizing and overseeing a large number of transportation construction and maintenance projects that generally entail several miles of a worksite are a critical burden for each DOT. In addition, it requires manual monitoring of a project or construction managers to identify a progress status, a work activity, and a safety issue in a job site. Because of the projected huge volume, complexity, significant impacts of future transportation infrastructure projects, it is evident that we are now facing a critical need to create a means of improving the results of work zone management and evaluating their impacts on our society. In …

The Effect Of Covid-19 Lockdown On Traffic Crashes In Texas., Hatim Sharif, Samer Dessouky

Publications

An analysis of traffic patterns during COVID-19 has identified that reduction in the miles traveled has a significant negative correlation with COVID-19 cases and deaths across the USA. Preliminary statistics in the US suggest an increase in fatal crashes over the period of the lockdown in comparison to the same period in previous years. Moreover, while total crashes are down, motor vehicle crashes involving non-motorists became more prevalent. At the same time, non-motorist traffic has increased while motor vehicle traffic and crashes have shifted to the local systems. The main goal of this research is to perform a comprehensive evaluation …

Calcined Clays As Alternative Supplementary Cementitious Material And Precursor For Geopolymer Binders In Transportation Infrastructure, Hassan Noorvand, Miladin Radovic, Marwa Hassan, Adriana A. Alvarado, Oscar Huang

Publications

This project aimed to assess the feasibility of using locally sourced calcined kaolinitic clays both as supplementary cementitious materials (SCMs) and as precursors for synthesizing geopolymers (GPs). For SCMs, a comprehensive set of characterizations was conducted, including X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), particle size analysis, and loss on ignition (LOI), along with evaluations of concrete properties such as strength activity index (SAI), slump, air content, compressive strength, and surface resistivity. For GPs, compressive strength was tested. The study yielded several key findings: (1) Three types of calcined clays (CCs) were analyzed based …

Prediction Of Moisture Resistance Of Polymeric Asphalt Binders Through The Atomic Force Microscopy (Afm) Technique, Zahid Hossain, Ashraf Elsayed, Khaja Sameer Sadat

Publications

Moisture damage is a significant concern for state Departments of Transportation (DOTs) and other agencies due to its adverse impact on pavement performance as well as longevity. The main focus of the current study project is to quantify, at the molecular level, the interaction between binder and aggregate at the interface level in the form of adhesion forces between bitumen samples and minerals of various chemical compositions. First of all, A thorough review of the literature on moisture degradation in asphalts was conducted. Based on the literature review, a comprehensive project plan and test matrix were created. Binder samples from …

Early-Age Strength Monitoring Of Sensor-Embedded 3d Printed Structures, Ali Kazemian, Marwa Hassan, Hassan Noorvand, Gabriel Arce, Kasra Banijamali

Publications

Construction 3D printing (C3DP) is an automated technology that has the potential to reduce the construction time and cost by utilizing different types of robotic systems. Due to the absence of formwork in C3DP, potential excessive water evaporation can cause issues to the freshly-printed structures that are exposed to the ambient curing condition. Moreover, the 3D printed elements should carry the service loads in a short time after printing to provide a load-bearing capacity. Destructive and non-destructive methods are the two types of methods that are being used in the construction industry for quality monitoring. Due to the time-consuming nature …

Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy

Publications

The rapid progression of Artificial Intelligence (AI) systems, facilitated by the advent of Large Language Models (LLMs), has resulted in their widespread application to provide human assistance across diverse industries. This trend has sparked significant discourse centered around the ever-increasing need for LLM-based AI systems to function among humans as part of human society, sharing human values, especially as these systems are deployed in high-stakes settings (e.g., healthcare, autonomous driving, etc.). Towards this end, neurosymbolic AI systems are attractive due to their potential to enable easy-tounderstand and interpretable interfaces for facilitating valuebased decision-making, by leveraging explicit representations of shared values. …

Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth

Publications

Despite their wide applications to language understanding tasks, large language models (LLMs) still face challenges such as hallucinations - the occasional fabrication of information, and alignment issues - the lack of associations with human-curated world models (e.g., intuitive physics or common-sense knowledge). Additionally, the black-box nature of LLMs makes it highly challenging to train them meaningfully in order to achieve a desired behavior. Specifically, the attempt to adjust LLMs’ concept embedding spaces can be highly intractable, which involves analyzing the implicit impact on LLMs’ numerous parameters and the resulting inductive biases. This paper proposes a novel architecture that wraps powerful …

Towards Pragmatic Temporal Alignment In Stateful Generative Ai Systems: A Configurable Approach, Kaushik Roy, Yuxn Zi, Amit Sheth

Publications

Temporal alignment in stateful generative artificial intelligence (AI) systems remains an underexplored area, particularly beyond goal-driven approaches in planning. Stateful refers to maintaining a persistent memory or “state” across runs or sessions. This helps with referencing past information to make system outputs more contextual and relevant. This position paper proposes a framework for temporal alignment with several configurable toggles. We present four alignment mechanisms: knowledge graph path-based, neural score-based, vector similarity-based, and sequential process-guided alignment. By offering these interchangeable approaches, we aim to provide a flexible solution adaptable to complex and real-world applications. This paper discusses the potential benefits and …

Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance In The Age Of Large Language Models, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Allen, Amit P. Sheth

Publications

Current Virtual Mental Health Assistants (VMHAs) primarily offer counseling and suggestive care but do not assist with patient diagnosis due to their lack of training in safety-constrained and specialized clinical process knowledge, referred to as ProKnow. In this work, we define ProKnow as an ordered set of information aligned with evidence-based guidelines or categories of conceptual understanding used by domain experts. We also introduce a new dataset of diagnostic conversations guided by safety constraints and Pro- Know, known as ProKnow-data. We develop a method for natural language question generation (NLG) designed to interactively gather diagnostic information from patients, termed ProKnow-algo. …

Causal Event Graph-Guided Language-Based Spatiotemporal Question Answering, Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit Sheth

Publications

Large Language Models have excelled at encoding and leveraging language patterns in large text-based corpora for various tasks, including spatiotemporal event-based question answering (QA). However, due to encoding a text-based projection of the world, they have also been shown to lack a fullbodied understanding of such events, e.g., a sense of intuitive physics, and cause-and-effect relationships among events. In this work, we propose using causal event graphs (CEGs) to enhance language understanding of spatiotemporal events in language models, using a novel approach that also provides proofs for the model’s capture of the CEGs. A CEG consists of events denoted by …

Dynamics Of A 3-D Inlet/Isolator Measured With Fast Pressure-Sensitive Paint, Andrew N. Bustard, Mark E. Noftz, Mitsugu Hasegawa, Hirotaka Sakaue, Joseph S. Jewell, Nicholas J. Bisek, Thomas J. Juliano

Publications

Fast pressure-sensitive paint (PSP) was applied to an inlet/isolator designed using the Osculating Internal Waverider Inlet with Parallel Streamlines (OIWPS) method. The dorsal isolator surface pressure was measured using anodized-aluminum PSP through transparent cast acrylic that makes up the ventral portion of the isolator. Temperature-sensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at Re = 8.5 ×106 /m and 10.2 ×106 /m in the AFOSR–Notre Dame Large Mach-6 Quiet Tunnel (ANDLM6QT) under conventional noise conditions. Flow phenomena, such as shocks originating in the inlet and flow separation at the …

Fundamentals Of Sustainability, Eva Maleviti

Publications

Fundamentals of Sustainable Aviation is the frst textbook to survey the critical feld of sustainability within the aviation industry. Taking a systems thinking approach, it presents the foundational principles of sustainability and methodically applies them to diferent aviation sectors. Opening with the basics of sustainability, emphasising the Sustainable Development Goals, the book then considers the environmental, economic and social dimensions of aviation. The following chapters apply these insights to aviation design, supply chains, operations, maintenance and facilities. The fnal chapter examines the concept of resilience in sustainable aviation. Overall, the textbook shows how future sustainability can be achieved by making …

Short-Term Forecasting Airport Passenger Flow During Periods Of Volatility: Comparative Investigation Of Time Series Vs. Neural Network Models, David H. Hopfe, Kiljae Lee, Chunyan Yu

Publications

Recurrent Neural Networks (RNNs), known for handling complex data tasks like language translation and speech recognition, are seldom employed in airport management practice for daily and weekly passenger flow forecasting tasks. In this paper, we evaluate the effectiveness and adaptability of various neural network models (RNN, LSTM, GRU, Deep LSTM, Bidirectional LSTM, multivariate RNN, and multivariate LSTM) against standard time series models (ARIMA, SARIMA, and SARIMAX) for a short-term forecasting airport security checkpoint passenger flows at five major U.S. airports during the pandemic.

At Atlanta's Hartsfield-Jackson Airport (ATL), the RNN notably surpasses SARIMA's forecasting accuracy by 34% (DM= 3.44, p …

Barriers To The Adoption Of Digitalization In The Construction Industry: Perspectives Of Owners, Contractors, And Contractors, Waleed Abu-Khader

Publications

Construction organizations are moving toward adopting digitalization in response to Industry 4.0. However, the slow adoption of digitalization has been observed. This study aimed to assess the level of digitalization adoption and evaluate the barriers to adopting digitalization in the Jordanian construction industry by all project parties in the public and private sectors. The study targets were achieved through a structured questionnaire using SPSS software for analysis through the following statistical tests: Normality test, Mann-Whitney U, Kruskal-Wallis H, and Exploratory Factor Analysis (EFA). Most respondents used software at the design stage, and less than half did not use any software …

Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi

Publications

Weather is responsible for approximately 70% of air transportation delays in the National Airspace System, and delays resulting from convective weather alone cost airlines and passengers millions of dollars each year due to delays that could be avoided. This research sought to establish relationships between environmental variables and airport efficiency estimates by data mining archived weather and airport performance data at ten geographically and climatologically different airports. Several meaningful relationships were discovered from six out of ten airports using various machine learning methods within an overarching data mining protocol, and the developed models were tested using historical data.

An Ontology Design Pattern For Representing Causality, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

The causal pattern is a proposed ontology design pattern for representing the structure of causal relations in a knowledge graph. This pattern is grounded in the concepts defined and used by the CausalAI community i.e., Causal Bayesian Networks and do-calculus. Specifically, the pattern models three primary concepts: (1) causal relations, (2) causal event roles, and (3) causal effect weights. Two use cases involving a sprinkler system and asthma patients are provided along with their relevant competency questions.

Flying To Net Zero With Sustainable Atos; Changing Cultures​, Eva Maleviti

Publications

What is Sustainability?

• World Commission on Environment and Development’s (WCED) 1987 Brundtland Report ‘’Our Common Future’’.
• Help world nations towards sustainable development.

17 Sustainable Development Goals

• The start of all industries are the 17 SDGs
• Aviation can address the 15 SDGs
• Net zero target suggest reduction of aviation emissions up to 21.2 Gt CO2

Deficient Aeronautical Decision-Making Contributions To Fatal General Aviation Accidents, Douglas D. Boyd, Mark Scharf Phd

Publications

INTRODUCTION: General aviation (GA), mainly comprised of light (≤12,500 lb) aircraft, maintains an inferior safety record compared with air carriers. To improve safety, aeronautical decision-making (ADM) practices have been advocated to GA pilots since 1991. Herein, we determined the extent to which GA pilots disregard such practices. METHODS: Fatal accidents (1991–2019) involving private pilots (PPLs) in single-engine airplanes were identified (N = 1481) from the National Transportation Safety Board AccessR database. Of these, deficient go/no-go and in-flight ADM-related mishaps were scored using the PAVE (pilot, aircraft, environment, external pressure)/IMSAFE (illness, medicine, stress, alcohol, fatigue, eating) and PPP (perceive, process, …

Strategies For Engagement Of Non-Traditional Students In Engineering-Related Courses, Kimberly T. Luthi Dr., David Harvie, Keith Wilson, Monica Surrency

Publications

Project Goals

Overview

• Goal #1: Increase students' commitment to engineering pathways.
• Goal #2: Increase academic performance and persistence in engineering.
• Goal #3: Increase persistence of Veterans in engineering pathways.

Research Questions

• How does students' participation in peer-led team learning activities in online engineering courses correlate to their a) commitment to engineering, b) engineering identity, and c) self-efficacy.
• How do students in peer-led team learning activities compare to students in non-PLTL groups in terms of a) academic performance and b) persistence in engineering pathways?

Experimental Evaluation Of Airflow Guiding Components For Wind-Driven Single-Sided Natural Ventilation: A Comparative Study In A Test Chamber, Nima Najafi Ziarani, Malcolm J. Cook, Paul D. O’Sullivan

Publications

Single-sided ventilation is a frequently employed ventilation strategy in contemporary structures, yet its effectiveness is often mediocre, underscoring the need for solutions to enhance its performance. To evaluate the effect of louvres and guide vanes on the effective ventilation rate, 21 different louvre configurations and four guide vane designs were compared with a plain opening for single-sided ventilation in a full-scale experimental test chamber under three different magnitudes of local wind velocity. Ventilation rates were measured using the tracer gas decay method with 12 NDIR CO2 sensors. The findings, obtained under specific test conditions, indicate that deeper openings result in …