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Articles 1 - 30 of 37
Full-Text Articles in Management and Operations
Bitseat: Reimagining The Financing For Airliners Using Nonfungible Tokens (Blockchain Technology), Edwin S. Ongola
Bitseat: Reimagining The Financing For Airliners Using Nonfungible Tokens (Blockchain Technology), Edwin S. Ongola
Journal of Aviation Technology and Engineering
This essay describes how blockchain technology, particularly nonfungible tokens, can be used to raise funding for airliners. The essay begins with a brief overview on the costs, categories, and acquisition methods of airliners. After that, the essay introduces concepts on blockchain technology, tokens, and smart contracts. The essay then touches on how nonfungible tokens can be used to facilitate fractional ownership of airliners. From there, the essay discusses Bitseat, a conceptual nonfungible token for fractional ownership of airliners, covering its overall design, appeal, marketplace alternatives, and challenges. Finally, in the discussion, the essay summarizes the overall concept and outlines its …
Ai-Driven Scheduling Algorithms For Private Aviation, Tayan Benson, Jessica Buskey, Gabriel Camacho, Caitlyn A. Gabrinowitz
Ai-Driven Scheduling Algorithms For Private Aviation, Tayan Benson, Jessica Buskey, Gabriel Camacho, Caitlyn A. Gabrinowitz
Discovery Day - Daytona Beach
Private aviation scheduling is complex and dynamic, requiring frequent aircraft repositioning based on demand and operational constraints, unlike fixed commercial airline schedules. As fleets grow beyond 300 aircraft, traditional deterministic methods become too slow, leading to the use of approaches such as genetic algorithms, but neural network-based methods have not seen in-depth exploration. This project models aircraft scheduling as a network, where airports and flights form a graph. It explores advanced AI methods, including graph neural networks and spatio-temporal graph neural networks (STGNNs), to capture both network structure and time constraints. The goal is to generate efficient daily schedules from …
Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen
Predicting Passenger Demand On National Flights Departing From Hartsfield-Jackson Atlanta International Airport (Atl) In 2024, Brooklyn Gossett, Ana Yu Wen
Discovery Day - Daytona Beach
The aviation industry relies heavily on accurate demand forecasting to guide critical decisions regarding route planning, capacity management, and pricing strategy. Misjudging passenger demand can result in significant revenue loss and operational inefficiency, making it essential for airlines and analysts to identify the key drivers of flight patronage. This study investigates the factors that most significantly predict the number of passengers on domestic flights departing from Hartsfield-Jackson Atlanta International Airport (ATL) during the 2024 calendar year. Using passenger and route data sourced from the Bureau of Transportation Statistics (BTS) and the U.S. Department of Transportation (DOT), a multiple regression analysis …
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Publications
As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …
Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng
Statistical Analysis Of Log Transformation Effectiveness In Air Traffic Movement Forecasting During Covid-19 In South Africa, John Lehlaka Masekoameng
Journal of Aviation Technology and Engineering
This study evaluates the effectiveness of log transformation in enhancing multiple regression models used to forecast air traffic movements (ATMs) in South Africa during the COVID-19 pandemic. Using 60 monthly observations from October 2016 to September 2021, the analysis incorporates variables such as revenue, lockdown levels, COVID-19 metrics, exchange rates, gross domestic product, and population. Two models are compared: one using raw ATMs and another with log-transformed ATMs as the dependent variable.
While the untransformed model shows stronger explanatory power (R² = 0.904, adjusted R² = 0.891) compared to the log-transformed model (R² = 0.772, adjusted R² = 0.741), the …
Network-Aware Airline-Specific Flight Delay Prediction Using Tree-Based Ensemble Models, Mary Dufie Afrane
Network-Aware Airline-Specific Flight Delay Prediction Using Tree-Based Ensemble Models, Mary Dufie Afrane
College of Graduate Studies: Theses & Dissertations
Flight delays pose persistent challenges to the efficiency and reliability of air transportation systems, affecting airlines, airports, regulators, and passengers alike. As traffic demand grows and operational environments become increasingly interconnected, accurately predicting both departure and arrival delays has become crucial for effective planning and mitigation. This study presents a network-aware, airline-specific framework for predicting flight delays in U.S. domestic air transportation systems using tree-based ensemble machine learning models. A large-scale dataset of 1.98 million flights, enriched with weather information, is used to develop predictive models for both departure and arrival delays. To capture the structural and operational complexity of …
A Technical And Statistical Analysis Of Unleaded Aviation Fuel (Ul94) Adoption In A High- Volume Collegiate Aviation Environment, Nicholas D. Wilson, Ryan Guthridge, Brandon Wild, Jeremy Roesler, Daniel Kasowski, Nick Geinert, Aaron Terbest, Aaron Fettig, Robert Kraus
A Technical And Statistical Analysis Of Unleaded Aviation Fuel (Ul94) Adoption In A High- Volume Collegiate Aviation Environment, Nicholas D. Wilson, Ryan Guthridge, Brandon Wild, Jeremy Roesler, Daniel Kasowski, Nick Geinert, Aaron Terbest, Aaron Fettig, Robert Kraus
Journal of Aviation Technology and Engineering
The University of North Dakota (UND) adopted unleaded aviation fuel (UL94) for approximately a four-month period in the summer and early fall of 2023. The UL94 fuel was used in all reciprocating engine fleets based at the university’s primary training airport, Grand Forks International Airport in North Dakota. During the operational implementation of UL94, the UND flew 46,600 flight hours, consuming 386,778 gallons of fuel across all fleets powered by Lycoming engines. After approximately two months of using UL94, operational reports and maintenance inspections began to indicate potential for exhaust valve seat recession (EVSR), although early indications were limited in …
Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley
Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley
Publications
Risk assessment in aviation is a critical process that safeguards the safety and reliability of operations. Aviation operations encompass inherent risks, from mechanical failures to human errors and environmental factors. The significance of these risks may be severe, leading to accidents, injuries, and loss of life. Recognizing and mitigating risks is supreme in this dynamic environment, where emerging technologies and innovation constantly reshape this industry. This chapter includes an in-depth explanation of risk management and analysis, leading to the core elements of risk assessment specifically for aviation operations. We will describe the process and explore some of the applications and …
Analysis Of Public Acceptance Of Urban Air Mobility (Uam) Based On Air Travel Frequency, Seuggyun Jin, Kim O. Chambers
Analysis Of Public Acceptance Of Urban Air Mobility (Uam) Based On Air Travel Frequency, Seuggyun Jin, Kim O. Chambers
Journal of Aviation/Aerospace Education & Research
Urban Air Mobility (UAM) is an innovative air transportation system designed for efficient travel in urban and suburban areas, offering significant time saving compared to traditional ground transportation. However, concerns about UAM services, such as safety and noise, remain prominent. Understanding public acceptance of UAM is crucial to identifying potential customers and ensuring the sustainability of commercial UAM operations. This study utilizes an online survey from a total of 254 consumer attitudes on the scales of reliability, usefulness, behavioral intention, safety, and concerns to examine public acceptance of UAM based on people's air travel frequencies. Using a one-way ANOVA, the …
Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola
Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola
Journal of Aviation Technology and Engineering
This article provides a perspective on how an internet of heterogeneous self-service airport terminal systems can be used for data collection, which is stored on a private or consortium blockchain depending on the ownership or operations of an airport or both. Such a setup would help to increase efficiency, reduce costs, and improve traveler experience at airport terminals. Moreover, it would allow airports to gather data directly from passengers as opposed to waiting to receive the same data from airlines. Subsequently, this data, now on a blockchain system, becomes a data source for other applications such as machine learning. In …
Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen
Representation Learning For Generative Models With Applications To Healthcare, Astronautics, And Aviation, Van Minh Nguyen
Theses and Dissertations
This dissertation explores applications of representation learning and generative models to challenges in healthcare, astronautics, and aviation.
The first part investigates the use of Generative Adversarial Networks (GANs) to synthesize realistic electronic health record (EHR) data. An initial attempt at training a GAN on the MIMIC-IV dataset encountered stability and convergence issues, motivating a deeper study of 1-Lipschitz regularization techniques for Auxiliary Classifier GANs (AC-GANs). An extensive ablation study on the CIFAR-10 dataset found that Spectral Normalization is key for AC-GAN stability and performance, while Weight Clipping fails to converge without Spectral Normalization. Analysis of the training dynamics provided further …
Examining The Effect Of Contractor Logistics Support On The Reliability Of Military Aircraft, Rodrigo S. Campos De Moura
Examining The Effect Of Contractor Logistics Support On The Reliability Of Military Aircraft, Rodrigo S. Campos De Moura
Theses and Dissertations
This study utilizes survival analysis for examining the effect of Contractor Logistics Support (CLS) on the reliability of military aircraft before and after implementing CLS. The provider of CLS in this study is the original equipment manufacturer that designed and produced the target aircraft of this study, the Embraer A-29 Super Tucano.
Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu, Joseph P. Hupy, Chien-Tsung Lu, Zhenglei Ji
Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu, Joseph P. Hupy, Chien-Tsung Lu, Zhenglei Ji
Journal of Aviation/Aerospace Education & Research
The National Airspace System (NAS) is a sophisticated network of air traffic control, navigation, and communication systems that play a critical role in ensuring the safe and efficient flow of air traffic across the United States. However, the occurrence of severe weather conditions, particularly hailstorms, poses a significant threat to flight safety within the NAS. To mitigate the risks associated with hail, aviation organizations have implemented a range of safety measures. This study utilized Esri’s ArcGIS as a mapping software to conduct a geospatial analysis of the impact of severe weather, particularly hail, on the NAS. The Hail Awareness Spatial …
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman
College of Graduate Studies: Theses & Dissertations
Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …
Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi
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.
Integrating External Sensors With Crazyflie Drones, Xiaowen Wang, Dheryta Jaisinghani, Andrew Berns
Integrating External Sensors With Crazyflie Drones, Xiaowen Wang, Dheryta Jaisinghani, Andrew Berns
Summer Undergraduate Research Program (SURP) Symposium
- Drones are widely used: Mini drones such as Crazyflie 2.1 are used in a variety of fields.
- Grove Sound Sensor function: Grove Sound Sensor can capture sound, providing more application possibilities for drones.
- The potential of Crazyflie 2.1: Although Crazyflie 2.1 has the potential to be an integrated sensor platform, prior to this project, it was uncertain whether sensors could be connected on it.
- Project motivation: Our project aims to explore whether Crazyflie 2.1 can be connected to the Grove Sound Sensor and collect and process data from the sensor.
- Impact of the project: If successful, this project will open …
Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins
Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins
Faculty Publications
Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …
Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal
Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal
International Journal of Aviation, Aeronautics, and Aerospace
Since there is an uncertainty in the arrival times of flights, pre-scheduled allocation of runways and stands and the subsequent first-come-first-served treatment results in a sub-optimal allocation of runways and stands, this is the prime reason for the unusual delays in taxi-in times at IGIA, New Delhi.
We simulated the arrival pattern of aircraft and utilized stochastic optimization to arrive at the best runway-stands allocation for a day. Optimization is done using a GRG Non-Linear algorithm in the Frontline Systems Analytic Solver platform. We applied this model to eight representative scenarios of two different days. Our results show that without …
A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas
A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas
Journal of Aviation/Aerospace Education & Research
This paper proposes a classification approach for flight delays using Bidirectional Long Short-Term Memory (BiLSTM) and Long Short-Term Memory (LSTM) models. Flight delays are a major issue in the airline industry, causing inconvenience to passengers and financial losses to airlines. The BiLSTM and LSTM models, powerful deep learning techniques, have shown promising results in a classification task. In this study, we collected a dataset from the United States (US) Bureau of Transportation Statistics (BTS) of flight on-time performance information and used it to train and test the BiLSTM and LSTM models. We set three criteria for selecting highly important features …
Directional Speaker Poster, Eugene Ng, Bryan Wong, Ruhaan Das
Directional Speaker Poster, Eugene Ng, Bryan Wong, Ruhaan Das
Student Works
Changi Airport is set to expand with a new terminal, Terminal 5. Currently, many of the airport's processes are manual, requiring a high dependence on staff. This proposal aims to incorporate automation and AI for a smoother passenger experience.
Scheduling Aircraft Departures To Avoid Enroute Congestion, Johannes Martinez
Scheduling Aircraft Departures To Avoid Enroute Congestion, Johannes Martinez
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
When scheduled flights are forecast to overcrowd sections of enroute airspace, an air traffic control authority may need to delay departures. Mixed integer linear programming can be used to compute a schedule that resolves the congestion while bringing the sum of all delays to a minimum. Standard linear programming constraint formulations for such scheduling problems, however, have poor run times for instances of realistic size. A new constraint formulation based on cycles and paths through a route graph reduces run times in computational experiments. It shows particularly strong performance for schedules that approach the worst-case solution times in standard formulations.
Conceptual Design Of A South Pole Carrier Pigeon Uav, Kendrick M. Dlima
Conceptual Design Of A South Pole Carrier Pigeon Uav, Kendrick M. Dlima
Master's Theses
Currently, the South Pole has a large data problem. It is estimated that 1.2 TB of data is being produced every day, but less than 500 GB of that data is being uploaded via aging satellites to researchers in other parts of the world. This requires those at the South Pole to analyze the data and carefully select the parts to send, possibly missing out on vital scientific information. The South Pole Carrier Pigeon will look to bridge this data gap.
The Carrier Pigeon will be a small unmanned aerial vehicle that will carry a 30 TB solid-state hard drive …
Assessing If Motivation Impacts General Aviation Pilots’ Persistence In Varying Weather Conditions, Sabrina Woods
Assessing If Motivation Impacts General Aviation Pilots’ Persistence In Varying Weather Conditions, Sabrina Woods
Doctoral Dissertations and Master's Theses
Continued flight under visual flight rules into instrument meteorological conditions is the predominant cause for fatal accidents by percentage, for general aviation aircraft operations. It is possible that a pilot’s motivation or reason for flying will override other safer, more logical courses of action when a hazard presents itself. The decision appears to stem from a willingness to persist in a course of action despite factors that indicate an alternate and safer course is warranted. This research addresses what is currently presumed about the decision to continue flying under visual flight rules into instrument conditions and marries those ideas with …
How Airport Construction Will Evolve With The Increased Effects Of Climate Change, Xavier M. Ashley
How Airport Construction Will Evolve With The Increased Effects Of Climate Change, Xavier M. Ashley
Beyond: Undergraduate Research Journal
This report addressed the effects rising global temperatures resulting from climate change have had on flight operations in their entirety. The research objective was to discover what methods could enhance climate adaptation in airport construction, as higher mean-surface temperatures have an increasingly negative effect on aircraft performance. The findings would primarily be of interest to the Federal Aviation Administration (FAA) Primary Office presiding over the planning and development of airports. Overall, the report provided a comprehensive analysis of global warming’s effects on aviation, including the implications of degraded aircraft performance and sea-level rise for coastal airports. Additionally, it examined comparative …
Evaluating Annual Fixed Wing Maintenance Costs, Kirsten Bunecke, Edward D. White, Jonathan D. Ritschel, Brett A. Bush
Evaluating Annual Fixed Wing Maintenance Costs, Kirsten Bunecke, Edward D. White, Jonathan D. Ritschel, Brett A. Bush
Faculty Publications
This article serves two purposes: first, to empirically model the annual percentage increase of operations and support (O&S) costs for fixed wing aircraft; and second, to place into the archival realm another reference for other researchers to consider when investigating other O&S topics. For this study of 21 different airframes grouped together at the Mission- Design Series (MDS), maintenance subcategories 3.1 Consumable Materials and Repair Parts, 3.2 Depot Level Repairables (DLR), and 3.4 Depot Maintenance accounted for an average 91.5% of annual organic maintenance costs. For contractor-maintained MDS, subcategory 3.7, Contractor Logistics Support (CLS) accounted for 96.6% of annual maintenance …
Book Review: Fundamentals Of International Aviation, Alan Bender
Book Review: Fundamentals Of International Aviation, Alan Bender
International Journal of Aviation, Aeronautics, and Aerospace
Not applicable.
Space Operations In The Suborbital Space Flight Simulator And Mission Control Center: Lessons Learned With Xcor Lynx, Pedro Llanos, Christopher Nguyen, David Williams, Kim O. Chambers, Erik Seedhouse, Robert Davidson
Space Operations In The Suborbital Space Flight Simulator And Mission Control Center: Lessons Learned With Xcor Lynx, Pedro Llanos, Christopher Nguyen, David Williams, Kim O. Chambers, Erik Seedhouse, Robert Davidson
Journal of Aviation/Aerospace Education & Research
This study was conducted to better understand the performance of the XCOR Lynx vehicle. Because the Lynx development was halted, the best knowledge of vehicle dynamics can only be found through simulator flights. X-Plane 10 was chosen for its robust applications and accurate portrayal of dynamics on a vehicle in flight. The Suborbital Space Flight Simulator (SSFS) and Mission Control Center (MCC) were brought to the Applied Aviation Sciences department in fall 2015 at Embry-Riddle Aeronautical University, Daytona Beach campus. This academic and research tool is a department asset capable of providing multiple fields of data about suborbital simulated flights. …
Visually Analyzing The Impacts Of Essential Air Service Funding Decisions, Rohan Kashuka, Chittayong Surakitbanharn, Calvin Yau, David S. Ebert
Visually Analyzing The Impacts Of Essential Air Service Funding Decisions, Rohan Kashuka, Chittayong Surakitbanharn, Calvin Yau, David S. Ebert
The Summer Undergraduate Research Fellowship (SURF) Symposium
Essential Air Service (EAS) is a U.S. government subsidy program which ensures maintenance of commercial airline services in small deregulated communities. The program’s budget currently is around $250 million annually, which is used as subsidy for airlines to maintain a minimal level of scheduled air service in relatively smaller airports. It is evident that 2% of the FAA budget is being spent to maintain air service in smaller communities, but there is not enough evidence to prove that all the current decisions made by Congress about EAS are advantageous. To understand these decisions, 15 years of data produced by the …
Forecasting The Air Race Classic: Lessons In Interdisciplinary Aviation Weather Support And Decision-Making, Shawn M. Milrad, Debbie Schaum
Forecasting The Air Race Classic: Lessons In Interdisciplinary Aviation Weather Support And Decision-Making, Shawn M. Milrad, Debbie Schaum
Journal of Aviation/Aerospace Education & Research
The Air Race Classic (ARC) is an all-female Visual Flight Rules air race held each June. Embry-Riddle Aeronautical University Daytona Beach (ERAU-DB) has had primarily student race teams participate and frequently place strongly in the ARC since 1996. The ERAU-DB Meteorology Program has provided successful weather support to ERAU-DB race team(s) for the past decade, including as the terminus host institution in 2016. In 2014, the weather support was formalized as a three-credit interdisciplinary summer course, incorporating a mix of aeronautical science (pilot), dispatch, and meteorology students. Using concepts of service and experiential learning, the ARC course has successfully integrated …
Estimation Of Performance Airspeeds For High-Bypass Turbofans Equipped Transport-Category Airplanes, Nihad E. Daidzic
Estimation Of Performance Airspeeds For High-Bypass Turbofans Equipped Transport-Category Airplanes, Nihad E. Daidzic
Journal of Aviation Technology and Engineering
Conventional Mach-independent subsonic drag polar does not replicate the real airplane drag characteristics exactly and especially not in the drag-divergence region due to shock-induced transonic wave drag. High-bypass turbofan thrust is a complicated function of many parameters that eludes accurate predictions for the entire operating envelope and must be experimentally verified. Fuel laws are also complicated functions of many parameters which make optimization and economic analysis difficult and uncertain in the conceptual design phase. Nevertheless, mathematical models and predictions have its important place in aircraft development, design, and optimization. In this work, airspeed-dependent turbofan thrust and the new fuel-law model …