Digital Commons Network^™

Using Computational Methods To Optimize High Heat Flux Component Thermal Performance In Magnetic Confinement Fusion Reactor Research, Monica Gehrig

Doctoral Dissertations

"Heat transfer enhancement by means of internally modified geometries in tubes and channels is an important mechanism to improve the survivability of components in extreme high-heat flux environments. Various features such as ribs and fins are studied using computational fluid dynamics in both uniform and one-sided heating in tubes and rectangular channels respectively to determine the most effective geometries across a variety of different flow and heating conditions. This work examines heat transfer enhancement and rib geometry optimization to support experimental research for nuclear fusion applications. The project begins by designing and analyzing test sections supporting a helium flow loop …

The Effect Of Mass Transport On Deposit Quality In Copper Electrowinning, Joseph Bauer

Doctoral Dissertations

"Roughness and nodulation of copper electrodeposits depend strongly on mass transfer conditions of copper ions to the electrode surface. Mass transfer properties in electrowinning electrolytes were first characterized. The effective diffusivity of cupric ion was measured with a rotating disk electrode in CuSO₄-H₂SO₄ electrolytes at temperatures relevant to electrowinning, with and without additives. Adding 20 mg L^-1 of chloride ion increased the measured diffusion coefficient, but commercial smoothing additives had little effect. An empirical formula to predict cupric diffusivity was generated for later use in mass transport modeling.

Boundary layer thickness information for commercial …

Mantle Flow And Transition Zone Discontinuities Beneath The Carribean Plate: Constraints From Shear Wave Splitting And Receiver Function Analyses, Tu Xue

Doctoral Dissertations

"Azimuthal anisotropy quantified by teleseismic SKS, SKKS, PKS (“XKS”) and local S wave splitting parameters is used to investigate lithospheric deformation and asthenospheric flow beneath the boundary zone of the North American and Caribbean plates and adjacent areas. A total of 4915 XKS and 1202 pairs of local S wave splitting parameters were obtained at 24 broad band seismic stations. The XKS observations can be divided into two groups based on the spatial distribution of the resulting fast polarization orientations. Those observed on the Caribbean Plate are mostly WNW-ESE which are roughly trench-parallel. In contrast, the fast orientations observed on …

Development And Application Of Ensemble Machine Learning Algorithms To Enable A Priori, High-Fidelity, And Prompt Predictions And Optimizations Of Complex Materials And Systems, Taihao Han

Doctoral Dissertations

"Complex materials consisting of multiple chemical components/phases have been widely used in different engineering applications that have strict criteria. To optimize the mixture design of complex materials, researchers invest enormous resources in cumbersome experiments. However, due to substantial variations in precursors and processing techniques, it has been challenging to develop theoretical frameworks (i.e., empirical models) that could produce reliable predictions of properties of complex materials. In recent years, scientists have harnessed the power of machine learning (ML) and “Big” data to uncover the underlying mixture design-property correlations and produce high-fidelity predictions of properties of complex materials. The ML models autonomously …

Far-End Crosstalk Modeling And Prediction For High-Speed Pcb Design With Inhomogeneous Dielectric Layers (Idls), Yuanzhuo Liu

Doctoral Dissertations

"Far-end crosstalk (FEXT) noise is a critical factor that affects signal integrity performance in high-speed systems. The FEXT level is sensitive to the inhomogeneity of the dielectric layers in fabricated printed circuit boards (PCB). The stripline is laminated by multiple inhomogeneous dielectric layers (IDL). The dielectric layers of the stripline are laminated with epoxy resin and glass bundles. The dielectric permittivity of the epoxy resin and glass bundles are different, which causes the inhomogeneity of the dielectric layers while also increasing the FEXT magnitude. The dielectric of the microstrip in printed circuit boards (PCB) fabrication usually consists of two layers: …

Optimization Of Energy Storage Scheduling In Electricity Markets, Jian Liu

Doctoral Dissertations

"In the existing literature, merchants' trading actions are usually assumed not to affect market prices; however, a large-scale energy storage merchant’s actions can affect market prices. This work examined two electricity merchant scenarios: one with only energy storage and the other with both energy storage and renewable power plants. We approximated market impact via a linear function of the electricity traded by the merchant. This study began by applying dynamic programming to the optimal economic dispatch policy of electricity merchants and it considered the market impact, physical characteristics of storage systems, and the uncertainty of renewable energy sources. Then, this …

Disorder Effects In Frustrated Magnets And Absorbing State Transitions, Xuecheng Ye

Doctoral Dissertations

"Correlation, topology, and disorder can fundamentally affect the properties of interacting many-particle systems. After a short introduction which covers the basic concepts of phase transitions and scaling as well as the physics of Josephson junctions, the dissertation focuses on three separate projects.

The first project is motivated by the stripe and nematic phases observed e.g. in cuprate superconductors and iron pnictides. To understand the effects of disorder on such phases, we have investigated the behavior of the diluted J₁-J₂ Ising model. Spinless impurities generate a random-field disorder for the spin-density (stripe) order parameter, which destroys the stripe …

Resistivity Imaging Of Prominent Seepage Pathways In Karst Terrain, Abdullah Hadi Zaid Alhaj

Doctoral Dissertations

"An integrated research approach was conducted to evaluate subsurface karstic conditions in Greene County, southwestern Missouri. Electrical resistivity tomography (ERT) was employed to image anomalously low resistivity zones associated with the presence of seepage pathways that were anthropogenic and/or natural in origin. Techniques including visual inspection (VI), multichannel analysis of surface waves (MASW), borehole control (BC), and aerial imagery (AI) were supplementally used to constrain the ERT data interpretations.

This research addressed six objectives. First, the ERT data interpretations were verified in terms of depth to the top of bedrock, fractures/voids, and moisture changes using the MASW, borehole control, and …

Mobility Analysis And Topology Synthesis Of Compliant Mechanism Using Compliance Number And Pseudo-Rigid-Body Model (Prbm), Pratheek Bagivalu Prasanna

Doctoral Dissertations

"Establishing and understanding the kinematic properties of a compliant mechanism has been a relatively recent endeavor and has proved to be a challenging task. A concept of compliance number was offered earlier; the development of terminologies was emphasized that aided in its determination. It also hypothesized that the compliance number (C) and stored strain energy, or mode shapes, are strongly correlated. This compliance number (C) concept is revisited, and a more lucid interpretation of its significance is provided. A fundamental understanding of the concept of deformation mode shapes in compliant mechanisms is formalized using two distinct categories: (i) segmental and …

Deep Learning-Based Surrogate Models For Post-Earthquake Damage Assessment, Xinzhe Yuan

Doctoral Dissertations

"Seismic damage assessment is a critical step to enhance community resilience in the wake of an earthquake. This study aims to develop deep learning-based surrogate models for widely used fragility curves to achieve more accurate and rapid assessment in practice. These surrogate models are based on artificial neural networks trained from the labelled ground motions whose resulting damage classes on targeted structures are determined by nonlinear time history analyses. The development of various surrogate models is progressed in four phases. In Phase I, the multilayer perceptron (MLP) is used to develop multivariate seismic classifiers with up to 50 hand-crafted intensity …

Plasma Spheroidization Of Gas-Atomized 304l Stainless Steel Powder For Laser Powder Bed Fusion Process, M. Hossein Sehhat, Austin T. Sutton, Chia-Hung Hung, Ben Brown, Ronald J. O'Malley, Jonghyun Park, Ming-Chuan Leu

PSMRC Faculty Research

Particles of AISI 304L stainless steel powder were spheroidized by the induction plasma spheroidization process (TekSphero-15 spheroidization system) to assess the effects of the spheroidization process on powder and part properties. The morphology of both as-received and spheroidized powders was characterized by measuring particle size and shape distribution. The chemistry of powders was studied using inductively coupled plasma optical emission spectroscopy for evaluation of composing elements, and the powder’s microstructure was assessed by X-ray diffraction for phase identification and by electron backscattered diffraction patterns for crystallography characterization. The Revolution Powder Analyzer was used to quantify powder flowability. The mechanical properties …

Liquid Core Detection And Strand Condition Monitoring In A Continuous Caster Using Optical Fiber, Deva Prasaad Neelakandan, Dinesh Reddy Alla, Jie Huang, Ronald J. O'Malley

PSMRC Faculty Research

Real-time monitoring of the liquid core position during the continuous casting of steel has been demonstrated using low-cost distributed optical-fiber-based strain sensors. These sensors were installed on the containment roll support structures in the segments of a production continuous caster to detect the position of the solid–liquid interface and monitor the strand condition during the continuous casting. Distributed Fiber Bragg Grating sensors (FBGs) were used in this work to monitor strain at six roll positions in the caster. The sensor performance was first validated by comparing optical strain measurements with conventional strain gauge measurements in the lab. Next, optical strain …

Forecasting Nodal Price Difference Between Day-Ahead And Real-Time Electricity Markets Using Long-Short Term Memory And Sequence-To-Sequence Networks, Ronit Das, Rui Bo, Haotian Chen, Waqas Ur Rehman, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Price forecasting is at the center of decision making in electricity markets. Much research has been done in forecasting energy prices for a single market while little research has been reported on forecasting price difference between markets, which presents higher volatility and yet plays a critical role in applications such as virtual trading. To this end, this paper takes the first attempt at it and employs novel deep learning architecture with Bidirectional Long-Short Term Memory (LSTM) units and Sequence-to-Sequence (Seq2Seq) architecture to forecast nodal price difference between day-ahead and real-time markets. In addition to value prediction, these deep learning architectures …

Scholars' Mine Quick Facts December 2021, Nancy S. Krost

Scholars’ Mine Statistics

Scholars' Mine Quick Facts are monthly reports of downloads, page hits, and other information about works in the institutional repository of Missouri S&T. A map with downloads by region is also included.

Removal Of Methylene Blue By Adsorption Of Water Hyacinth Derived Active Carbon Embedded With Cobalt Nanoparticles, Hany A. Elazab, A. O. Okasha, M. A. Radwan, M. A. Sadek, Amin Firouzi, Tamer T. El-Idreesy

Chemical and Biochemical Engineering Faculty Research & Creative Works

In this research, active carbon-based catalyst synthesis and characterization were tested for potential catalysts to be used in dye removal of methylene blue (MB). Water hyacinth is one of the major problems that is facing humankind and especially here in Egypt. One of the implications of industrial activities is environmental pollution. Dyes used in the production of textiles, paper, and clothes are one of the major pollutants. The waste of those dyes discharged into water supplies without treatment or with ineffective treatment harmfully impacts the environment. In this research, the treatment is implemented using active carbon-based catalysts using embedded nanoparticles. …

A Novel Dental Re-Mineralizing Blend Of Hydroxyethyl-Cellulose And Cellulose Nanofibers Oral Film Loaded With Nepheline Apatite Glass: Preparation, Characterization And In Vitro Evaluation Of Re-Mineralizing Effect, Dalia Y. Zaki, Engie M. Safwat, Shaymaa M. Nagi, Haidy N. Salem, Tamer M. Hamdy, Lamiaa M. Moharam, Mohammad L. Hassan, E. M.A. Hamzawy

Chemical and Biochemical Engineering Faculty Research & Creative Works

The present investigation aimed to prepare and evaluate an innovated re-mineralizing oral films made from a blend of hydroxyethyl-cellulose (HEC) and cellulose nanofibers (CNF), loaded with nepheline fluorapatite glass powder. Evaluation of film thickness, folding endurance, disintegration time, surface pH, ions release, together with SEM were carried out. In vitro re-mineralizing effect of the prepared film on demineralized teeth was examined. Results revealed the uniformity in thickness of films, folding endurance more than 300, and the disintegration times more than 24 hrs. The pH values were nearly neutral and high concentrations of calcium and fluoride ions were released. SEM showed …

Durable Nanocomposite Face Masks With High Particulate Filtration And Rapid Inactivation Of Coronaviruses, Andrew Gonzalez, Hamada A. Aboubakr, John Brockgreitens, Weixing Hao, Yang Wang, Sagar M. Goyal, Abdennour Abbas

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The COVID-19 pandemic presents a unique challenge to the healthcare community due to the high infectivity rate and need for effective personal protective equipment. Zinc oxide nanoparticles have shown promising antimicrobial properties and are recognized as a safe additive in many food and cosmetic products. This work presents a novel nanocomposite synthesis approach, which allows zinc oxide nanoparticles to be grown within textile and face mask materials, including melt-blown polypropylene and nylon-cotton. The resulting nanocomposite achieves greater than 3 log₁₀ reduction (≥ 99.9%) in coronavirus titer within a contact time of 10 min, by disintegrating the viral envelope. The …

Editorial: Molecular Simulation On Cementitious Materials: From Computational Chemistry Method To Application, Hongyan Ma, Dongshuai Hou, Jinrui Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Discovery Of An Olivine-Type Lithium Manganese Thiophosphate, Limnps4,: Via A Building Block Approach, Srikanth Balijapelly, Kartik Ghosh, Aleksandr V. Chernatynskiy, Amitava Choudhury

Physics Faculty Research & Creative Works

An olivine-type orthothiophospate LiMnPS4 has been synthesized for the first time through a building block approach by reacting preformed ternary lithium thiophospate with MnCl2. Diffuse reflectance measurements show an optical band gap of 2.36 eV, which is further confirmed by DFT calculations. Irreversible weak ferromagnetic ordering and metamagnetism are verified through preliminary magnetic measurements.

Solvation Of Isoelectronic Halide And Alkali Metal Ions By Argon Atoms, Carly A. Rock, Sarah N. Arradondo, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work systematically examines the interactions of alkali metal cations and their isoelectronic halide counterparts with up to six solvating Ar atoms (M+Arn and X–Arn, where M = Li, Na, K, and Rb; X = H, F, Cl, and Br; and n = 1–6) via full geometry optimizations with the MP2 method and robust, correlation-consistent quadruple-ζ (QZ) basis sets. 116 unique M+Arn and X–Arn stationary points have been characterized on the MP2/QZ potential energy surface. To the best of our knowledge, approximately two dozen of these stationary points have been reported here for the first time. Some of these new …

Modeling Iterative Reconstruction And Displacement Field In The Large Scale Structure, Atsuhisa Ota, Hee Jong Seo, Shun Saito, Florian Beutler

Physics Faculty Research & Creative Works

The next generation of galaxy surveys like the Dark Energy Spectroscopic Instrument and Euclid will provide datasets orders of magnitude larger than anything available to date. Our ability to model nonlinear effects in late time matter perturbations will be a key to unlock the full potential of these datasets, and the area of initial condition reconstruction is attracting growing attention. Iterative reconstruction developed by Marcel Schmittfull et al. [Phys. Rev. D 96, 023505 (2017)PRVDAQ2470-001010.1103/PhysRevD.96.023505] is a technique designed to reconstruct the displacement field from the observed galaxy distribution. The nonlinear displacement field and initial linear density field are highly correlated. …

Hyperspectral Imaging And Data Analytics For Civil Infrastructure Inspection, Genda Chen

INSPIRE Archived Webinars

In this 50-minute lecture, the fundamental concept of hyperspectral imaging is reviewed. Each hyperspectral image represents a narrow, contiguous wavelength range of an electromagnetic spectrum, which could be indicative of a chemical substance. All the images in the spectral range of a hyperspectral camera are combined to form a three-dimensional hyperspectral data cube with two spatial dimensions and one spectral dimension. A hyperspectral cube can be sampled in four ways: spatial scanning, spectral scanning, snapshot imaging, and spatio-spectral scanning. This presentation will be focused on spatial scanning from a line-scan camera. The feasibility of horizontal imaging from a synchronized hyperspectral …

Signatures Of A Quantum Griffiths Phase Close To An Electronic Nematic Quantum Phase Transition, Pascal Reiss, David Graf, Amir A. Haghighirad, Thomas Vojta, Amalia I. Coldea

Physics Faculty Research & Creative Works

In the vicinity of a quantum critical point, quenched disorder can lead to a quantum Griffiths phase, accompanied by an exotic power-law scaling with a continuously varying dynamical exponent that diverges in the zero-temperature limit. Here, we investigate a nematic quantum critical point in the iron-based superconductor FeSe0.89S0.11 using applied hydrostatic pressure. We report an unusual crossing of the magneto resistivity isotherms in the Non superconducting normal state that features a continuously varying dynamical exponent over a large temperature range. We interpret our results in terms of a quantum Griffiths phase caused by nematic islands that result from the local …

Local Environmental Variables Are Key Drivers Of Ant Taxonomic And Functional Beta-Diversity In A Mediterranean Dryland, Clara Frasconi Wendt, Ana Ceia-Hasse, Alice Nunes, Robin Verble, Giacomo Santini, Mário Boieiro, Cristina Branquinho

Biological Sciences Faculty Research & Creative Works

The decomposition of beta-diversity (β-diversity) into its replacement (β_repl) and richness (β_rich) components in combination with a taxonomic and functional approach, may help to identify processes driving community composition along environmental gradients. We aimed to understand which abiotic and spatial variables influence ant β-diversity and identify which processes may drive ant β-diversity patterns in Mediterranean drylands by measuring the percentage of variation in ant taxonomic and functional β-diversity explained by local environmental, regional climatic and spatial variables. We found that taxonomic and functional replacement (β_repl) primarily drove patterns in overall β-diversity (β_tot). …

Oscillation Of Nonlinear Third-Order Difference Equations With Mixed Neutral Terms, Jehad Alzabut, Martin Bohner, Said R. Grace

Mathematics and Statistics Faculty Research & Creative Works

In this paper, new oscillation results for nonlinear third-order difference equations with mixed neutral terms are established. Unlike previously used techniques, which often were based on Riccati transformation and involve limsup or liminf conditions for the oscillation, the main results are obtained by means of a new approach, which is based on a comparison technique. Our new results extend, simplify, and improve existing results in the literature. Two examples with specific values of parameters are offered.

Fourth Derivative Singularly P-Stable Method For The Numerical Solution Of The Schrödinger Equation, Ali Shokri, Higinio Ramos, Mohammad Mehdizadeh Khalsaraei, Fikret A. Aliev, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we construct a method with eight steps that belongs to the family of Obrechkoff methods. Due to the explicit nature of the new method, not only does it not require another method as predictor, but it can also be considered as a suitable predictive technique to be used with implicit methods. Periodicity and error terms are studied when applied to solve the radial Schrödinger equation, considering different energy levels. We show its advantages in terms of accuracy, consistency, and convergence in comparison with other methods of the same order appearing in the literature.

Scholars' Mine Quick Facts November 2021, Nancy S. Krost

Scholars’ Mine Statistics

Scholars' Mine Quick Facts are monthly reports of downloads, page hits, and other information about works in the institutional repository of Missouri S&T. A map with downloads by region is also included.

Orchestrating Performance Of Healthcare Networks Subjected To The Compound Events Of Natural Disasters And Pandemic, Emad M. Hassan, Hussam N. Mahmoud

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The current COVID-19 pandemic has demonstrated the vulnerability of healthcare systems worldwide. When combined with natural disasters, pandemics can further strain an already exhausted healthcare system. To date, frameworks for quantifying the collective effect of the two events on hospitals are nonexistent. Moreover, analytical methods for capturing the dynamic spatiotemporal variability in capacity and demand of the healthcare system posed by different stressors are lacking. Here, we investigate the combined impact of wildfire and pandemic on a network of hospitals. We combine wildfire data with varying courses of the spread of COVID-19 to evaluate the effectiveness of different strategies for …

Predicting Lifespan Of Drosophila Melanogaster: A Novel Application Of Convolutional Neural Networks And Zero-Inflated Autoregressive Conditional Poisson Model, Yi Zhang, V. A. Samaranayake, Gayla R. Olbricht, Matthew S. Thimgan

Mathematics and Statistics Faculty Research & Creative Works

A model to classify the lifespan of Drosophila, the fruit fly, into short- and long-lived categories based on a sleep characteristic, extracted from activity data, is developed using a two-stage process. Stage 1 models the per-minute activity counts of each fly using a zero-inflated autoregressive conditional Poisson model. These probabilities are allowed to vary hourly, reflecting the circadian and other cycles present in a fly's sleep architecture. A 5-day moving window is used to model data allowing the model parameters to vary over the course of the fly's life. The resulting probabilities capture information about changes in sleep patterns with …

Generalization Of Mitrinović–Pečarić Inequalities On Time Scales, Ahmed A. El-Deeb, Elvan Akin, Billur Kaymakçalan

Mathematics and Statistics Faculty Research & Creative Works

We prove some new inequalities of Mitrinović–Pečarić inequalities for convex functions on an arbitrary time scale using delta integrals. These inequalities extend and improve some known dynamic inequalities in the literature. The main results will be proved by using Hölder and Jensen inequalities and a simple consequence of Keller's and Poetzsche's chain rules on time scales.