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Air Force Institute of Technology

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Articles 211 - 240 of 2678

Full-Text Articles in Physical Sciences and Mathematics

The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon Mar 2022

The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon

Theses and Dissertations

Immersive simulations such as virtual reality is becoming more prevalent for use in training environments for many professions. United States Air Force firefighters may benefit from incorporating VR technology into their training program to increase organizational commitment, job satisfaction, self-efficacy, and job performance. With implementing a new training platform, it is also important to understand the relationship between these variables and the perceived benefits and efficacy of the VR training, which has not yet been studied in previous research. This study addresses this issue by gathering data from fire departments currently fielding a VR fire training platform.

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Autonomous And Resilient Management Of All-Source Sensors For Navigation Integrity: A Comparison And Analysis, Niles A. Tate Mar 2022

Autonomous And Resilient Management Of All-Source Sensors For Navigation Integrity: A Comparison And Analysis, Niles A. Tate

Theses and Dissertations

When navigating using Global Navigation Satellite Systems (GNSS), multiple/redundant, synchronous pseudorange measurements are readily available. However, when navigating in a GNSS degraded and/or denied region, this is not guaranteed. In response to this challenge, the ANT Center developed a framework known as Autonomous and Resilient Management of All-source Sensors (ARMAS). The ARMAS framework is designed to be resilient towards data corruption caused from mismodeled, uncalibrated, and faulty sensors. This thesis further expands on this work by performing a comparison against a Residual-Based Receiver Autonomous Integrity Monitoring (RBRAIM) scheme using simulated and real flight data to evaluate each systems performance.

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Generalized Robust Feature Selection, Bradford L. Lott Mar 2022

Generalized Robust Feature Selection, Bradford L. Lott

Theses and Dissertations

Feature selection may be summarized as identifying salient features to a given response. Understanding which features affect the response enables, in the future, only collecting consequential data; hence, the feature selection algorithm may lead to saving effort spent collecting data, storage resources, as well as computational resources for making predictions. We propose a generalized approach to select the salient features of data sets. Our approach may also be applied to unsupervised datasets to understand which data streams provide unique information. We contend our approach identifies salient features robust to the sub-sequent predictive model applied. The proposed algorithm considers all provided …

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Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray Mar 2022

Carbon Estimation And Decision Making In Usaf Acquisition, Robert F. Gray

Theses and Dissertations

Recent executive orders and international agreements require the United States to significantly reduce its carbon and greenhouse gas emissions. The DoD is a significant contributor to the carbon emissions of the USA and will be required to reduce the emissions. Therefore, in order to make appropriate programmatic decisions the DoD needs to develop an appropriate method for estimating carbon and making programmatic decisions; trading-off carbon emissions with the traditional cost-schedule-performance metrics. This thesis examines the possibility of developing a model that can be used to estimate the carbon footprint of producing a system before detailed engineering designed have been complete.

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Investigating Collaboration In Software Reverse Engineering, Allison M. Wong Mar 2022

Investigating Collaboration In Software Reverse Engineering, Allison M. Wong

Theses and Dissertations

Reverse engineering (RE) is a rigorous process of exploration and analysis to support software design recovery and exploit development. The process is often conducted in teams to divide the workload and take full advantage of engineers' individual expertise and strengths. Collaboration in RE requires versatile and reliable tools that can match the environment's unpredictable and fluid nature. While studies on collaborative software development have indicated common best practices and implementations, similar standards have not been explored in reverse engineering. This research conducts semi-structured interviews with reverse engineering experts to understand their needs and solutions while working in a team. The …

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Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos Mar 2022

Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos

Theses and Dissertations

A climatology of sporadic-E (Es) derived from a combined data set of GPS radio occultation (GPS-RO) and ground-based ionosonde soundings is presented for the period from September 2006 to February 2019. The ionosonde soundings were measured using the Lowell Digisonde International (LDI) Global Ionosphere Radio Observatory (GIRO) network consisting of 65 sites and 13,141,060 total soundings. The GPS-RO observations were taken aboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites and processed using two binary Es detection algorithms, totaling 9,072,922 occultations. The first algorithm is an S4 amplitude threshold calibrated to the occurrence of any blanketing Es …

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Real Time Evaluation Of Boom And Drogue Occlusion With Aar, Xiaoyang Wu Mar 2022

Real Time Evaluation Of Boom And Drogue Occlusion With Aar, Xiaoyang Wu

Theses and Dissertations

In recent years, Unmanned Aerial Vehicles (UAV) have seen a rise in popularity. Various navigational algorithms have been developed as a solution to estimate a UAV’s pose relative to the refueler aircraft. The result can be used to safely automate aerial refueling (AAR) to improve UAVs’ time-on-station and ensure the success of military operations. This research aims to reach real-time performance using a GPU accelerated approach. It also conducts various experiments to quantify the effects of refueling boom/drogue occlusion and image exposure on the pose estimation pipeline in a lab setting.

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Feasibility Of Fireball Trail Detection Using Ground-Based Gps Receivers, Ian R. Moffett Mar 2022

Feasibility Of Fireball Trail Detection Using Ground-Based Gps Receivers, Ian R. Moffett

Theses and Dissertations

The feasibility of using GPS data to detect fireballs is analyzed by first modeling the fireball’s trail diffusion and plasma chemistry to get a resulting ion density profile of the trail over time. The signal perturbation caused by the fireball trail is simulated for a ground receiver using an analytic solution for diffraction from a Gaussian lens. Five cases were modeled with varying initial peak ion densities and altitudes taken from fireball and reentry vehicle data. This paper shows that it is feasible to detect a fireball trail using GPS if the fireball has a sufficiently high initial ion density, …

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Examining Failures Of Kc-135s Using Survival Analysis, Vanessa I. R. Unseth Mar 2022

Examining Failures Of Kc-135s Using Survival Analysis, Vanessa I. R. Unseth

Theses and Dissertations

The United States Air Force manages an inventory of 396 KC-135 Stratotanker aircraft. With mission capability rates falling and total non-mission capability supply rates increasing, it is necessary to take a deeper look at recurrent failures. The study applies non-parametric and semi-parametric survival models to a dataset retrieved from LIMS-EV to look at the duration(s) until failure for the KC-135. Results of non-parametric models show cumulative failure rates increase as sorties or flight hours increase. In addition, semi-parametric models or Cox proportional hazards models with frailty confirm that locations or air bases are not associated with recurrent failures.

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Malware Detection Using Electromagnetic Side-Channel Analysis, Matthew A. Bergstedt Mar 2022

Malware Detection Using Electromagnetic Side-Channel Analysis, Matthew A. Bergstedt

Theses and Dissertations

Many physical systems control or monitor important applications without the capacity to monitor for malware using on-device resources. Thus, it becomes valuable to explore malware detection methods for these systems utilizing external or off-device resources. This research investigates the viability of employing EM SCA to determine whether a performed operation is normal or malicious. A Raspberry Pi 3 was set up as a simulated motor controller with code paths for a normal or malicious operation. While the normal path only calculated the motor speed before updating the motor, the malicious path added a line of code to modify the calculated …

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Evaluating Secure Enclave Firmware Development For Contemporary Risc-V Workstations, Samuel D. Chadwick Mar 2022

Evaluating Secure Enclave Firmware Development For Contemporary Risc-V Workstations, Samuel D. Chadwick

Theses and Dissertations

The emergence of the open-source RISC-V ISA empowers developers and engineers, device manufactures, industry leaders, nation-states, adversaries and allies alike with the unique opportunity to re-evaluate existing Trusted Computing paradigms. Emerging open-source security mechanisms facilitate the proliferation of Confidential Computing principles. These technology standards aim to provide secure enclave computing as a fundamental computing attribute, inherent within the RISC-V ISA specification. Security enforcement within these enclaves are handled by performing computation in memory-isolated, hardware-based, software-defined TEEs. This research evaluates the firmware development procedures required to implement Keystone Enclave on new unsupported hardware. Expressly, this effort extends Keystone SM firmware components …

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Automated Reconstructions For The Digital Forensic Examiner Workflow, Ryan P. Montgomery Mar 2022

Automated Reconstructions For The Digital Forensic Examiner Workflow, Ryan P. Montgomery

Theses and Dissertations

One product of a digital forensics examination is a reconstruction of events recorded in the media. A reconstruction places all of the case relevant trace into temporal, identity and associative relationships. Creating this reconstruction is a manual and time consuming process for the examiner. This thesis presents AIER. AIER integrates automation, abstraction and visualization into the Autopsy forensic software to improve the reconstruction process. The integration utilizes a custom Autopsy ingest module to extract and abstract artifact data and an interactive graph-based timeline visualization module. These improvements to the forensic examiner workflow are evaluated through a series of use cases.

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Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli Mar 2022

Improving Anonymized Search Relevance With Natural Language Processing And Machine Learning, Niko A. Petrocelli

Theses and Dissertations

Users often sacrifice personal data for more relevant search results, presenting a problem to communities that desire both search anonymity and relevant results. To balance these priorities, this research examines the impact of using Siamese networks to extend word embeddings into document embeddings and detect similarities between documents. The predicted similarity can locally re-rank search results provided from various sources. This technique is leveraged to limit the amount of information collected from a user by a search engine. A prototype is produced by applying the methodology in a real-world search environment. The prototype yielded an additional function of finding new …

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Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro Mar 2022

Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro

Theses and Dissertations

A method of generating synthetic lightning through the use of a convective available potential energy (CAPE) times precipitation rate (P) proxy is applied over three distinct climatological zones of the world for a single warm season: central and southern AZ of the United States, central Cuba, and North Korea. Global Forecast System (GFS) 0.25° by 0.25° forecast data for June, July, and August of 2019 is used to provide 6-hourly CAPE and precipitation rate, while Global Lightning Dataset (GLD360) data for the period 2016 to 2020 is used to provide observed lightning strokes. A five-year lightning climatology study is conducted …

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Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey Mar 2022

Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey

Theses and Dissertations

A challenging task in computer vision is finding techniques to improve the object detection and classification capabilities of ML models used for processing images acquired by moving aerial platforms. This research explores if GAN augmented UAV training sets can increase the generalizability of a detection model trained on said data. To answer this question, the YOLOv4-Tiny Object Detection Model was trained with aerial image training sets depicting rural environments. The salient objects within the frames were recreated using various GAN architectures, placed back into the original frames, and the augmented frames appended to the original training sets. GAN augmentation on …

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Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller Mar 2022

Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller

Theses and Dissertations

Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …

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Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price Mar 2022

Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price

Theses and Dissertations

Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …

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Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminant Surrogate Particle From Military Uniform Fabric, George D. Cooksey Mar 2022

Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminant Surrogate Particle From Military Uniform Fabric, George D. Cooksey

Theses and Dissertations

During a mass casualty medical evacuation after a bioaerosol attack, a decontamination method is needed that is effective at both decontamination and preventing the secondary hazard of biological particles reaerosolizing from contaminated clothing. However, neither the efficacy of current decontamination methods nor the risk of biological particle reaerosolization is significantly explored in existing literature. The goals of this thesis were to develop a repeatable methodology to quantify the reaerosolization of a biological contaminate off Airman Battle Uniform (ABU) fabric swatches, and to test the efficacy of one decontamination method (high-volume, low-pressure water) using 1 mpolystyrene latex (PSL) spheres as a …

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A Framework For Assessing Facility-Level Vulnerability And Risk To Extreme Weather Events, Blake A. Gawlik Mar 2022

A Framework For Assessing Facility-Level Vulnerability And Risk To Extreme Weather Events, Blake A. Gawlik

Theses and Dissertations

Intensifying extreme weather events, tied to the rise in the global average temperature, put global built infrastructure at risk. This presents a daunting challenge for organizational leaders who are tasked to determine how best to adapt current infrastructure to uncertain future events. To develop adaptation plans and policies, vulnerability and risk must be downscaled to an actionable scale, such that planners, designers, and engineers can make adaptation recommendations. However, previous research has largely assessed risk at coarser scales, e.g., regional, national, or global. These assessments are informative, but do not help those tasked to lead adaptation to make detailed, actionable …

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The Impacts Of Climate Uncertainty On Streamflow In Andes, Antioquia, Colombia, Kristen R. Roberts Mar 2022

The Impacts Of Climate Uncertainty On Streamflow In Andes, Antioquia, Colombia, Kristen R. Roberts

Theses and Dissertations

Natural hazards, such as hurricanes, wildfires, floods, and droughts impact human systems that rely on predictable patterns in the natural elements with which they interact. Skillful prediction of the impacts of climate change on linked, human-natural systems, like surface water resources, can help ensure physical risks within vulnerable communities are mitigated, resource sustainability is maximized, and intersectoral markets continue to contribute to socioeconomic stability. Due to water resources being a primary conduit through which climate uncertainty impacts people, economies, and ecosystems, its study is worthy of investigation; particularly, where those resources are uncertain and demanded by a variety of competitive …

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Persistence And Mitigation Of Pfas Within Concrete Stormwater Drainage Infrastructure, Jason R. Mcdonald Mar 2022

Persistence And Mitigation Of Pfas Within Concrete Stormwater Drainage Infrastructure, Jason R. Mcdonald

Theses and Dissertations

The persistence, fate, and transport of per- and poly-fluoroalkyl substances, which have been shown to have adverse effects on human health, have been previously studied in environmental media such as soils and groundwater. This study investigates concrete, a medium that is rarely studied but frequently present in instances where PFAS originating from AFFF releases and spills have occurred. Used heavily throughout aviation firefighting, AFFF poses environmental hazards due to the length of PFAS degradation and toxicological implications, thus its classification as a forever chemical. From the very limited reports to date, studies have suggested very slow release from concrete, potentially …

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Constructing Prediction Intervals With Neural Networks: An Empirical Evaluation Of Bootstrapping And Conformal Inference Methods, Alexander N. Contarino Mar 2022

Constructing Prediction Intervals With Neural Networks: An Empirical Evaluation Of Bootstrapping And Conformal Inference Methods, Alexander N. Contarino

Theses and Dissertations

Artificial neural networks (ANNs) are popular tools for accomplishing many machine learning tasks, including predicting continuous outcomes. However, the general lack of confidence measures provided with ANN predictions limit their applicability, especially in military settings where accuracy is paramount. Supplementing point predictions with prediction intervals (PIs) is common for other learning algorithms, but the complex structure and training of ANNs renders constructing PIs difficult. This work provides the network design choices and inferential methods for creating better performing PIs with ANNs to enable their adaptation for military use. A two-step experiment is executed across 11 datasets, including an imaged-based dataset. …

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Incorporating Armed Escorts To The Military Medical Evacuation Dispatching Problem Via Stochastic Optimization And Reinforcement Learning, Andrew G. Gelbard Mar 2022

Incorporating Armed Escorts To The Military Medical Evacuation Dispatching Problem Via Stochastic Optimization And Reinforcement Learning, Andrew G. Gelbard

Theses and Dissertations

The military medical evacuation (MEDEVAC) dispatching problem seeks to determine high-quality dispatching policies to maximize the survivability of casualties within contingency operations. This research leverages applied operations research and machine learning techniques to solve the MEDEVAC dispatching problem and evaluate system performance. More specifically, we develop an infinite-horizon, continuous-time Markov decision process (MDP) model and approximate dynamic programming (ADP) solution approach to generate high-quality policies. The ADP solution approach utilizes an approximate value iteration algorithm strategy incorporating gradient descent Q-learning to approximate the value function. A notional, synthetically-generated scenario in Africa based around the capital city of Niger, Niamey is …

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Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry Mar 2022

Formal Spark Verification Of Various Resampling Methods In Particle Filters, Osiris J. Terry

Theses and Dissertations

The software verification in this thesis concentrates on verifying a particle filter for use in tracking and estimation, a key application area for the Air Force. The development and verification process described in this thesis is a demonstration of the power, limitation, and compromises involved in applying automated software verification tools to critical embedded software applications.

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Simulating Autonomous Cruise Missile Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Kyle W. Goggins Mar 2022

Simulating Autonomous Cruise Missile Swarm Behaviors In An Anti-Access Area Denial (A2ad) Environment, Kyle W. Goggins

Theses and Dissertations

The increasingly sophisticated anti-access area denial (A2AD) threat imposed by the modern integrated air defense system (IADS), coupled with the decreasingly potent advantage provided by high-end stealth platforms, has prompted Air Force senior leaders to invest in radically changing the nature of air power for the year 2030 and beyond. A prominent element of this new vision is weapon swarming, which aims to address this challenge by overwhelming the IADS with huge numbers of low-cost, attritable aerial assets emboldened by autonomous capabilities. This research proposes a framework for classifying the different levels of autonomous capability along three independent dimensions—namely ability …

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Securing Infiniband Networks With End-Point Encryption, Noah B. Diamond Mar 2022

Securing Infiniband Networks With End-Point Encryption, Noah B. Diamond

Theses and Dissertations

The NVIDIA-Mellanox Bluefield-2 is a 100 Gbps high-performance network interface which offers hardware offload and acceleration features that can operate directly on network traffic without routine involvement from the ARM CPU. This allows the ARM multi-core CPU to orchestrate the hardware to perform operations on both Ethernet and RDMA traffic at high rates rather than processing all the traffic directly. A testbed called TNAP was created for performance testing and a MiTM verification process called MiTMVMP is used to ensure proper network configuration. The hardware accelerators of the Bluefield-2 support a throughput of nearly 86 Gbps when using IPsec to …

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Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park Mar 2022

Dds-Cerberus: Improving Security In Dds Middleware Using Kerberos Tickets, Andrew T. Park

Theses and Dissertations

The military deploys many IoT in battlefield operations to provide information on terrain and enemy combatants. It also deploys automated robots or UAVs where securing and trusting collected data is essential. Choosing the middleware that handles this message transfer is crucial for real-time operations. Networks with multiple entities, including IoT devices, UAVs, and small computers, require robust middleware facilitating message sending in real-time. Ideally, the middleware would provide QoS to handle lost packets and retransmissions in lossy environments, especially between low-power machines. DDS is a middleware that implements real-time and QoS capabilities by sending messages, not based on endpoints but …

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Exploring Learning Classifier System Behaviors In Multi-Action, Turn-Based Wargames, Garth J.S. Terlizzi Iii Mar 2022

Exploring Learning Classifier System Behaviors In Multi-Action, Turn-Based Wargames, Garth J.S. Terlizzi Iii

Theses and Dissertations

State of the art game-playing Artificial Intelligence research focuses heavily on non-symbolic learning methods. These methods offer little explainable insight into their decision-making processes. Learning Classifier Systems (LCSs) provide an alternative. LCSs use rule-based learning, guided by a Genetic Algorithm (GA), to produce a human-readable rule-set. This thesis explores LCS usefulness in game-playing agents for multi-agent wargames. Several Multi-Agent Learning Classifier System (MALCS) variants are implemented in the wargame Stratagem MIST: a Zeroeth-Level Classifier System (ZCS), an extended Classifier System (XCS), and an Adaptive Pittsburgh Classifier System (APCS). These algorithms were tested against baseline agents as well as the Online …

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Intercomparison Of Four Microphysics Schemes In Simulating Persistent Arctic Mixed-Phase Stratocumulus Clouds, Zachary A. Cleveland Mar 2022

Intercomparison Of Four Microphysics Schemes In Simulating Persistent Arctic Mixed-Phase Stratocumulus Clouds, Zachary A. Cleveland

Theses and Dissertations

Persistent Arctic mixed-phase stratocumulus clouds (AMPS) are important to the surface radiation budget of the Arctic. Their presence produces warming within the boundary layer and at the surface and inaccurately forecasting AMPS can lead to large, erroneous temperature forecasts. A Large Eddy Simulation of a case study of a persistent AMPS cloud was conducted using the Advanced Research Weather Research and Forecasting (WRF-ARW) model. The case examined occurred near Oliktok Point, AK between 26 and 27 April, 2017. The produced cloud pattern and properties of four different microphysics schemes -- P3, Thompson, Morrison, and WSM6 -- are compared to observations. …

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Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha Mar 2022

Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha

Faculty Publications

In this work, an attempt has been made to explore numerically the thermo-fluidic transport process in a novel M-shaped enclosure filled with permeable material along with Al2O3-Cu hybrid nanoparticles suspended in water under the influence of a horizontal magnetizing field. To exercise the influence of geometric parameters, a classical trapezoidal cavity is modified with an inverted triangle at the top to construct an M-shaped cavity. The cavity is heated isothermally from the bottom and cooled from the top, whereas the inclined sidewalls are insulated. The role of geometric parameters on the thermal performance is scrutinized thoroughly …

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