Engineering Commons^™

Prioritization Of Voluntary Silence Criteria In Military Aviation For The Sustainability Or Safety Superiority, Vildan Durmaz, Cüneyt Ceyran, Ebru Yazgan

International Journal of Aviation, Aeronautics, and Aerospace

Since aviation is one of the sectors involving high levels of risk in today’s world, the presence of a safe working environment is crucial for both flight operations and aircraft maintenance services. Thus, it is vital for aviation workers to be aware of unsafe situations as well as dangers and potential risks in order to create a safe environment and establish an organizational safety culture. One of the fundamental components of such awareness is information, and voluntary reporting of this information as well as unsafe situations by aviation employees is one of the most important ways for managers to access …

Airspace Saturation And Midair Collision Risk: A Case Study At A Class D Airport, Luigi Raphael I. Dy, John H. Mott

International Journal of Aviation, Aeronautics, and Aerospace

Near midair collisions are precursor events to actual collisions and may be an indicator of risk. While previous studies have used reports of near midair collisions to relate factors such as airspace saturation to near midair collisions, the reports relied upon were generally subjective in nature. With the adoption of automatic dependent surveillance-broadcast (ADS-B), the approximate position of every equipped aircraft can be recorded. A six-month case study was performed at the Purdue University airport to relate the number of 1000-foot proximity events to airspace saturation, and whether the Class D airspace affected this relationship. Through a logistic regression analysis, …

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 …

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 …

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 …

Artificial Intelligence-Assisted Inertial Geomagnetic Passive Navigation, Andrei Cuenca

Doctoral Dissertations and Master's Theses

In recent years, the integration of machine learning techniques into navigation systems has garnered significant interest due to their potential to improve estimation accuracy and system robustness. This doctoral dissertation investigates the use of Deep Learning combined with a Rao-Blackwellized Particle Filter for enhancing geomagnetic navigation in airborne simulated missions.

A simulation framework is developed to facilitate the evaluation of the proposed navigation system. This framework includes a detailed aircraft model, a mathematical representation of the Earth's magnetic field, and the incorporation of real-world magnetic field data obtained from online databases. The setup allows an accurate assessment of the performance …

Verification And Validation Of Robot Manipulator Adaptive Control With Actuator Deficiency, Sebastian Comeaux

Doctoral Dissertations and Master's Theses

This work addresses the joint tracking problem of robotic manipulators with uncertain dynamical parameters and actuator deficiencies, in the form of an uncertain control effectiveness matrix, through adaptive control design, simulation, and experimentation. Specifically, two novel adaptive controller formulations are implemented and tested via simulation and experimentation. The proposed adaptive control formulations are designed to compensate for uncertainties in the dynamical system parameters as well as uncertainties in the control effectiveness matrix that pre-multiplies the control input. The uncertainty compensation of the dynamical parameters is achieved via the use of the desired model compensation–based adaptation, while the uncertainties related to …

Deep-Learning Based Multiple-Model Bayesian Architecture For Spacecraft Fault Estimation, Rocio Jado Puente

Doctoral Dissertations and Master's Theses

This thesis presents recent findings regarding the performance of an intelligent architecture designed for spacecraft fault estimation. The approach incorporates a collection of systematically organized autoencoders within a Bayesian framework, enabling early detection and classification of various spacecraft faults such as reaction-wheel damage, sensor faults, and power system degradation.

To assess the effectiveness of this architecture, a range of performance metrics is employed. Through extensive numerical simulations and in-lab experimental testing utilizing a dedicated spacecraft testbed, the capabilities and accuracy of the proposed intelligent architecture are analyzed. These evaluations provide valuable insights into the architecture's ability to detect and classify …

Stochastic Point Process Modeling For Engineering Applications, Samarth Motagi

Doctoral Dissertations and Master's Theses

Hawkes model or self-exciting point process model is a branching point process model. The model classifies the dataset of discrete events to background and offspring events. It has been used to study interconnected events in many fields, but relatively little work exists in applying these concepts to engineering problems. In our research, we use a self-exciting point process model for two engineering applications: (a) To identify secondary crashes from a given traffic data and (b) To quantify the agglomeration state and size of nanoparticles from computationally generated carbon nanotube microstructure using stochastic percolation model and experimentally generated titanium nanoparticle microstructures. …

Comparison Of Methods For Estimating Instantaneous Turn Radius Of Ackermann Steering Vehicles, Kenneth Gennaro Stutts

Doctoral Dissertations and Master's Theses

The instantaneous turn radius of an Ackermann steering vehicle is the distance to a point in space about which the vehicle will travel in an arc during a turn. There are at least six ways to estimate instantaneous turn radius and each method uses different inputs and has distinct advantages and disadvantages. In this thesis, six different methods will be used to estimate the instantaneous turn radius of a vehicle traveling on a closed circuit. This testing will clarify similarities and differences between the methods. This thesis clarifies which method will be the most appropriate for a given set of …

Comparative Evaluation Of Propulsive Power Transmission Technologies For High-Speed Vertical Takeoff And Landing (Hsvtol) Cargo Aircraft, Xinyu Yang

Doctoral Dissertations and Master's Theses

Designing High-Speed Vertical Takeoff and Landing (HSVTOL) cargo aircraft capable of both low downwash velocity hovering and high subsonic speed cruising presents a significant engineering challenge. This challenge, stemming from conflicting design requirements, has been substantially influenced by recent technological advancements, which have offered greater flexibility in rotor placement. Consequently, this has led to the emergence of innovative mission-specific designs that hold the potential to outperform traditional concepts. The central objective of this study is to evaluate the benefits of modern technologies for VTOL cargo aircraft and assess their performance relative to baseline VTOL aircraft. The results of this comparative …

Development Of A Constellation Simulator For A 5g/Iot Mission Planning System, Franco Criscola

Doctoral Dissertations and Master's Theses

The advancement of 5G and Internet-of-Things technologies has presented new challenges for telecommunications providers. One of the challenges is integrating these technologies with present networks. A solution has been found in low-Earth orbit satellite constellations. On one hand, this method increases coverage and reduces costs, but on the other it raises new problems like how to efficiently manage large constellations of spacecraft. This thesis introduces the Constellation Management System, developed in collaboration with i2Cat foundation. This novel tool is composed of two modules: the simulator and the scheduler. The former propagates satellite motion and computes visibility events to various targets …

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.

Understanding Collective Performance: Human Factors And Team Science, Joseph Keebler

Math Department Colloquium Series

This talk will focus on modern issues with team science. Joe will discuss a variety of projects he's been involved with aimed at improving teamwork in complex sociotechnical systems including military, aviation, and healthcare. He will discuss major theoretical facets of teamwork and provide evidence-based best practices that were utilized to improve teams in applied settings.

Six-Degree-Of-Freedom Optimal Feedback Control Of Pinpoint Landing Using Deep Neural Networks, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

Machine learning regression techniques have shown success at feedback control to perform near-optimal pinpoint landings for low fidelity formulations (e.g. 3 degree-of-freedom). Trajectories from these low-fidelity landing formulations have been used in imitation learning techniques to train deep neural network policies to replicate these optimal landings in closed loop. This study details the development of a near-optimal, neural network feedback controller for a 6 degree-of-freedom pinpoint landing system. To model disturbances, the problem is cast as either a multi-phase optimal control problem or a triple single-phase optimal control problem to generate examples of optimal control through the presence of disturbances. …

Stereoscopic-Based Mass Properties Estimation For Warhead Fragments, Alessia Nocerino, Katharine Larsen, Riccardo Bevilacqua, Elisabetta L. Jerome

Student Works

FRAGMENTATION characteristics such as spatial distribution, number of fragments, fragment velocity, and fragment mass can be used to characterize the lethality of a fragmenting weapon or any metal cased explosive [1,2]. However, most warhead tests and evaluations are limited to static arena testing, where fragment characteristics must be collected by hand. Recently, stereoscopic imaging techniques have been added to static arena tests. Using this method, position tracks can be collected for each fragment, and then velocity information can be found. This paper proposes a method to estimate the mass and moment of inertia using data collected by a stereoscopic imaging …

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?

Modeling And Estimation Of A Continuous Flexible Structure Using The Theory Of Functional Connections, Riccardo Bevilacqua

Math Department Colloquium Series

This talk presents a novel method for modeling and estimating the dynamics of a continuous structure based on a limited number of noisy measurements. The goal is reached using a Kalman filter in synergy with the recently developed mathematical framework known as the Theory of Functional Connections (TFC). The TFC allows to derive a functional expression capable of representing the entire space of the functions that satisfy a given set of linear and, in some cases, nonlinear constraints. The proposed approach exploits the possibilities offered by the TFC to derive an approximated dynamical model for the flexible system using the …

Orbital Debris Mitigation: Exploring Cubesat Drag Sail Technology, Robinson Raphael

Student Works

In an era marked by remarkable advancements in space exploration and research, the advent of satellite technology has contributed accordingly to the lives of people here on Earth. Through applications that tie into broadband connectivity, weather forecasting, disaster management, etc., the occupancy in orbital domains like Low-Earth Orbit (LEO) only continues to grow. However, the presence of orbital debris emerges as a significant concern, posing threats to both operational satellites and future space missions. Resulting as a consequence due to decades of activities since the launch of Sputnik 1 in 1957, as more countries ventured into space so did the …

State Space Modeling And Estimation Of Flexible Structure Using The Theory Of Functional Connections, Carlo Lombardi, Riccardo Bevilacqua

Student Works

In this work, we present a novel method to model the dynamics of a continuous structure based on measurements taken at discrete points. The method is conceived to provide new instruments to address the problem of flexible dynamics modeling in a spacecraft, where an effective mathematical representation of the non-rigid behavior of the is of critical importance in the design of an effective and reliable attitude estimation and control system. Both the measurements and the model that describes the structure can be affected by uncertainty. The purpose of the developed method is to estimate the position and the velocity of …

Using Machine Learning To Predict Hypervelocity Fragment Propagation Of Space Debris Collisions, Katharine Larsen, Riccardo Bevilacqua

Student Works

The future of spaceflight is threatened by the increasing amount of space debris, especially in the near-Earth environment. To continue operations, accurate characterization of hypervelocity fragment propagation following collisions and explosions is imperative. While large debris particles can be tracked by current methods, small particles are often missed. This paper presents a method to estimate fragment fly-out properties, such as fragment, velocity, and mass distributions, using machine learning. Previous work was performed on terrestrial data and associated simulations representing space debris collisions. The fragmentation of high-velocity fragmentation can be modeled by terrestrial fragmentation tests, such as static detonations. Recently, stereoscopic …

Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …

The Role Of Feedback Within Scrum For Engineering Department Operations, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu

Posters

The Scrum framework is built on the principles of inspection and adaptation. Feedback drives the inspection process, and the team adapts based on that feedback to optimize its performance and outcomes. Within engineering departments, Scrum requires departments to examine how and when feedback is obtained to ensure that the department is remaining agile. This poster illustrates the role of feedback within two Scrum teams, one focused on student success and the other focused on faculty rewards and incentives. The two cases emphasize the need for continuous introspection at team and department levels.

Interfacial Thermomechanical Behavior Of Hybrid Carbon Fibers, Sriraj Srihari

Doctoral Dissertations and Master's Theses

The carbon fiber/epoxy interface is of great importance in composite design due to its load transfer mechanisms from the weak epoxy to the stronger fiber. Improving the strength of the interface reduces the risk of failure at the interface and improves the load transfer to the fiber. In this study, two types of nano-species ZnO nanowires and nickel-based metal organic frameworks were grown on carbon fibers to improve the interfaces. The interfacial mechanics of the enhanced fibers are evaluated using nanoindentation studies. Composite samples with Aeropoxy matrix and vertically aligned fibers are fabricated for this purpose. A Bruker TI-980 TriboIndenter …

Design And Characterization Of A High Pressure Flow Loop For Heat Transfer Experiments Of Supercritical Carbon Dioxide, Joseph Sauerbrun

Doctoral Dissertations and Master's Theses

Supercritical carbon dioxide (sCO2) sees heightened heat transfer characteristics near its critical point due to its drastically changing thermophysical properties. Conventional single phase heat transfer theory was not developed to capture this nonlinear variation in properties and cannot predict the heat transfer characteristics of sCO2 to a practical level useful for design. To delve deeper into the behavior near the critical point and shed light on this crucial phenomenon, a state-of-the-art closed flow loop was developed. This setup enabled convective heat transfer experiments of sCO2 under diverse boundary conditions and test section geometries. Key components of the loop include the …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Explorations In Monocular Distance And Ranging (Modar) Techniques For Real-World Applications, Devon Vail

Doctoral Dissertations and Master's Theses

In this work, an initial prototype of a monocular camera system capable of retrieving depth-from-focus using a liquid focus-tunable lens is constructed out of hobby-grade photography equipment. This concept has been explored previously in laboratory settings using specialized equipment; this work seeks to determine the feasibility of retrieving depth-from-focus using commercially available components. To achieve this, an iterative exploration of existing techniques was performed to verify their utility in the final ensemble of processes to retrieve depth from 2D images. Initially, blurry images were simulated by applying Gaussian blur to test images to verify the functionality of a Laplacian of …

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …