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Articles 1 - 30 of 76
Full-Text Articles in Engineering
Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa
Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa
Theses and Dissertations
“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …
Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi
Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi
Theses and Dissertations
This research focuses on the cyber-attack of the smart grid and its retrieval to a normal state by estimating the smart grid's resilience. This study developed a theoretical model to estimate the resilience of the smart grid using choice modeling. A utility function is formulated based on various factors and sub-factors of resilience to estimate the resilience of the smart grid. Choice modeling is applied to estimate the model parameters in various fields such as marketing, energy, transportation, and health and to predict the outcome.
Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela
Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela
Theses and Dissertations
We developed a deep fusion methodology of non-destructive (NDT) in-situ infrared and ex- situ ultrasonic images for localization of porosity detection without compromising the integrity of printed components that aims to improve the Laser-based additive manufacturing (LBAM) process. A core challenge with LBAM is that lack of fusion between successive layers of printed metal can lead to porosity and abnormalities in the printed component. We developed a sensor fusion U-Net methodology that fills the gap in fusing in-situ thermal images with ex-situ ultrasonic images by employing a U-Net Convolutional Neural Network (CNN) for feature extraction and two-dimensional object localization. We …
The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna
The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna
Theses and Dissertations
This dissertation develops virtual reality modules to capture individuals’ learning abilities and systems thinking skills in dynamic environments. In the first chapter, an immersive queuing theory teaching module is developed using virtual reality technology. The objective of the study is to present systems engineering concepts in a more sophisticated environment and measure students learning abilities. Furthermore, the study explores the performance gaps between male and female students in manufacturing systems concepts. To investigate the gender biases toward the performance of developed VR module, three efficacy measures (simulation sickness questionnaire, systems usability scale, and presence questionnaire) and two effectiveness measures (NASA …
Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi
Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi
Theses and Dissertations
The growth of technology and the proliferation of information made modern complex systems more fragile and vulnerable. As a result, competitive advantage is no longer achieved exclusively through strategic planning but by developing an influential cadre of technical people who can efficiently manage and navigate modern complex systems. The dissertation aims to provide educators, practitioners, and organizations with a model that helps to measure individuals’ systems thinking skills, complex problem solving, personality traits, and the impacting demographic factors such as managerial and work experience, current occupation type, organizational ownership structure, and education level. The intent is to study how these …
Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe
Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe
Theses and Dissertations
Wood pellet production has become an advancing industry for the sake of reducing greenhouse emissions into the atmosphere especially, in European Union countries. Researchers and industry executives seek new methods and materials to improve the pelletization process. Rice hulls or husks has the potential to aid in wood pelletization as they possess high calorific values. This study focuses on using rice hull derived bio-oil from pyrolysis, which will also decrease ash content, as an additive to aid in the wood pelletization process. Using two groups of rice hull derived bio-oil as an additive in wood pelletization: Group 1 uses heavy …
A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio
A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio
Theses and Dissertations
Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures …
Testing Of Methods For Reducing Motivational Bias In Multi - Criteria Decision Analysis Problems, Chadwick Samuel Kerr
Testing Of Methods For Reducing Motivational Bias In Multi - Criteria Decision Analysis Problems, Chadwick Samuel Kerr
Theses and Dissertations
The idea of multi-criteria decision making has been around for quite a while. All judgement tasks are potential points of bias introduction. Each judgement task was assessed to identify common biases introduced through an extensive literature review for each task and bias. In several other studies, the distinction is made between cognitive and motivational biases. Cognitive biases are widely studied and well known with mitigations that have been validated. Motivational biases are judgements influenced by the decision maker’s desire for a specific outcome, also referred to as intentional bias, that are hard to correct and received very little testing and …
Applications In Multi-Band Isolation Of Spectra With Data-Adaptive Sub-Banding (Midas): Using Multi-Criteria Decision Analysis To Optimize Midas-Based De-Noising Methods When Processing Infrasound And Other Signals Of Interest, Everett Raymond Coots
Theses and Dissertations
The ever-present challenge faced by the signal processing analyst is to get more from the available data, whether it be exploiting the same data in new ways to garner new information, or simply to increase the confidence in existing qualitative metrics. Traditional techniques include filtering (to improve the signal to noise ratio of detected signals or images or to isolate and possibly remove interfering signals), feature detection/extraction (identifying key characteristics within the signal) and signal decomposition (identification of dominant signals of interest relative to noise terms). Current research by our team began with an emphasis on the filtering of signals …
A Joint Soft Warping And Clustering Approach To Detecting Time Series Anomalies, Christopher John Schuchmann
A Joint Soft Warping And Clustering Approach To Detecting Time Series Anomalies, Christopher John Schuchmann
Theses and Dissertations
Unsupervised anomalous time series detection methods focus on identifying outliers without prior knowledge of the dataset. However, these methods often require multiple parameters to be optimized, with adequate performance tied to their careful tuning and prior domain knowledge. In this work, two methods are proposed for detecting outlier time series that adopt a joint clustering and alignment optimization to filter out the desired signals. The time series are globally clustered while simultaneously being aligned to other signals in their same cluster group. This alternating optimization employs time-warping similarity measures to help identify closely matching time series as well as the …
Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He
Theses and Dissertations
Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …
The Effect Of Information Acquisition Automation And Workspace Design On Human Pattern Recognition For Information Fusion, Kellie L. Turner
The Effect Of Information Acquisition Automation And Workspace Design On Human Pattern Recognition For Information Fusion, Kellie L. Turner
Theses and Dissertations
Automation employed in information fusion systems is designed to help humans combine information derived from multiple sources to form a cohesive assessment of the situation. Research using the Levels of Automation model (Parasuraman, Wickens, and Sheridan, 2000) have produced conflicting results, which Patterson (2017) posited was because it focused solely on analytical processing while neglecting the effects of intuitive cognition. The present study examined how information acquisition automation affects the human’s ability to detect patterns in data needed to reach higher levels of information fusion. Results showed that when information acquisition was performed through manual operations, pattern recognition performance was …
Machine Learning Application For Mission Data Reprogramming, Paolo A. Bingham
Machine Learning Application For Mission Data Reprogramming, Paolo A. Bingham
Theses and Dissertations
Before entering a conflict or theater, USAF aircraft require updated mission data software reprogramming. Mission data controls all electronic warfare (EW) operations of the aircraft. EW operations include identifying and jamming radar operated systems, whether they are friendly or hostile. The process of reprogramming software is continuous and routinely updated for every EW system annually. On specific circumstances, the process can be expedited to months, but this puts a strain on the development team and shifts all attention to one specific mission data file. Unfortunately, a growing number of requests to upgrade mission data to a higher priority state, has …
Assessment Of Visual Field Performance Asymmetries While Utilizing Aircraft Attitude Symbology, George A. Reis
Assessment Of Visual Field Performance Asymmetries While Utilizing Aircraft Attitude Symbology, George A. Reis
Theses and Dissertations
Two experiments were conducted to examine visual performance asymmetries when perceiving complex, meaningful visual stimuli, such as the Arc Segment Attitude Reference (ASAR). The ASAR symbology represents an aircraft’s attitude. Experiment 1 examined participants’ performance while recalling and reporting various attitudes of ASAR symbology and a Gabor patch, which were briefly presented in the peripheral visual field. Performance was assessed for coordinate and categorical judgments at various display locations. The results were consistent with the horizontal-vertical anisotropy literature, which implies that performance would be better for stimuli placed on the horizontal meridian as compared to stimuli placed on the vertical …
Meta-Analysis Of Performance Characteristics Of Modern Database Schemas, Carter Grove
Meta-Analysis Of Performance Characteristics Of Modern Database Schemas, Carter Grove
Theses and Dissertations
Industry and academia alike are more commonly using databases as solutions to advanced and complex problems. Unfortunately, not all database schemas are created equal and can yield different advantages in different areas. To try to understand what database schema might be best suited for a user’s needs, we sought out to distinguish how databases are measured against each other, what their performance characteristics are, and what advantages each type of database inherently possesses. To allow for the ingestion of data across the five different categories of database schemas, we used a met-analysis of past literature and aggregated the data to …
Using Custom Ner Models To Extract Dod Specific Entities From Contracts, Kayla P. Haberstich
Using Custom Ner Models To Extract Dod Specific Entities From Contracts, Kayla P. Haberstich
Theses and Dissertations
The Air Force Sustainment Center collected 3.7 million contracts onto the Air Force Research Laboratory’s high power computers. They are in the format of a .pdf or scanned document, making them unstructured data. The Data Analytics Resource Team extracted the documents into a textual format for use in further analysis. This thesis looks to extract four DOD specific entities (NSN, Part Number, CAGE Code, and Supplier Name) from the contracts using custom NER models. This newly extracted information will allow the Air Force to identify what parts are supplied by which vendors. This information along with historical CLIN pricing for …
Combat Assessment For The Simulation Of Warfare, Benjamin L. Finch
Combat Assessment For The Simulation Of Warfare, Benjamin L. Finch
Theses and Dissertations
Military assessment seeks to answer two primary questions: "are we creating the effects that we desire?" and "are we accomplishing tasks to standard?" This thesis steps through several desirable characteristics for a simulated combat assessment methodology. After developing a value hierarchy from these characteristics, this thesis provides and evaluates several candidate methodologies for use within a combat simulation. Each alternative's evaluation is informed by its application to a small combat simulation. Upon recommending the use of Linear Programming, we utilize value-focused thinking to modify this alternative. The thesis terminates with some conclusory thoughts and ideas for future research.
Applying Model-Based Systems Engineering And Fidelity Quantification To Support Fair Fight In A Distributed Simulation System, Nathaniel Erbe, David Lemmer
Applying Model-Based Systems Engineering And Fidelity Quantification To Support Fair Fight In A Distributed Simulation System, Nathaniel Erbe, David Lemmer
Theses and Dissertations
Current 5th and 6th generation fighter aircraft capabilities, and the DoD's push towards digital engineering have created an environment in which simulated testing using live, virtual, and constructive assets has increasing utility. These simulations need to be credible in the eyes of the stakeholders, which for distributed simulation systems includes establishing fair fight between simulation services. Fair fight is when multiple simulations interoperate without generating one-sided systematic advantages. Issues that impede fair fight can be categorized into interoperability issues at the simulations implementation level and incompatible representations of reality between underlying models. This research used model-based systems engineering to generate …
Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom
Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom
Theses and Dissertations
Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used to …
Performance Improvement Through Better Understanding Of Supply Chain Resilience, Amanda L. Femano
Performance Improvement Through Better Understanding Of Supply Chain Resilience, Amanda L. Femano
Theses and Dissertations
Businesses operate every day in a disruptive environment. Supply and demand uncertainty, natural disasters, global pandemics, and mishaps can all cause chaos to a supply chain’s flow. It is impossible to predict every disruption a supply chain may encounter. The best an organization can do to protect network performance is to build resilience in the supply chain and life-blood of its operations. Ensuring that a supply chain has the proper built-in mechanisms to resist and recover from disruptions is referred to as Supply Chain Resilience (SCR). While it is generally agreed that SCR can be improved through the implementation of …
Collaborative All-Source Navigation With Integrity, Jonathon S. Gipson
Collaborative All-Source Navigation With Integrity, Jonathon S. Gipson
Theses and Dissertations
The novel ARMAS-SOM framework fuses collaborative all-source sensor information in a resilient manner with fault detection, exclusion, and integrity solutions recognizable to a GNSS user. This framework uses a multi-filter residual monitoring approach for fault detection and exclusion and is augmented with an additional "observability" EKF sub-layer for resilience. We monitor the a posteriori state covariances in this sub-layer to provide intrinsic awareness when navigation state observability assumptions required for integrity are in danger. This is used to selectively augment the framework with offboard information to preserve resilience. By maintaining split parallel collaborative and proprioceptive estimation instances and employing a …
Requirements Analysis And Architecture For An Operational Study Of Fatigue In Usaf Mobility Aircrew, Jonathan F. Mecham
Requirements Analysis And Architecture For An Operational Study Of Fatigue In Usaf Mobility Aircrew, Jonathan F. Mecham
Theses and Dissertations
Aircrew fatigue in flight operations is a known hazard that has driven the creation of fatigue-reducing regulation and fatigue risk management systems industry wide. In addition, biomathematical models have been created and tested to forecast the effectiveness of aircrew under conditions of time-zone shifts and long duty days. However, limited operational studies exist to validate these models or to help understand how individual factors can affect them. Operational studies have a variety of limitations that make gathering typical data regarding fatigue or sleep difficult. This research takes systems requirement analysis approach to design a study that measures effects of circadian …
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Theses and Dissertations
This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Theses and Dissertations
Clustering weather data is a valuable endeavor in multiple respects. The results can be used in various ways within a larger weather prediction framework or could simply serve as an analytical tool for characterizing climatic differences of a particular region of interest. This research proposes a methodology for clustering geographic locations based on the similarity in shape of their temperature time series over a long time horizon of approximately 11 months. To this end an emerging and powerful class of clustering techniques that leverages deep learning, called deep representation clustering (DRC), are utilized. Moreover, a time series specific DRC algorithm …
Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore
Interdependent Infrastructure Recovery Using Multilayered Networks And Optimization, Brigham A. Moore
Theses and Dissertations
Interdependent infrastructure recovery modeling and simulation are complicated due to various interdependent connections and complexities. Current efforts have identified both operational and restoration interdependency subtypes and coupling strategies that have not been integrated into one comprehensive model. This research presents a model which simultaneously integrates nine interdependency subtypes and four coupling strategies in a multi-objective format to provide the most tailorable and comprehensive network-based recovery model available. This research also created a defense-centric interdependent infrastructure database by modifying the existing CLARC database. This research then addressed assumptions regarding recovery work management in order to address the impact of work crew …
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
Theses and Dissertations
A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …
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 …
Developing A Basic Formal Supply Chain Ontology To Improve Communication And Interoperability, David Morrow
Developing A Basic Formal Supply Chain Ontology To Improve Communication And Interoperability, David Morrow
Theses and Dissertations
Information is crucial to supply chain performance because it is used to make decisions and trigger actions. Organizations across world-class supply chains increasingly use information technology to analyze and process supply chain data. However, supply chain management lacks a common language, making information exchange difficult. An ontology can provide a standardized framework that organizes a given knowledge domain. This research proposes a common language for developing a supply chain ontology that can be built into a basic formal ontology understood by both humans and computers. According to current research, an established and widely used supply chain framework is a good …
Examining The Influence Of Source Dependence On Supplier Performance In The Usaf Organic Supply Chain, Thomas A. Counter
Examining The Influence Of Source Dependence On Supplier Performance In The Usaf Organic Supply Chain, Thomas A. Counter
Theses and Dissertations
The purpose of this study is to examine the U.S. Air Force's dependence toward sole sourcing and how that influences procurement outcomes in terms of supplier performance. This research used linear regression to explain the effect of source dependence and supplier size on performance categories for 326 suppliers. The five supplier performance categories in the study included timeliness, cost control, quality, business relations, and regulatory compliance. The research found that the USAFs dependence on sole sourcing had a small but statistically significant influence on all five aspects of supplier performance, with timeliness being the most adversely impacted.
Applying A Statistical Approach To Develop A Sustainable Technology For Capturing Phosphorous From An Agricultural Tile Drainage System Using By-Product Phosphorous Sorbing Materials (Psm), Amir Kordijazi
Theses and Dissertations
Due to nutrient pollution, agriculture is one of the major sources of pollution in water bodies. Every time it rains, fertilizers, pesticides, and animal waste wash nutrients and pathogens—such as bacteria and viruses—into waterways. As rainfall increases due to climate change, the water problem will worsen. One of the nutrients that extensively contributes to the degradation of water quality is phosphorous (P). In this research, the performance of electric arc furnace (EAF) steel slag was investigated as a P sorbing materials (PSM) according to the conditions present in a P removal structure designed for treating water discharge from an agricultural …