Engineering Commons^™

The Effect Of Green Biobased Binder On Structural, Mechanical, Liquid Absorption And Wetting Properties Of Coated Papers, Bilge N. Altay, Charles Klass, Ting Chen, Alexandar Fleck, Cem Aydemir, Arif Karademir, Paul D. Fleming

Articles

Synthetic styrene-butadiene (SB) and styrene-acrylic (SA) latex binders used in paper coating formulations are common and based on unsustainable petroleum sources. Today's papermaking industry turns towards sustainable substitutes that do not compromise quality, and reduce carbon emission, toxic substance release and waste disposal concerns related to fossil fuel sources. In this study, colloidal starch-based latex nanoparticles that do not require cooking were used for pigment coating and coated on the paper surfaces. The effects of these new biobased binders on the structural and mechanical strength properties, liquid absorption, wetting and surface topography of the paper were investigated and compared with …

Optimal Feature Learning For Facial Expression Recognition, Kamran Ali

Electronic Theses and Dissertations, 2020-2023

A great deal of research has been done to improve the performance of Facial Expression Recognition (FER) algorithms, but extracting optimal features to represent expressions remains a challenging task. The biggest drawback is that most work on FER ignores the inter-subject variations in facial attributes of individuals present in data. Hence, the representation extracted for the recognition of expressions is polluted by identity-related features that negatively affect the generalization capability of a FER technique on unseen identities. To overcome the effect of subject-identity bias, previous research shows the effectiveness of extracting identity-invariant expression features for FER. However, most of those …

Study Of Mos2/High-K Interface And Implementation Of Mos2 Based Memristor For Neuromorphic Computing Applications, Durjoy Dev

Electronic Theses and Dissertations, 2020-2023

The scientific world is witnessing an unprecedented triumph of artificial neural network (ANN)- a computing system inspired by the biological neural network. With the enthralling quest for Internet of Everything (IoE), it is expected to have an unparalleled dominance of ANN in our day-to-day life. In recent times, memristor has come as an emerging candidate to realize ANN through emulating biological synapse and neuron behavior. Molybdenum disulfide (MoS2), one well-known two-dimensional (2D) transition metal dichalcogenides (TMDCs), has drawn interest for high speed, flexible, low power electronic devices since it has a tunable bandgap, reasonable carrier mobility, high Young's modulus, and …

Effect Of Various Speed Management Strategies On Bicycle Crashes For Urban Roads In Central Florida, Jorge Ugan

Electronic Theses and Dissertations, 2020-2023

In recent years, cycling has become an increasingly popular transportation mode around the world. In contrast to other popular modes of transportation, cycling is more economic and energy efficient. While many studies have been conducted for the bicycle safety analysis, most of them were limited in terms of bicycle exposure data and on-street data. This study tries to improve the current safety performance functions for bicycle crashes at urban corridors by utilizing crowdsource data from STRAVA and on-street speed management strategies data. Speed management strategies are any roadway alterations that causes a change in motorists' driving behavior. In Florida, these …

Spectral Dependence Of Deep Subwavelength Metallic Apertures In The Mid-Wave Infrared, Heath Gemar

Electronic Theses and Dissertations, 2020-2023

For two decades, extraordinary optical transmission (EOT) has amplified exploration into subwavelength systems. Researchers have previously suggested exploiting the spectrally selective electromagnetic field confinement of subwavelength cavities for multispectral detectors. Utilizing the finite-difference frequency domain (FDFD) method, we examine electromagnetic field confinement in both 2-dimensional and 3-dimensional scenarios from 2.5 to 6 microns (i.e., mid-wave infrared or MWIR). We explore the trade space of deep subwavelength cavities and its impact on resonant enhancement of the electromagnetic field. The studies provide fundamental understanding of the coupling mechanisms allowing for prediction of resonant spectral behavior based on cavity geometry and material properties. …

Decision Tool For Prioritizing Bridge Repair Or Replacement, Nyoka Amy Florius

Civil Engineering Dissertations - Archive

Bridges are typically damaged/deteriorated due to various factors that require close evaluation to make informed decisions about repair/replacement. There are several aspects of study to evaluate bridges for repair/replacement, such as age, structural adequacy, and frequent usage. Further, bridges which are in poor condition must be identified to mitigate their damage/deterioration and as a result, maintain a safe environment for users. Therefore, to assess the need for funding, state Departments of Transportation are required to evaluate bridges by considering several factors, while prioritizing safety. In Texas, the Highway Bridge Program is responsible for funding bridges which are listed for repair/replacement. …

Improving Probabilistic Quantitative Precipitation Forecasting Using Machine Learning And Statistical Postprocessing Methods, Mohammadvaghef Ghazvinian

Civil Engineering Dissertations - Archive

The objective of this research is to address the limitations inherent in conventional statistical postprocessing schemes to generate probabilistic quantitative precipitation forecasts (PQPFs) and improve postprocessed PQPFs quality through introducing new robust statistical models and machine learning frameworks. This dissertation comprises three main elements. First, a new, two-part scheme for creating PQPFs from single-valued quantitative precipitation forecasts is introduced. This scheme, herein referred to as the Mixed-type Non-Homogenous Regression (MNHR), combines the use of logistic regression for estimating rainfall intermittency, and non-homogeneous regression for estimation of additional parameters of the conditional distribution. The performance of MNHR is evaluated relative to …

Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin

All Dissertations

Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …

Understanding Process-Structure-Property-Performance Relationships Of Thermoplastic Olefins (Tpo) Foams Through A Novel Manufacturing To Response Pathway, Sai Aditya Pradeep

All Dissertations

The global transportation industry is the second highest contributor to climate change. As a result, there has been a concerted effort to spearhead research in economical lightweighting technologies, as every 10 % reduction in weight will lead to to 6 – 8 % improvement in fuel efficiency. Additionally, the recent push for electrification and the emphasis on Corporate Average Fuel Economy (CAFE) standards have seen original equipment manufacturers (OEM’s) dive into lightweighting of materials to improve overall range and/or fuel-efficiency. Thermoplastic Olefins (TPOs) have in recent years carved out a niche in the automotive industry due to advantages such as …

Deep Learning-Guided Prediction Of Material’S Microstructures And Applications To Advanced Manufacturing, Jianan Tang

All Dissertations

Material microstructure prediction based on processing conditions is very useful in advanced manufacturing. Trial-and-error experiments are very time-consuming to exhaust numerous combinations of processing parameters and characterize the resulting microstructures. To accelerate process development and optimization, researchers have explored microstructure prediction methods, including physical-based modeling and feature-based machine learning. Nevertheless, they both have limitations. Physical-based modeling consumes too much computational power. And in feature-based machine learning, low-dimensional microstructural features are manually extracted to represent high-dimensional microstructures, which leads to information loss.

In this dissertation, a deep learning-guided microstructure prediction framework is established. It uses a conditional generative adversarial network (CGAN) …

An Algorithm For Biobjective Mixed Integer Quadratic Programs, Pubudu Jayasekara Merenchige

All Dissertations

Multiobjective quadratic programs (MOQPs) are appealing since convex quadratic programs have elegant mathematical properties and model important applications. Adding mixed-integer variables extends their applicability while the resulting programs become global optimization problems. Thus, in this work, we develop a branch and bound (BB) algorithm for solving biobjective mixed-integer quadratic programs (BOMIQPs). An algorithm of this type does not exist in the literature.

The algorithm relies on five fundamental components of the BB scheme: calculating an initial set of efficient solutions with associated Pareto points, solving node problems, fathoming, branching, and set dominance. Considering the properties of the Pareto set of …

A Pipeline For Enhanced Multimodal 2d Imaging Of Concrete Structures, Sina Mehdinia, Thomas Schumacher, Xubo Song, Eric A. Wan

Civil and Environmental Engineering Faculty Publications and Presentations

We present an imaging pipeline to achieve enhanced images of the interior of concrete from ground penetrating radar (GPR) and ultrasonic echo array (UEA) measurements. This work lays the foundation for an advanced yet practical imaging tool to assess concrete structures. Specifically, we propose an enhanced two-dimensional (2D) total focusing method (XTFM) to reconstruct images from raw GPR and UEA data. The proposed XTFM algorithm integrates total focusing method (TFM) and synthetic aperture focusing technique (SAFT) concepts to post-process large independent and interelement measurements from both modalities in a computationally efficient way. Furthermore, we introduce a novel 2D image fusion …

Collective Motion In Pelotons And Fish Schools: Observation And Modeling, Syed Rafid Rahman

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In recent years there has been a sharp increase in deriving inspiration from nature for engineering applications. However there has been lack of high-resolution data from which insights into collective behavior can be drawn and models can be validated. In this imaging based thesis, data from high-speed, overhead cameras, and GPS tracking are used to collect position and sensory data for large groups of 40 or more members. These data helps us understand how different members (fish, cyclists) of a group interact with each other in collective motion. The focus of this work is to find how individual behavior leads …

Towards Automation Of Aluminum Cell Ramming Process, Maryam Salem Abdelfattah Mohamed Alkaabi

Theses

Newly installed cathode blocks in an aluminium reduction cell, expand due to a rapid increase of temperature when passing a high current at the start-up of the cell. High thermal stresses may result if cathode blocks are lined without gaps, and this can lead to cracking of the cathodes and failure of the cell. On the other hand, leaving gaps would cause failure due to molten metal infiltration in the gaps. To overcome these problems carbon-based ramming material is used to fill these gaps. Currently ‘Filling’ is carried out manually or partially automated, but this needs to be fully automated …

Immobilized Lipase On Zif For Enhanced Biofuel Production, Reem Mohammed Al Mansouri

Theses

Enzymatic transesterification of triglycerides to produce biodiesel has been gaining increasing attention owing to its advantages over chemical processes. Being catalysts, enzymes are not consumed during the processes in which they are used. Therefore, a successful technique to allow their repeated use can significantly enhance the economic feasibility of the process. The most common approach to allow easy separation of the enzymes and to eliminate their wastage is immobilization on a support matrix. Recently, Metal-Organic Frameworks (MOFs) have been suggested as preferable support for enzyme immobilization, owing to their high-order structure and high porosity and specific surface area. This thesis …

The Impact Of Wastewater Chemistry And Flow Characteristics On Hydrogen Sulfide Concentration, Mohsina Muhammed Sherief

Theses

Hydrogen sulfide (H₂S) is a naturally occurring, highly toxic gas that is formed from the decomposition of sulfur compounds. At low concentrations, H₂S is an irritant for the eyes, respiratory and gastrointestinal tract. At higher H₂S concentrations, it produces neurological impairment with dizziness, headache, and loss of consciousness. Mortality was reported to reach 6 percent following exposure to elevated concentrations. H₂S is generated in different industrial processes. In wastewater collection and treatment plants, H₂S is a common source of concrete and metal corrosion that has resulted in huge economic loss. …

Minimization Of The Weld Distortion By Weld Sequence Optimization Using Artificial Intelligence, Jeyaganesh Devaraj

Theses

The application of dissimilar metal welding processes is increasing nowadays in the automobile, aerospace, marine industry as they not only serve for joint welding for different metals but also assist in repairing and reworking in a simplified manner. Study on optimization of weld parameter to weld a structure is important to have control over the distortion, mass deposition, tensile strength, etc. The present research reports the development and implementation of the Genetic algorithm integrated Artificial Neural Network (GANN) based weld sequence optimization for reducing deformation of dissimilar metal joining using the hot-encode technique. Gas Metal Arc Welding (GMAW) is used …

Split-Horizon Dual-Stage Dispatch Scheme For A Standalone Microgrid, Aslam Amir

Theses

The advent of microgrids has prompted plenty of studies into its design, control, protection, and implementation, with several operational as well as pilot systems being commissioned worldwide. This necessitates the development of hardware and software for the Energy Management System, the supervisory controller in a microgrid. Hence, this thesis provides a novel dual-stage dispatch scheme for the Energy Management System of a Standalone microgrid by “splitting” the dispatch time horizon into four equal quarters to facilitate better usage of power forecast accuracies. The two stages include Unit Commitment/Scheduling and Economic Dispatch for the dispatchable Distributed Energy Resources based on renewable …

Numerical Green's Function-Based Method For Modeling Radiated Emission From Pcbs In Shielding Enclosures, Zi An Wang, Li (Lijun) Jun Jiang, Jun Fa Mao, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

Due to stringent electromagnetic compatibility (EMC) regulations, all electronic devices need to go through rigorous radiated emission tests before launching to market. Thus, efficient, accurate, and cheap characterization approaches are quite of interest. Instead of utilizing the time-consuming and expensive direct far-field measurement, in this work, a novel methodology on the basis of numerical Green's function (NGF) is proposed to acquire the parasitic EM emissions from PCBs placed in a shielding enclosure with ventilation slots. Referring to Schelkunoff's equivalence principle, the whole modeling procedure can be decomposed into two steps in order to obtain the emissions in the entire space. …

Frequency Domain Measurements Of Melt Pool Recoil Force Using Modal Analysis, Tristan Cullom, Cody Lough, Nicholas Altese, Douglas A. Bristow, Robert G. Landers, Ben Brown, For Full List Of Authors, See Publisher's Website.

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Recoil pressure is a critical factor affecting the melt pool dynamics during Laser Powder Bed Fusion (LPBF) processes. Recoil pressure depresses the melt pool. When the recoil pressure is low, thermal conduction and capillary forces may be inadequate to provide proper fusion between layers. However, excessive recoil pressure can produce a keyhole inside the melt pool, which is associated with gas porosity. Direct recoil pressure measurements are challenging because it is localized over an area proportionate to the laser spot size producing a force in the mN range. This paper reports a vibration-based approach to quantify the recoil force exerted …

2d Layered Sip As Anisotropic Nonlinear Optical Material, Huseyin Sar, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Two-dimensional (2D) material of silicon phosphide (SiP) has recently been shown as a promising optical material with large band gap, fast photoresponse and strong anisotropy. However, the nonlinear optical properties of 2D SiP have not been investigated yet. Here, the thickness-dependent in-plane anisotropic third-harmonic generation (THG) from the mechanically exfoliated 2D layered SiP flakes is reported. The crystal orientation of the SiP flake is determined by the angle-resolved polarized Raman spectroscopy. The angular dependence of the THG emission with respect to the incident linear polarization is found to be strongly anisotropic with the two-fold polarization dependence pattern. Furthermore, the effect …

Naturally Occurring Layered Mineral Franckeite With Anisotropic Raman Scattering And Third-Harmonic Generation Responses, Ravi P. N. Tripathi, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vertically stacked van der Waals (vdW) heterostructures have introduced a unique way to engineer optical and electronic responses in multifunctional photonic and quantum devices. However, the technical challenges associated with the artificially fabricated vertical heterostructures have emerged as a bottleneck to restrict their proficient utilization, which emphasizes the necessity of exploring naturally occurring vdW heterostructures. As one type of naturally occurring vdW heterostructures, franckeite has recently attracted significant interest in optoelectronic applications, but the understanding of light-matter interactions in such layered mineral is still very limited especially in the nonlinear optical regime. Herein, the anisotropic Raman scattering and third-harmonic generation …

Anisotropic Optical Responses Of Layered Thallium Arsenic Sulfosalt Gillulyite, Ravi P. N. Tripathi, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Multi-element two-dimensional (2D) materials hold great promise in the context of tailoring the physical and chemical properties of the materials via stoichiometric engineering. However, the rational and controllable synthesis of complex 2D materials remains a challenge. Herein, we demonstrate the preparation of large-area thin quaternary 2D material flakes via mechanical exfoliation from a naturally occurring bulk crystal named gillulyite. Furthermore, the anisotropic linear and nonlinear optical properties including anisotropic Raman scattering, linear dichroism, and anisotropic third-harmonic generation (THG) of the exfoliated gillulyite flakes are investigated. The observed highly anisotropic optical properties originate from the reduced in-plane crystal symmetry. Additionally, the …

Polarization-Dependent Optical Responses In Natural 2d Layered Mineral Teallite, Ravi P. N. Tripathi, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Multi-element layered materials enable the use of stoichiometric variation to engineer their optical responses at subwavelength scale. In this regard, naturally occurring van der Waals minerals allow us to harness a wide range of chemical compositions, crystal structures and lattice symmetries for layered materials under atomically thin limit. Recently, one type of naturally occurring sulfide mineral, ternary teallite has attained significant interest in the context of thermoelectric, optoelectronic, and photovoltaic applications, but understanding of light-matter interactions in such ternary teallite crystals is scarcely available. Herein, polarization-dependent linear and nonlinear optical responses in mechanically exfoliated teallite crystals are investigated including anisotropic …

Impact Of Surface And Pore Characteristics On Fatigue Life Of Laser Powder Bed Fusion Ti–6al–4v Alloy Described By Neural Network Models, Seunghyun Moon, Ruimin Ma, Ross Attardo, Charles Tomonto, Mark Nordin, Paul Wheelock, Michael Glavicic, Maxwell Layman, Richard Billo, Tengfei Luo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, the effects of surface roughness and pore characteristics on fatigue lives of laser powder bed fusion (LPBF) Ti–6Al–4V parts were investigated. The 197 fatigue bars were printed using the same laser power but with varied scanning speeds. These actions led to variations in the geometries of microscale pores, and such variations were characterized using micro-computed tomography. To generate differences in surface roughness in fatigue bars, half of the samples were grit-blasted and the other half were machined. Fatigue behaviors were analyzed with respect to surface roughness and statistics of the pores. For the grit-blasted samples, the contour …

Anisotropy In Impact Toughness Of Powder Bed Fused Aisi 304l Stainless Steel, Sreekar Karnati, Atoosa Khiabhani, Aaron Flood, Frank W. Liou, Joseph William Newkirk

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The current effort involved investigation into the anisotropy of AISI 304L fabricated through laser powder bed fusion. Charpy V‐notch specimens made from material fabricated at three different build orientations were tested and analyzed. A statistically significant difference among the toughness values indicates the presence of anisotropy within the additively manufactured material. While the lowest toughness was found in vertically built specimens, the horizontal specimens were found to exhibit the highest toughness. From the fracture surfaces, an atypical mode of failure was observed. Exclusive crack propagation along the interlayer track boundaries was observed. The toughness variation correlated with the ease of …

Tissue Engineering And The Effect Of Volumetric Muscle Loss On Muscle Performance, Alex Pemberton

Biomedical Engineering Undergraduate Honors Theses

Trauma, for so many people, creates life altering injuries. One of the major injuries that results from trauma is volumetric muscle loss (VML), which is the loss of muscle tissue that cannot be naturally regenerated and results in chronic loss of function. When a small amount of damage is done to a muscle, but the underlying extracellular matrix of the cell is still intact, the muscle can regenerate much of its volume and function. If the injury damages the extracellular matrix, the injury site is instead filled with scar tissue, which cannot regenerate muscle mass or function. Seen widely in …

Using Iphone Significant Location Data To Improve Air Pollution Exposure Estimation, Elizabeth Eastman

Electronic Theses and Dissertations, 2020-2023

An accurate estimation of human exposure to ambient air pollution is crucial for air pollution health studies. Time-activity patterns may introduce substantial uncertainties in exposure estimation. As smartphones are becoming increasingly popular and their ownership is becoming ubiquitous in the US. Virtually all smartphones can collect location data, and such data is continuously somewhere. Therefore, it is clear that such stored location data has the potential to be used for characterizing an individual's time-activity patterns for air pollution health studies. However, studies on the accuracy and feasibility of using a smartphone's location data in air pollution exposure estimation are still …

Assessment Of Leadership Styles And Lean Six Sigma Critical Success Factors In The Aerospace And Defense Industry, Corey Gellis

Electronic Theses and Dissertations, 2020-2023

The Aerospace and Defense industry has shifted into a global competitive market that is prioritizing innovative advancements in technological capabilities. Corporations are now having to further develop customer focused strategies based in adding value while reducing costs. Large manufacturing corporations often embrace continuous improvement methodologies, such as Lean Six Sigma, for process improvement. Many organizations have received minimal benefit from the methodology which may link back to leadership and culture. This research examined which styles of leadership are most effective when trying to gain the most value from Lean Six Sigma within manufacturing. The research study surveyed 112 black belt …

Anomaly Detection And Failure Prediction In Gas Turbines, Vipul Goyal

Electronic Theses and Dissertations, 2020-2023

This study is based on time-series data taken from the combined cycle heavy-duty utility gas turbines. For analysis, first, a multi-stage vector autoregressive model is constructed for the nominal operation of powerplant assuming sparsity in the association among variables, and this model is used as a basis for anomaly detection and prediction. This prediction is compared with the time-series data of the powerplant test data containing anomalies. Granger causality networks, which are based on the associations between the time series streams, can be learned as an important implication from the vector autoregressive modelling. This method suffers from the disadvantage that …