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Strengthening Criteria Independence Through Optimization Of Alternative Value Ratio Comparisons, Joseph P. Kristbaum, Frank W. Ciarallo
Strengthening Criteria Independence Through Optimization Of Alternative Value Ratio Comparisons, Joseph P. Kristbaum, Frank W. Ciarallo
Faculty Publications
Every decision maker’s internal scale is different based on a myriad of possible factors unique to that decision maker. Conflicting criteria within and between alternatives in multicriteria decision making can create negative effects within the weighting schemes and amplify preference biases and scale disparities between decision makers in a group decision context. Additionally, the weighting of group decision-making frameworks can intensify the already skewed criteria values. When making judgments against requirements, it may be preferable to reduce scale trend distortions between decision makers as much as possible. Previous research supports that certain information presentation modes can significantly reduce preference bias …
Rotating Scatter Mask For Directional Radiation Detection And Imaging, Darren Holland, Robert Olesen, Larry Burggraf, Buckley O'Day, James E. Bevins
Rotating Scatter Mask For Directional Radiation Detection And Imaging, Darren Holland, Robert Olesen, Larry Burggraf, Buckley O'Day, James E. Bevins
AFIT Patents
A radiation imaging system images a distributed source of radiation from an unknown direction by rotating a scatter mask around a central axis. The scatter mask has a pixelated outer surface of tangentially oriented, flat geometric surfaces that are spherically varying in radial dimension that corresponds to a discrete amount of attenuation. Rotation position of the scatter mask is tracked as a function of time. Radiation counts from gamma and/or neutron radiation are received from at least one radiation detector that is positioned at or near the central axis. A rotation-angle dependent detector response curve (DRC) is generated based on …
Autonomous Mission Planning For Spacecraft Rendezvous And Proximity Operations, Julia C. Bell
Autonomous Mission Planning For Spacecraft Rendezvous And Proximity Operations, Julia C. Bell
Theses and Dissertations
The evolving space environment has created a demand for autonomous spacecraft that can maneuver in complex and sometimes contentious environments. Constraint enforcement, such as an avoidance zone to prevent collision with a target, is a key component of autonomous control to ensure safety and performance requirements are met. Finite-horizon Model Predictive Control (MPC) is a popular control method due to its improved computation time while optimizing performance. Two areas of MPC in need of expansion are time-varying constraints and phase transitions in multi-phase applications. In this work, MPC is employed to track the reference trajectory of a multi-phase satellite inspection …
Improving The Stability And Operability Of A Small-Scale Rotating Detonation Engine, Nathan T. Fiorino
Improving The Stability And Operability Of A Small-Scale Rotating Detonation Engine, Nathan T. Fiorino
Theses and Dissertations
A small scale RDE was designed with a channel diameter of 28 mm and channel gap of 2 mm and operated on nitrous oxide (N2O) and ethylene (C2H4) as the oxidizer and fuel respectively. Changes to the original Jets in Crossflow (JIC) injection scheme and spark plug ignition method were implemented to counteract previously observed wave instabilities. Successful detonation was observed over a range of mass flows (0.035-0.068 kg/s) and equivalence ratios (ɸ = 0.6-1.4) and a stable single wave mode with frequency up to 16.8 kHz was observed for the first time. Injection …
Sar Collection Planning And Data Quality Assessment, Jacob M. Brumfield
Sar Collection Planning And Data Quality Assessment, Jacob M. Brumfield
Theses and Dissertations
Radar resource management is an important research topic in the radar community. Identifying the performance of a synthetic aperture radar image early into a data processing chain can improve intelligence collection mission performance. To achieve that goal, separate flags can be presented to a radar technician along a data processing chain to identify various errors within a data collection. Toward the end, this thesis analyzes he radar image processing chain and identifies data quality checks that could be implemented. The first quality check is to identify canonical targets and the necessary Nyquist-Shannon sampling requirements. Then, observations can be made to …
Prioritizing Facilities Linked To Corporate Strategic Objectives Using A Fuzzy Model, Devin Depalmer, Steven J. Schuldt, Justin D. Delorit
Prioritizing Facilities Linked To Corporate Strategic Objectives Using A Fuzzy Model, Devin Depalmer, Steven J. Schuldt, Justin D. Delorit
Faculty Publications
Excerpt: Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.
Statistically Defensible Wind Tunnel Models, Timothy A. Roche
Statistically Defensible Wind Tunnel Models, Timothy A. Roche
Theses and Dissertations
Wind tunnels are used to test scale-model air frames in order to collect aerodynamic data. The Subsonic Aerodynamic Research Laboratory (SARL) Wind Tunnel is a low speed wind tunnel located at Wright-Patterson Air Force Base. The SARL Wind Tunnel team approached AFIT for assistance in creating statistically defensible models for the conditions inside the wind tunnel. During a wind tunnel test, pressure sensors cannot be placed at the test model. Instead, pressure is measured by a pitot probe permanently mounted in the corner of the test chamber. The pressure at the model location is predicted from the measurements taken by …
Neutron Pulse-Time Extension Through Conversion To Positronium, Shawn T. Mctaggart
Neutron Pulse-Time Extension Through Conversion To Positronium, Shawn T. Mctaggart
Theses and Dissertations
Laser-Plasma interactions have strong potential as future neutron sources. Measuring the neutron rate is difficult due to several issues: the very short duration of the laser pulse and subsequent fusion events (on the order of a few picoseconds), the corresponding short duration of the neutron pulse, and the simultaneous emission of other ionizing particles such as protons and electrons. A system was designed to measure neutron emission by imposing a delay from the emission of other radiation by conversion of the neutrons into ortho-positronium (o-Ps), the triplet state of positronium. This lifetime extension enables more sensitive and selective detection of …
Feasibility Study Of Radio Frequency Microelectromechanical Filters For Space Operation, Karanvir Singh
Feasibility Study Of Radio Frequency Microelectromechanical Filters For Space Operation, Karanvir Singh
Theses and Dissertations
Piezoelectric contour mode resonator technology has the unique advantage of combining low motional resistance with the ability to define multiple frequencies on the same substrate. Contour mode resonators can be mechanically coupled together to form robust band-pass filters for the next generation of GPS satellites with extreme size reduction compared to electrically coupled filters. Piezoelectric zinc oxide (ZnO) contour mode resonators have the potential for monolithic integration with current ZnO transistor further reducing size, power consumption, and cost of filter modules. Barium strontium titanate (BST) contour mode resonators have incredible frequency tunability due to the fundamental nature of the thin …
One Dimensional Study Of Magnetoplasmadynamic Thrusters For A Potential New Class Of Heavy Ion Drivers For Plasma Jet Driven Magnetoinertial Fusion, Patrick M. Brown
One Dimensional Study Of Magnetoplasmadynamic Thrusters For A Potential New Class Of Heavy Ion Drivers For Plasma Jet Driven Magnetoinertial Fusion, Patrick M. Brown
Theses and Dissertations
Plasma Jet Driven Magnetoinertial Fusion (PJMIF) requires high velocity heavy ion drivers in order to compress a magnetized target to fusion conditions. Previous work with heavy ion drivers has revealed sub-par accelerations due to plasma instabilities; thus, it is necessary to investigate new methods of heavy ion plasma acceleration. One such method is Magnetoplasmadynamic (MPD) thrusters. Past studies of these thrusters have been conducted at an initial temperature at or below the energy of full ionization. Here MPD thrusters are investigated using a Godunov type MHD solver with a Harten-Lax van Leer-D (HLLD) flux solving scheme assuming the plasma is …
Correlated Positron-Electron Orbital (Cpeo): A Novel Method That Models Positron-Electron Correlation In Virtual Ps At The Mean-Field Level, Kevin E. Blaine
Correlated Positron-Electron Orbital (Cpeo): A Novel Method That Models Positron-Electron Correlation In Virtual Ps At The Mean-Field Level, Kevin E. Blaine
Theses and Dissertations
The Correlated Positronic-Electronic Orbital (CPEO) method was developed and implemented to capture correlation effects at between the positron and electron in the modeling of systems that involve a bound positron. Methods that effectively model these systems require many hundred basis functions and use a mean field approach as the beginning step. CPEO builds an orbital for virtual Positronium (Ps) that contains a positron in a bound state along with an accompanying electron to the larger system. Assigning the virtual Ps orbital allows for the two particle variational optimization in conjunction with the other particles that compose the whole system. This …
Evolutionary Generation Of Diversity In Embedded Binary Executables For Cyber Resiliency, Mitchell D. I. Hirschfeld
Evolutionary Generation Of Diversity In Embedded Binary Executables For Cyber Resiliency, Mitchell D. I. Hirschfeld
Theses and Dissertations
Hardening avionics systems against cyber attack is difficult and expensive. Attackers benefit from a "break one, break all" advantage due to the dominant mono-culture of automated systems. Also, undecidability of behavioral equivalence for arbitrary algorithms prevents the provable absence of undesired behaviors within the original specification. This research presents results of computational experiments using bio-inspired genetic programming to generate diverse implementations of executable software and thereby disrupt the mono-culture. Diversity is measured using the SSDeep context triggered piecewise hashing algorithm. Experiments are divided into two phases. Phase I explores the use of semantically-equivalent alterations that retain the specified behavior of …
A Quantitative Argument For Autonomous Aerial Defense Overembedded Missile Systems To Thwart Cruise Threats, Andrew R. Davis
A Quantitative Argument For Autonomous Aerial Defense Overembedded Missile Systems To Thwart Cruise Threats, Andrew R. Davis
Theses and Dissertations
Given the high cost of missile defense systems, their ability to be overwhelmed, and rising tensions between the U.S. and adversaries in the Indo-Pacific region, a new modeled is proposed to investigate a new approach to missile defense. The Autonomous Aerial Defense Against Missiles (AADAM) system leverages reusable, small-scale UAVs to propose a cheaper, more effective system in defending against cruise missile threats. The aim of this system is to provide and additional layer in current missile defense strategies at lower-cost. This modeled system is found to outperform a modeled Patriot system in close-range interception of designated assets, with no …
Synthetic Aperture Radar Image Recognition Of Armored Vehicles, Christopher Szul, Torrey J. Wagner, Brent T. Langhals
Synthetic Aperture Radar Image Recognition Of Armored Vehicles, Christopher Szul, Torrey J. Wagner, Brent T. Langhals
Faculty Publications
Synthetic Aperture Radar (SAR) imagery is not affected by weather and allows for day-and-night observations, however it can be difficult to interpret. This work applies classical and neural network machine learning techniques to perform image classification of SAR imagery. The Moving and Stationary Target Acquisition and Recognition dataset from the Air Force Research Laboratory was used, which contained 2,987 total observations of the BMP-2, BTR-70, and T-72 vehicles. Using a 75%/25% train/test split, the classical model achieved an average multi-class image recognition accuracy of 70%, while a convolutional neural network was able to achieve a 97% accuracy with lower model …
Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals
Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals
Faculty Publications
Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …
Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals
Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals
Faculty Publications
Current food crisis predictions are developed by the Famine Early Warning System Network, but they fail to classify the majority of food crisis outbreaks with model metrics of recall (0.23), precision (0.42), and f1 (0.30). In this work, using a World Bank dataset, classical and neural network (NN) machine learning algorithms were developed to predict food crises in 21 countries. The best classical logistic regression algorithm achieved a high level of significance (p < 0.001) and precision (0.75) but was deficient in recall (0.20) and f1 (0.32). Of particular interest, the classical algorithm indicated that the vegetation index and the food price index were both positively correlated with food crises. A novel method for performing an iterative multidimensional hyperparameter search is presented, which resulted in significantly improved performance when applied to this dataset. Four iterations were conducted, which resulted in excellent 0.96 for metrics of precision, recall, and f1. Due to this strong performance, the food crisis year was removed from the dataset to prevent immediate extrapolation when used on future data, and the modeling process was repeated. The best “no year” model metrics remained strong, achieving ≥0.92 for recall, precision, and f1 while meeting a 10% f1 overfitting threshold on the test (0.84) and holdout (0.83) datasets. The year-agnostic neural network model represents a novel approach to classify food crises and outperforms current food crisis prediction efforts.
Model For Quantifying The Quality Of Secure Service, Paul M. Simon, Scott R. Graham, Christopher Talbot, Micah J. Hayden
Model For Quantifying The Quality Of Secure Service, Paul M. Simon, Scott R. Graham, Christopher Talbot, Micah J. Hayden
Faculty Publications
Although not common today, communications networks could adjust security postures based on changing mission security requirements, environmental conditions, or adversarial capability, through the coordinated use of multiple channels. This will require the ability to measure the security of communications networks in a meaningful way. To address this need, in this paper, we introduce the Quality of Secure Service (QoSS) model, a methodology to evaluate how well a system meets its security requirements. This construct enables a repeatable and quantifiable measure of security in a single- or multi-channel network under static configurations. In this approach, the quantification of security is based …
The Effects Of Individual Differences, Non‐Stationarity, And The Importance Of Data Partitioning Decisions For Training And Testing Of Eeg Cross‐Participant Models, Alexander J. Kamrud, Brett J. Borghetti, Christine M. Schubert Kabban
The Effects Of Individual Differences, Non‐Stationarity, And The Importance Of Data Partitioning Decisions For Training And Testing Of Eeg Cross‐Participant Models, Alexander J. Kamrud, Brett J. Borghetti, Christine M. Schubert Kabban
Faculty Publications
EEG-based deep learning models have trended toward models that are designed to perform classification on any individual (cross-participant models). However, because EEG varies across participants due to non-stationarity and individual differences, certain guidelines must be followed for partitioning data into training, validation, and testing sets, in order for cross-participant models to avoid overestimation of model accuracy. Despite this necessity, the majority of EEG-based cross-participant models have not adopted such guidelines. Furthermore, some data repositories may unwittingly contribute to the problem by providing partitioned test and non-test datasets for reasons such as competition support. In this study, we demonstrate how improper …
Single-Shot Positron Annihilation Lifetime Spectroscopy Using A Liquid Scintillator, Joshua R. Machacek, Shawn Mctaggart, Larry W. Burggraf
Single-Shot Positron Annihilation Lifetime Spectroscopy Using A Liquid Scintillator, Joshua R. Machacek, Shawn Mctaggart, Larry W. Burggraf
Faculty Publications
Liquid scintillators provide a fast, single component response. However, they traditionally have a low flashpoint and high vapor pressure. We demonstrate the use of an EJ-309 scintillator (high flashpoint and low vapor pressure variant) to acquire single-shot positron annihilation lifetime spectroscopy spectra using a trap-based positron beam.
Defect Detection In Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning, Philip Cho, Aihua W. Wood, Krishnamurthy Mahalingam, Kurt Eyink
Defect Detection In Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning, Philip Cho, Aihua W. Wood, Krishnamurthy Mahalingam, Kurt Eyink
Faculty Publications
Point defects play a fundamental role in the discovery of new materials due to their strong influence on material properties and behavior. At present, imaging techniques based on transmission electron microscopy (TEM) are widely employed for characterizing point defects in materials. However, current methods for defect detection predominantly involve visual inspection of TEM images, which is laborious and poses difficulties in materials where defect related contrast is weak or ambiguous. Recent efforts to develop machine learning methods for the detection of point defects in TEM images have focused on supervised methods that require labeled training data that is generated via …
Meta-Heuristic Optimization Methods For Quaternion-Valued Neural Networks, Jeremiah Bill, Lance E. Champagne, Bruce Cox, Trevor J. Bihl
Meta-Heuristic Optimization Methods For Quaternion-Valued Neural Networks, Jeremiah Bill, Lance E. Champagne, Bruce Cox, Trevor J. Bihl
Faculty Publications
In recent years, real-valued neural networks have demonstrated promising, and often striking, results across a broad range of domains. This has driven a surge of applications utilizing high-dimensional datasets. While many techniques exist to alleviate issues of high-dimensionality, they all induce a cost in terms of network size or computational runtime. This work examines the use of quaternions, a form of hypercomplex numbers, in neural networks. The constructed networks demonstrate the ability of quaternions to encode high-dimensional data in an efficient neural network structure, showing that hypercomplex neural networks reduce the number of total trainable parameters compared to their real-valued …
Characterization Of A Boron-Loaded Deuterated Liquid Scintillator For Fast And Thermal Neutron Detection, Bryan V. Egner, Michael Febbraro, James E. Bevins
Characterization Of A Boron-Loaded Deuterated Liquid Scintillator For Fast And Thermal Neutron Detection, Bryan V. Egner, Michael Febbraro, James E. Bevins
Faculty Publications
The preparation and characterization of novel boron-loaded deuterated liquid scintillators (BLDLS) are presented for the first time to investigate the performance of a detector sensitive to both fast and thermal neutrons intended for future neutron spectroscopy measurements. Three deuterated toluene-based scintillation cocktails were produced, one without boron, one loaded with ortho-carborane (natural boron isotopic abundance), and one with 96 wt% 10B enriched ortho-carborane. General optical and material properties were analyzed to include the composition, density, index of refraction, photoluminescence emission spectra, and absorbance spectra in addition to the relative light yield, resolution, relative efficiency, and pulse-shape-discrimination performance for all three …
Impact Of Hurricane Michael (2018) On Local Vertical Total Electron Content, Joanna E.S. Williams, Robert C. Tournay, H. Rose Tseng, Daniel J. Emmons Ii, Omar A. Nava
Impact Of Hurricane Michael (2018) On Local Vertical Total Electron Content, Joanna E.S. Williams, Robert C. Tournay, H. Rose Tseng, Daniel J. Emmons Ii, Omar A. Nava
Faculty Publications
An analysis of vertical total electron content (TEC) estimates from the MIT Madrigal database is performed for the regions surrounding the eye of Hurricane Michael (2018). Absolute and detrended TEC values show a noticeable increase during the tropical cyclone (TC) relative to fluctuations at the same locations prior to the storm. Direct comparisons of TEC perturbation magnitudes to the number of lightning flashes in latitude-longitude boxes surrounding the eye of Hurricane Michael for each 5 min period of 10 October 2018 showed no visible trends. A similar comparison of the vertical TEC fluctuations with respect to the rainfall rates showed …
Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv
Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv
Faculty Publications
We present twisted spatiotemporal optical vortex (STOV) beams, which are partially coherent light sources that possess a coherent optical vortex and a random twist coupling their space and time dimensions. These beams have controllable partial coherence and transverse orbital angular momentum (OAM), which distinguishes them from the more common spatial vortex and twisted beams (known to carry longitudinal OAM) in the literature and should ultimately make them useful in applications such as optical communications and optical tweezing. We present the mathematical analysis of twisted STOV beams, deriving the mutual coherence function and linear and angular momentum densities. We simulate the …
Zn Acceptors In Β-Ga2O3 Crystals, Timothy D. Gustafson, J. Jesenovec, Christopher A. Lenyk, Nancy C. Giles, J. S. Mccloy, M. Mccluskey, Larry E. Halliburton
Zn Acceptors In Β-Ga2O3 Crystals, Timothy D. Gustafson, J. Jesenovec, Christopher A. Lenyk, Nancy C. Giles, J. S. Mccloy, M. Mccluskey, Larry E. Halliburton
Faculty Publications
Electron paramagnetic resonance (EPR) is used to identify and characterize neutral zinc acceptors in Zn-doped β-Ga2O3 crystals. Two EPR spectra are observed at low temperatures, one from Zn ions at tetrahedral Ga(1) sites (the Zn0Ga1 acceptor) and one from Zn ions at octahedral Ga(2) sites (the Zn0Ga2 acceptor). These Zn acceptors are small polarons, with the unpaired spin localized in each case on a threefold coordinated oxygen O(I) ion adjacent to the Zn ion. Resolved hyperfine interactions with neighboring 69Ga and 71Ga nuclei allow the EPR spectra from the two acceptors …
Achieving The Shot-Noise Limit Using Experimental Multi-Shot Digital Holography Data, Douglas E. Thornton, Cameron J. Radosevich, Samuel Horst, Mark F. Spencer
Achieving The Shot-Noise Limit Using Experimental Multi-Shot Digital Holography Data, Douglas E. Thornton, Cameron J. Radosevich, Samuel Horst, Mark F. Spencer
Faculty Publications
In this paper, we achieve the shot-noise limit using straightforward image-post-processing techniques with experimental multi-shot digital holography data (i.e., off-axis data composed of multiple noise and speckle realizations). First, we quantify the effects of frame subtraction (of the mean reference-only frame and the mean signal-only frame from the digital-hologram frames), which boosts the signal-to-noise ratio (SNR) of the baseline dataset with a gain of 2.4 dB. Next, we quantify the effects of frame averaging, both with and without the frame subtraction. We show that even though the frame averaging boosts the SNR by itself, the frame subtraction and the stability …
Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith
Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith
AFIT Patents
A passive microscopic Fabry-Pérot Interferometer (FPI) sensor an optical fiber a three-dimensional microscopic optical structure formed on a cleaved tip of an optical fighter that reflects a light signal back through the optical fiber. The reflected light is altered by refractive index changes in the three-dimensional structure that is subject to at least one of: (i) thermal radiation; and (ii) volatile organic compounds.
Weather-Related Construction Delays In A Changing Climate: A Systematic State-Of-The-Art Review, Steven J. Schuldt, Matthew R. Nicholson, Yaquarri A. Adams Ii, Justin D. Delorit
Weather-Related Construction Delays In A Changing Climate: A Systematic State-Of-The-Art Review, Steven J. Schuldt, Matthew R. Nicholson, Yaquarri A. Adams Ii, Justin D. Delorit
Faculty Publications
Adverse weather delays forty-five percent of construction projects worldwide, costing project owners and contractors billions of dollars in additional expenses and lost revenue each year. Additionally, changes in climate are expected to increase the frequency and intensity of weather conditions that cause these construction delays. Researchers have investigated the effect of weather on several aspects of construction. Still, no previous study comprehensively (1) identifies and quantifies the risks weather imposes on construction projects, (2) categorizes modeling and simulation approaches developed, and (3) summarizes mitigation strategies and adaptation techniques to provide best management practices for the construction industry. This paper accomplishes …
Air Force Institute Of Technology Research Report 2020, Graduate School Of Engineering And Management, Air Force Institute Of Technology
Air Force Institute Of Technology Research Report 2020, Graduate School Of Engineering And Management, Air Force Institute Of Technology
AFIT Documents
This Research Report presents the FY20 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial …
An Analysis Of Various Hydrogen Production Methods For Fleet Vehicle Fuel, Eugene J. Denezza Ii
An Analysis Of Various Hydrogen Production Methods For Fleet Vehicle Fuel, Eugene J. Denezza Ii
Theses and Dissertations
As conflict, the environment, and politics cause changes around the world, the United States Air Force is pursuing a diversification of drop-in and alternative fuel sources. Hydrogen fuel cells for vehicles are gaining popularity worldwide. Yet, how to best produce hydrogen gas still remains a question. This thesis will provide an overview of various hydrogen production methods and their respective environmental impacts, costs, efficiencies, and viability; and will perform sensitivity analysis to determine an optimal solution. The optimal production method is Thermolysis followed by Steam Reformation of Landfill or Natural Gas, Coal Gasification, and PEM Electrolysis. Based on varying requirements …