Engineering Commons^™

Valorization Of Xylan In Agroforestry Waste Streams, Harrison Appiah

Graduate Theses, Dissertations, and Problem Reports

Valorization of Xylan in Agroforestry Waste Streams.

Harrison Appiah

Microwave-assisted deep eutectic solvent and gamma-valerolactone metallic chloride catalyzed conversion of xylan to furfural were investigated using a 2x3 factorial experimental design at two levels of percent microwave power, reaction time, and catalyst concentration. The levels of each factor studied were (20%, 60% microwave power, 2, 4 minutes, and 10, 20mg) respectively. The effect of three metallic chloride catalysts (LiCl, FeCl3.6H20, CuCl2) on the conversion of xylan to furfural was also investigated. The gamma-valerolactone-ferric chloride sent system exhibited the highest mean yield of furfural (56.50%). The next highest furfural yield of …

Improving Deep Learning Models In Weakly Supervised Learning Paradigms, Fariborz Taherkhani

Graduate Theses, Dissertations, and Problem Reports

Convolutional Neural Networks (CNNs) have provided promising achievements for image classification problems. However, training a CNN model relies on a large number of labeled data. Considering the vast amount of unlabeled data available on the web, it is important to make use of these data in conjunction with a small set of labeled data to train a deep learning model. In this thesis, we aim to develop some methods that can make use of unlabeled data along with partially labeled data to obtain a better generalization performance for CNN models. Moreover, it is also often easier to collect labels that …

Various Operational Aspects Of The Extraction Of Critical Minerals From Acid Mine Drainage And Its Treatment By-Product, Zhongqing Xiao

Graduate Theses, Dissertations, and Problem Reports

Acid mine drainage (AMD) is environmentally hazardous acidic water, which is continuously generated in large volumes at coal mining sites, typically when pyrite is exposed to oxygen and water. As its continuous migration under the geologic conditions, AMD tends to leach metal elements out from the surrounding minerals, leading to high concentrations of metal elements, like iron, aluminum, magnesium, manganese, lead, arsenic, as well as critical cobalt and rare earth elements (REEs). AMD must be treated and monitored to meet the effluent limits, under U.S.C §1251, the Clean Water act, before being discharged to receiving streams.

Recently, the research is …

Evaluation Of Various Separation Techniques For The Removal Of Actinides From A Rare Earth-Containing Solution Generated From Coarse Coal Refuse, Deniz Talan

Graduate Theses, Dissertations, and Problem Reports

Rare earth elements have emerged as a vital commodity due to their significance in the production of high-tech devices as well as their utilization in defense and military systems. They are deemed critical due to potential scarcity, supply constraints, and the lack of minable concentrations. Therefore, alternative sources are needed to meet the demand and continue manufacturing rare earth-required products. Coal and coal by-products, in that regard, have presented a significant opportunity and proven to contain a considerable amount of rare earths. However, toxic elements such as thorium and uranium are frequently seen in the same mineralization as rare earths. …

Integration Of Deep Hashing And Channel Coding For Biometric Security And Biometric Retrieval, Veeru Talreja

Graduate Theses, Dissertations, and Problem Reports

In the last few years, the research growth in many research and commercial fields are due to the adoption of state of the art deep learning techniques. The same applies to even biometrics and biometric security. Additionally, there has been a rise in the development of deep learning techniques used for approximate nearest neighbor (ANN) search for retrieval on multi-modal datasets. These deep learning techniques knows as deep hashing (DH) integrate feature learning and hash coding into an end-to-end trainable framework. Motivated by these factors, this dissertation considers the integration of deep hashing and channel coding for biometric security and …

Process Modeling And Techno-Economic Analysis Of Micro- Encapsulated Carbon Sorbents (Mecs) For Co2 Capture In A Fixed Bed And Moving Bed Reactors, Goutham Kotamreddy

Graduate Theses, Dissertations, and Problem Reports

Carbon capture, utilization, and storage (CCUS) is seen as a suite of technologies to curb the carbon dioxide emissions from the atmosphere and plays a crucial role to meet the net zero emissions target for many countries by 2050. One of the major sources for CO₂ emissions is combustion of fossil fuels. Various innovative capture technologies are being explored because the state-of-the-art monoethanolamine (MEA) based carbon capture technology has drawbacks such as corrosion, energy penalty. There are several potential solvents that have lower energy penalty, but they are highly viscous or may turn into solid phase in the absorber …

Sustainability Assessment Of Direct Energy Deposition (Ded) Based Hybrid Manufacturing Using Life Cycle Assessment (Lca) Method, Faujia Islam

Graduate Theses, Dissertations, and Problem Reports

As sustainability has emerged as a highlight for almost every field over the last few decades, the manufacturing field is no exception. Generally, additive manufacturing performs better than traditional manufacturing in terms of sustainability because of its lean energy- and material usage. Previous studies have compared the sustainability performance between traditional and additive manufacturing, but hybrid manufacturing was not focused upon much. In this paper, the life cycle assessment method is used to analyze and compare the energy consumption and environmental impact of direct energy deposition (DED) based hybrid manufacturing and traditional manufacturing “CNC milling” process for a turbine blade. …

The Effect Of Natural Fractures On The Mechanical Behavior Of Limestone Pillars: A Synthetic Rock Mass Approach Application, Mustafa Can Süner

Graduate Theses, Dissertations, and Problem Reports

In general, underground limestone mines have inherently strong rock and experience good ground stability. Also, modern pillar design guidelines developed by National Institute for Occupational Safety and Health (NIOSH) have improved the design of stable layouts for modern limestone mines. However, ground control-related incidents are still an important problem. In underground limestone mines, previously mined sections stay open for the life of the mine which may be many years, and it is possible for travel ways to working faces to pass through these old sections. In a recent massive pillar collapse in an old section of a mine in Pennsylvania …

Determination Of Effectiveness Of Energy Management System In Buildings, Vivash Karki

Graduate Theses, Dissertations, and Problem Reports

Building Energy Management Systems (BEMS) are computer-based systems that aid in managing, controlling, and monitoring the building technical services and energy consumption by equipment used in the building. The effectiveness of BEMS is dependent upon numerous factors, among which the operational characteristics of the building and the BEMS control parameters also play an essential role. This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS. The simulation tool gives the user the flexibility to understand the potential energy savings by employing specific BEMS control and help …

Prediction Of Tensile Behaviors Of L-Ded 316 Stainless Steel Parts Using Machine Learning, Israt Zarin Era

Graduate Theses, Dissertations, and Problem Reports

Directed energy deposition (DED) is a rising field in the arena of metal additive manufacturing and has extensive applications in aerospace, medical and rapid prototyping. The process parameters, such as laser power, scanning speed and specimen height, play a great deal in controlling and affecting the properties of DED fabricated parts. Nevertheless, both experimental and simulation methods have shown constraints and limited ability to generate accurate and efficient computational predictions on the correlations between the process parameters and the final part quality. In this work, a data driven machine learning model XGBoost has been built and applied to predict the …

Analysis On Combined Heat And Power, And Combined Heat And Power Hybrid Systems For Unconventional Drilling Operations, Diego G. Dranuta Ferrer

Graduate Theses, Dissertations, and Problem Reports

The United States (U.S.) has experienced a natural gas “boom” due to the development of unconventional shale plays, but well development is energy intensive. Operations use electric drilling rigs typically powered by either three high-horsepower diesel engines (HHPDE) or three dedicated natural gas engines (DNGE) and associated generators. From a first law analysis, HHPDEs peak at 42% efficiency at full load, while DNGE peak at about 30%. Most of the fuel energy is lost as heat rejected by the exhaust and radiators. Concurrently, during cold seasons rigs utilize boilers to provide steam throughout the rig to prevent freezing and provide …

Next-Generation Re-Entry Aerothermodynamic Modeling Of Space Debris Using Machine Learning, Nicholas Sia

Graduate Theses, Dissertations, and Problem Reports

The number of resident space objects re-entering the atmosphere is expected to rise with increased space activity over recent years and future projections. Predicting the survival and impact location of the medium to large sized re-entering objects becomes important as they can cause on ground casualties and damage to property. Uncertainties associated with the re-entry process makes necessary a probabilistic approach, which can be computationally expensive when using high-fidelity numerical methods for estimating aerothermodynamic properties. To date, object-oriented analysis is the dominant tool used for atmospheric re-entry modeling and simulation, where aerothermodynamic coefficients are used to determine the risk a …

Transform Based Approaches For The Detection Of Astrophysical Signals, Marwan Mahfud Alkhweldi

Graduate Theses, Dissertations, and Problem Reports

Development of new algorithms for the detection of isolated astrophysical pulses is of interest to radio astronomers. Both Fast Radio Bursts (FRBs) and several Rotating Radio Transients (RRATs) were detected through the application of a single pulse search algorithm. The conventional approach to detect astronomical pulses requires an exhaustive search for the correct dispersion measure. Its accelerated versions involve signal processing in Fourier transform space.

In this dissertation, we present several new transform-based approaches for the detection and analysis of astrophysical signals with the latest being the most effective and advanced of all. It is implemented in several steps. First, …

Multivariate Time Series Classification Of Sensor Data From An Industrial Drying Hopper: A Deep Learning Approach, Md Mushfiqur Rahman

Graduate Theses, Dissertations, and Problem Reports

In recent years, the advancement of industry 4.0 and smart manufacturing has made a large number of industrial process data attainable with the use of sensors installed in the machineries. This thesis proposes an experimental predictive maintenance framework for an industrial drying hopper so that it can detect any unusual event in the hopper which reduces the risk of erroneous fault diagnosis in the manufacturing shop floor. The experimental framework uses Deep Learning (DL) algorithms in order to classify Multivariate Time Series (MTS) data into two categories- failure or unusual events and regular events, thus formulating the problem as binary …

Evaluating Social Media As A Medium Of Private Communication Through Steganographic Images, Kendall Weldon Coles

Graduate Theses, Dissertations, and Problem Reports

Social media is a vastly used communication tool with billions of users worldwide. These social networks provide users the ability to share their ideas and thoughts through the messages, videos, and images that they post. The images that are shared can possibly be embedded with private messages through the use of a steganographic tool. The messages are embedded in a fashion that doesn’t change the visual appearance of an image. This allows for these types of images to hide in plain sight, which creates the possibility of someone communicating privately in a public social media setting. This project proved how …

Deep Models For Improving The Performance And Reliability Of Person Recognition, Sobhan Soleymani

Graduate Theses, Dissertations, and Problem Reports

Deep models have provided high accuracy for different applications such as person recognition, image segmentation, image captioning, scene description, and action recognition. In this dissertation, we study the deep learning models and their application in improving the performance and reliability of person recognition. This dissertation focuses on five aspects of person recognition: (1) multimodal person recognition, (2) quality-aware multi-sample person recognition, (3) text-independent speaker verification, (4) adversarial iris examples, and (5) morphed face images. First, we discuss the application of multimodal networks consisting of face, iris, fingerprint, and speech modalities in person recognition. We propose multi-stream convolutional neural network architectures …

Application Of 3d Seismic Signal And Geomechanical Attributes For Subsurface Fracture Characterization: A Case Study In Clearfield County, Central Pennsylvania, Iman F. Zulkapeli

Graduate Theses, Dissertations, and Problem Reports

Hydrocarbon exploration in unconventional reservoirs is highly risky due to the nature of the reservoirs and the variability in fractures and reservoir geomechanical properties in the subsurface. The reservoir needs to be fully characterized to avoid any complication such as frac hit, wellbore failure, blowout, or even a dry hole. The Clearfield reservoir produces an exceptionally low amount of gas, compared to the neighboring region in the proximity, which has been poorly understood. This raises the question as to what causes the reservoir to have low productivity.

This study focuses on the natural fracture characterization using high-quality 3D seismic signal …

Increasing The Reliability Of Software Systems On Small Satellites Using Software-Based Simulation Of The Embedded System, Matthew D. Grubb

Graduate Theses, Dissertations, and Problem Reports

The utility of Small Satellites (SmallSats) for technology demonstrations and scientific research has been proven over the past few decades by governments, universities, and private companies. While the research and technology demonstration objectives that can be provided by these SmallSats are becoming similar to larger spacecraft, their reliability still falls behind. This is in part due to the reduced cost of SmallSat missions in comparison to large spacecraft, which requires cheaper components, rapid development schedules, and accepted risk. In these missions, the importance of the flight software is often overlooked, and the software is rushed through development and not fully …

The Role Of Structure Evolution For Prbaco2o6-Δ In Oxygen Reduction Reaction Kinetics At Sofc Cathode, Nan Zhang

Graduate Theses, Dissertations, and Problem Reports

Mixed ion and electron conductive materials especially those with perovskite-related structures have been widely used as cathode and anode of solid oxide fuel cells (SOFC). Double perovskite LnBaCo₂O_6-δ (Ln=Pr, Nd, Sm, Nd, Y) cathodes have been shown better performance than single perovskite Ln_0.5Ba_0.5CoO_3-δ in SOFC cathode studies. However, the effect of different double perovskite phases on oxygen transport properties has not been investigated. In this study, the electrochemical performance of different double perovskite materials PrBaCo₂O_6-δ (PBCO), NdBaCo₂O_6-δ (NBCO), YBaCo₂O_6-δ (YBCO), and single perovskite …

Touching Light: A Framework For The Facilitation Of Music-Making In Mixed Reality, Ian Thomas Riley

Graduate Theses, Dissertations, and Problem Reports

Drawing upon the historical development of analog and digital technologies alongside the proliferation of computer-assisted performance practices, this research seeks to develop a framework for integrating Mixed Reality applications to live musical performance, specifically through the creation of a Microsoft HoloLens 2 Mixed Reality application in order to facilitate a live performance of an original musical composition for percussion and real-time Mixed Reality environment. Mixed Reality enables a performer to interact with virtual (holograms, VSTs, etc.) and physical (vibraphone, tuned drums, microphones, etc.) objects simultaneously. Tandem to the development of the conceptual framework was the composition of an original score …

Floating-Gate Design And Linearization For Reconfigurable Analog Signal Processing, Steven Michael Andryzcik Ii

Graduate Theses, Dissertations, and Problem Reports

Analog and mixed-signal integrated circuits have found a place in modern electronics design as a viable alternative to digital pre-processing. With metrics that boast high accuracy and low power consumption, analog pre-processing has opened the door to low-power state-monitoring systems when it is utilized in place of a power-hungry digital signal-processing stage. However, the complicated design process required by analog and mixed-signal systems has been a barrier to broader applications. The implementation of floating-gate transistors has begun to pave the way for a more reasonable approach to analog design. Floating-gate technology has widespread use in the digital domain. Analog and …

Dynamic Modelling And Control Of Grid-Level Energy Storage Systems, Sai Pushpitha Vudata

Graduate Theses, Dissertations, and Problem Reports

The focus of this work is on two energy storage technologies, namely pumped storage hydroelectricity (PHS) and secondary batteries. Under secondary battery technologies, two potential technologies for grid-scale storage, namely high-temperature sodium-sulfur (NaS) battery and vanadium redox flow battery (VRFB), are investigated. PHS is a largescale (>100 MW) technology that stores and generates energy by transporting water between two reservoirs at different elevations. The goal is to develop a detailed dynamic model of PHS and then design the controllers to follow the desired load trajectory accurately with high efficiency. The NaS battery and VRFB are advanced secondary batteries which …

Application Of Artificial Intelligence In Three Phase Unbalanced Smart Power Distribution Grid, Deepak Tiwari

Graduate Theses, Dissertations, and Problem Reports

Electrification of the transportation sector can play an essential role in curbing fossil fuel scarcity and oil shortages in the world. Electric vehicles (EVs) can significantly reduce CO2 emissions, improve urban pollution. Apart from these advantages of EVs, they may also pose challenges to the distribution grid. Increasing penetration of EVs puts an extra burden and leads to affect the grid severely. Load congestions, voltage drops/regulation, overloading are some of the issues that might incur in the grid because of improper charging of EVs. The uncertain nature of EV owners makes it very difficult to predict the charging pattern. So …

Sustainability Key Performance Indicators For Mass Customization, Md Fahid Hasan Pulak

Graduate Theses, Dissertations, and Problem Reports

Today’s manufacturers are striving towards a more sustainable and customized product offering in their value chain to satisfy customer demand and compete on the marketplace. By adopting sustainability practices, companies are not only complying with environmental regulations but are strategically addressing the triple bottom line (TBL) of sustainability (environmental, social, and economic). Similarly, mass customization allows a company to better satisfy their customers by creating individualized products economically. Moving forward, it is important to better understand the relationship of these two competitive strategies. In order to assess the sustainability performance of mass customization, it is important to understand the appropriate …

Natural Gas Conversion To Value-Added Chemicals By Microwave Catalytic Processes, Brandon Robinson

Graduate Theses, Dissertations, and Problem Reports

Ethane is the second-largest component in natural gas and is typically separated out to minimize condensation in the pipelines. The technical difficulties and cost associated with the transportation and the storage of ethane have led companies to start burning natural gas to produce power or flaring which attributes to the global CO₂ emission problem. The conversion of ethane to higher-value liquid products is of increasing importance so that the natural gas can be safely utilized and cost-effectively transported. Existing commercial technologies used to convert ethane to liquid chemical products are typically based on the indirect syngas route, such as …

Multimodel Operability Framework For Design Of Modular And Intensified Energy Systems, Vitor Gazzaneo

Graduate Theses, Dissertations, and Problem Reports

In this dissertation, a novel operability framework is introduced for the process design of modular and intensified energy systems that are challenged by complexity and highly constrained environments. Previously developed process operability approaches are reviewed and further developed in terms of theory, application, and software infrastructure. An optimization-based multilayer operability framework is introduced for process design of nonlinear energy systems. In the first layer of this framework, a mixed-integer linear programming (MILP)-based iterative algorithm considers the minimization of footprint and achievement of process intensification targets. Then, in the second layer, an operability analysis is performed to incorporate key features of …

Dynamic Optimization Algorithms For Baseload Power Plant Cycling Under Variable Renewable Energy, Rebecca Hyen Hae Kim

Graduate Theses, Dissertations, and Problem Reports

The growing deployment of variable renewable energy (VRE) sources, such as wind and solar, is mainly due to the decline in the cost of renewable technologies and the increase of societal and cultural pressures. Solar and wind power generation are also known to have zero marginal costs and fuel emissions during dispatch. Thereby, the VRE from these sources should be prioritized when available. However, the rapid deployment of VRE has heightened concerns regarding the challenges in the integration between fossil-fueled and renewable energy systems. The high variability introduced by the VRE as well as the limited alignment between demand and …

Deep Learning Architectures For Heterogeneous Face Recognition, Seyed Mehdi Iranmanesh

Graduate Theses, Dissertations, and Problem Reports

Face recognition has been one of the most challenging areas of research in biometrics and computer vision. Many face recognition algorithms are designed to address illumination and pose problems for visible face images. In recent years, there has been significant amount of research in Heterogeneous Face Recognition (HFR). The large modality gap between faces captured in different spectrum as well as lack of training data makes heterogeneous face recognition (HFR) quite a challenging problem. In this work, we present different deep learning frameworks to address the problem of matching non-visible face photos against a gallery of visible faces.

Algorithms for …

Static And Dynamic Analysis Of Composite Plates Using The Monna Finite Element, Mohamed Omar

Graduate Theses, Dissertations, and Problem Reports

Composite materials are replacing metals in many fields due to their favorable qualities such as strength-to-weight ratio, fatigue characteristics, and corrosion resistance. An efficient, versatile, and accurate composite plate element applicable to the dynamic analysis of composite plates would help the advancement of composites tremendously.

The objective of this research is to analyze composite plates using the classical laminated plate theory (CLPT), first-order deformation theory (FSDT), and higher-order deformation theory (HSDT) with the applicable finite element modeling (FEM) for each theory. This thesis investigates which theory is more efficient and accurate and evaluates the benefits of using an h-p-version …

Development Of Thermal Management Strategies Using Cylinder Deactivation For Low-Load Operation In Heavy-Duty Diesel Trucks, Christian M. Hushion

Graduate Theses, Dissertations, and Problem Reports

Cylinder deactivation (CDA) has been used in gasoline engines, for decades, as a strategy for fuel consumption reduction. The idea of CDA in the heavy-duty diesel (HDD) engine sector has gained traction as a pathway to fuel efficient thermal management strategy. Oxides of nitrogen (NOx) control has been a major focus over the last decade and maintaining conducive aftertreatment temperatures is a major design aspect. HDD original equipment manufacturers (OEM) have developed a variety of thermal management strategies which almost all revolve around large fuel penalties. The goal of all of these strategies is for thermal management of the diesel …