Digital Commons Network^™

Oxidation Of Additively Manufactured Zrb2–Sic In Air And In Co2 At 700–1000 °C, Marharyta Lakusta, Nicholas M. Timme, Abid H. Rafi, Jeremy Lee Watts, M. (Ming) C. (Chuan) Leu, Gregory E. Hilmas, William G. Fahrenholtz, David W. Lipke

Materials Science and Engineering Faculty Research & Creative Works

Oxidation behavior of additively manufactured zrb2–sic in air and in co2 is reported in the temperature range of 700–1000 °c. Observed scale morphologies in air and in co2 were similar, featuring an outer borosilicate layer and an inner porous zirconia layer containing partially oxidized silicon carbide particles and remnant borosilicate products. Oxide scale thicknesses and parabolic scaling constants in air were approximately twice those observed in co2 across all studied temperatures. Activation energies for oxidation of 140 ± 20 kj/mol in air and 110 ± 20 kj/mol in co2 were determined, indicating similar diffusion processes that appear to be rate-limiting. …

Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Aggregate is the most extracted material from the world's mines and widely used in civil and construction projects. The Micro-Deval abrasion test (MD) is one of the most important tests that provides characteristics of crushed aggregates that show their resistance against mechanical abrasive factors such as repeated impact loading. The impact of various factors on abrasive resistance properties of aggregates has led researchers to seek correlations, often focusing on limited data samples, leading to reduced accuracy. This study employs machine learning (ML) methods to predict MD abrasion values, considering diverse aggregate properties. Various ensemble ML methods were applied, revealing the …

Scshm Benchmark Study On Bridge In-Service Structural Monitoring, Maria Pina Limongelli, Doug Thomson, Sreenivas Alampalli, Aftab Mufti, Thomas Schumacher, Luca Martinelli, Othmane Lasri, Harry Shenton, Genda Chen, Mohammad Noori, Farnaz Raeisi, Ahmed Silik, Ji Dang, Ray Hoemsen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The mission of the Society of Civil Structural Health Monitoring (SCSHM, previously known as ISHMII) is to advance the understanding and application of structural monitoring methodologies for the management of civil infrastructure systems. To enable comparative and contrasting studies of various monitoring issues and technologies, the SCSHM Committee on Data-Enhanced Infrastructures Management (DEIMC) identified the need for benchmark problems in the areas of bridge and building structural monitoring. This article reports and briefly discusses the first benchmark study on in-service structural monitoring of bridges that was developed in collaboration with the University of Manitoba, and presents the structure details, study …

Towards A Concurrency Platform For Scalable Multi-Axial Real-Time Hybrid Simulation, Marion Sudvarg, Oren Bell, Tyler Martin, Benjamin Standaert, Tao Zhang, Sun Beom Kwon, Chris Gill, Arun Prakash

Computer Science Faculty Research & Creative Works

Multi-axial real-time hybrid simulation (maRTHS) uses multiple hydraulic actuators to apply loads and deform experimental substructures, enacting both translational and rotational motion. This allows for an increased level of realism in seismic testing. However, this also demands the implementation of multiple-input, multiple-output control strategies with complex nonlinear behaviors. To realize true real-time hybrid simulation at the necessary sub-millisecond timescales, computational platforms will need to support these complexities at scale, while still providing deadline assurance. This paper presents initial work towards supporting (and is influenced by the need for) envisioned larger-scale future experiments based on the current maRTHS benchmark: it discusses …

Minerrouter : Effective Message Routing Using Contact-Graphs And Location Prediction In Underground Mine, Abhay Goyal, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Location-based distributed communication in underground mines has been a hard problem to solve due to unreliable centralized architecture such as leaky feeder systems, high attenuation, and the unavailability of GPS signals. Delay Tolerant Networks (DTN) enable decentralized message routing using the store-carry-forward method that can help in creating situational awareness needed to handle emergency and disaster scenarios. The ability to predict where the DTN nodes (miner) might have been at/are headed to (with respect to the mine regions and pillars) at different times, combined with contact-based routing and intelligent handling of buffer, can be used for better delivery of messages. …

Circular Economy Strategies For Decarbonization Of The Built Environment Value Chain Scope 3 Emissions: A Network Analysis, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

With The Anticipated Growth In Construction Activities, Minimizing Value Chain Emissions, Including Those Attributed To Activities Beyond An Organization's Direct Control - Aka "Scope 3" Emissions, And Adopting Circular Economy (CE) Practices Have Become Critical To Attaining The 2050 Climate Goals. Extant Literature Lacks A Value-Chain-Comprehensive Set Of CE Strategies On One Hand, And An Analysis Of Their Actual Project Applications On The Other. This Research Aims To Build A Holistic Portfolio Of CE Actionable Strategies That Span Across The Entire Built Environment Value Chain, Analyzing Their Extent Of Implementation And Interlinkages Within The Literature Versus Actual Projects. To This …

Evaluation Of Novel Preformed Particle Gel System For Conformance Control In Mature Oil Reservoirs, Abdulaziz Almakimi, Ahmed Ben Ali, Ibnelwaleed A. Hussein, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

To address challenges associated with excessive water production in mature oil reservoirs, this study introduces a carboxymethyl cellulose (CMC)-based material as a novel preformed particle gel (PPG) designed to plug excessive water pathways and redistribute the subsequent injected water toward unswept zones. Through microwave-assisted grafting copolymerization of CMC with acrylamide (AM), we successfully generated multi-sized dry particles within the range of 250–800 µm. Comprehensive analyses, including Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM), have confirmed the chemical composition and morphology of the resulting carboxymethyl cellulose-grafted crosslinked polyacrylamide (CMC/PAMBA). Swelling kinetics and rheology tests were conducted to confirm the …

Effect Of Bioactive Borate Glass On Printability And Physical Properties Of Hydrogels, Fateme Fayyazbakhsh, Mehedi H. Tusar, Yue-Wern Huang, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Hydrogels are a key component in bioinks and biomaterial inks for bioprinting due to their biocompatibility and printability at room temperature. The research described in the present paper contributes to the advancement of bioprinting by studying the effect of bioactive borate glass (BBG) incorporated into hydrogels on printability and physical properties. In this study, we fabricated 3D-printed hydrogel scaffolds using gelatin and alginate hydrogel mixture incorporated with various amounts of BBG, a bio ceramic rich in therapeutic ions including boron, calcium, copper, and zinc. We investigated the effect of incorporating BBG on the density, viscosity, physical interactions, chemical structure, and …

An Evaluation Of Methods For Assessing Robot Kinematic Model Accuracy In The Presence Of Noise, Mitchell R. Woodside, Patrick Bazzoli, Philip A. Olubodun, J. Adam Nisbett, Guixiu Qiao, Douglas A. Bristow

Mechanical and Aerospace Engineering Faculty Research & Creative Works

While there are many works developing methods for modeling and calibrating robot kinematics, assessing the accuracy of those models has received little attention. However, accuracy assessment is critically important for applications where the robot must operate with absolute accuracy over a large region of workspace, such as in robotic machining. When the model of such a system is well calibrated, the remaining deterministic error can be quite complex, owing to complicated gearing errors, deformations, and quasi-static thermal changes. Locating the largest deterministic error requires an exploration over the workspace, but assessing the largest error is complicated by repeatability error and …

Impact Of Aging On Pim And Dc Resistance Of Fabric-Over-Foam Metallic Contacts, Kalkidan W. Anjajo, Seunghun Ryu, Shengxuan Xia, Gracie Boyer, Yuchu He, Haicheng Zhou, Hanfeng Wang, Jonghyun Park, Chulsoon Hwang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this paper the impact of aging on the level of passive intermodulation (PIM) and DC resistance of fabric-over-foam metallic contacts is presented. These contacts are widely used to maintain metallic connections between modules and chassis in electronic devices. The PIM caused by the loose metallic contact of these materials mainly affects a receiver's RF sensitivity in mobile devices. This aging test under elevated temperature and relative humidity conditions offers an experiment-based approach with respect to various metallic contact cases. Energy dispersive spectroscopy and scanning electron microscopy are used to characterize the change in material composition and the contact surface …

Development Of Digital Twin For Fdm Printer With Preventive Cyber-Attack And Control Algorithms, Md Hazrat Ali, Asad Malik, Nursultan Jyeniskhan, Muhammad Arif Mahmood, Essam Shehab, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper presents a developed model of a Digital Twin (DT) for a fused deposition modeling (FDM) printer, real-time defect detection, and proposed frameworks for preventing cyber-attacks in real-time. It also highlights a model predictive control (MPC) algorithm for controlling the material feed based on a real-time feedback system. The system is designed and developed based on DT, and MPC with integrated machine learning (ML) algorithms to establish real-time process control and enhance the safety and reliability of the physical plant. ML algorithm is used for anomaly detection based on the convolutional neural network (CNN) model. The developed system can …

Hyper-Thick Electrodes For Lithium-Ion Batteries Enabled By Micro-Electric-Field Process, Tazdik Patwary Plateau, Gracie Boyer, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Increasing electrode thickness is a key strategy to boost energy density in lithium-ion batteries (LIBs), which is essential for electric vehicles and energy storage applications. However, thick electrodes face significant challenges, including poor ion transport, long diffusion paths, and mechanical instability, all of which degrade battery performance. to overcome these barriers, a novel micro-electric-field (μ-EF) process is introduced that enhances particle alignment during fabrication with reduced distance between anode and cathode. This process produces hyper-thick (≈700 µm) electrodes with low tortuosity and improved ion diffusion. the μ-EF electrodes achieve high areal capacities (≈8 mAh cm−2), while maintaining power density and …

Investigating Bistable Dynamics Of Coupled Oscillators With Similarities To Neural Activity In Epilepsy, Nilay Kant, Ranjan Mukherjee

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The dynamics of an oscillator, which exhibits a stable equilibrium and a stable limit cycle, is investigated. We refer to it as a bistable oscillator unit (BOU) and show that two coupled BOUs (CBOUs) exhibit dynamics analogous to neural activity patterns in epilepsy, including healthy, localized, and fully spread epileptic states. By treating each CBOU as an independent system influenced by the state of the other, we establish local input-to-state stability near the equilibrium and the limit cycle and estimate the ultimate bounds of the trajectories. Our analysis identifies the domain of the initial conditions and estimates the coupling parameter …

Modeling Human Strategy For Flattening Wrinkled Cloth Using Neural Networks, Nilay Kant, Ashrut Aryal, Rajiv Ranganathan, Ranjan Mukherjee, Charles Owen

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper explores a novel approach to model strategies for flattening wrinkled cloth learning from humans. A human participant study was conducted where the participants were presented with various wrinkle types and tasked with flattening the cloth using the fewest actions possible. A camera and Aruco marker were used to capture images of the cloth and finger movements, respectively. The human strategies for flattening the cloth were modeled using a supervised regression neural network, where the cloth images served as input and the human actions as output. Before training the neural network, a series of image processing techniques were applied, …

Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of …

Kinetic Simulations Of Dust Grain Charging Near Surfaces Under Various Plasma Conditions, David Lund, Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper presents fully kinetic numerical investigations of the charging of spherical and irregular shaped dust grains in multiple configurations utilizing the Parallel Immersed-Finite-Element Particle-in-Cell Dusty (PIFE-PIC-D) framework. The simulations account for both surface charging and in-depth charging of the dust grains immersed in various ambient plasma conditions near a floating or biased surface. PIFE-PIC-D explicitly resolves the geometrical and material properties (permittivity and photoelectron emissions) of each individual dust grain. PIFE-PIC-D will model self-consistently the unsteady and stochastic charging of grains directly from the deposition of electrons and ions onto them. PIFE-PIC-D will also simulate the charging of irregular-shaped …

Sensor Tasking Strategies For Space-Based Observers In The Cislunar Environment, Smriti Nandan Paul, Roshan Thomas Eapen, Puneet Singla

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The cislunar space environment has witnessed an increase in activities, and future projections indicate significant growth in object population. Consequently, it becomes crucial to monitor these objects for space domain awareness (SDA) purposes. As the number of objects surpasses the available observers, meticulous sensor tasking becomes essential. This paper focuses on designing and exploring strategies for observing and keeping custody of known objects in cislunar space. Optical space-based telescopes, combined with lunar ground-based telescope, are employed for sensor tasking of cislunar objects residing in valuable orbits. The proposed research aims to address the following key points: (1) examination of the …

Development And Characterization Of An Ion Source To Simulate Low Earth Orbit Plasma Environment In A Vacuum Chamber, Emmanuel Kofi Asuako Wie-Addo, Scott Lucas, Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

A magnetic filter-type plasma source has been installed and characterized in a 10 ft long x 6ft diameter vacuum chamber. The plasma source was characterized with a fleet of diagnostic probes including an in-house cylindrical Langmuir probe. This resulted in the measurement of key plasma parameters such as electron number density, electron temperature, plasma potential, Debye length, ion current density, streaming ion energy, ion number density, and streaming ion velocity. By varying the flow rates, discharge current, and distance, single points measurements were taken at three locations downstream of the plasma source to establish an optimum operating condition to simulate …

L∞ Bounds For Transient Growth In Repetitive And Iterative Learning Control Systems, Douglas A. Bristow, John R. Singler

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper revisits the problem of large transient growth in Iterative Learning Control (ILC) and Repetitive Process Control (RPC) systems. In ILC and RPC problems a process is repeated iteratively, with new control calculations occurring in between each iteration. Large transient growth refers to the propensity of some control algorithms to grow error exponentially before eventually converging. While robust monotonic convergence algorithms (in which monotonic convergence is guaranteed usually in exchange for a small loss in performance) have largely eliminated the concern for large transient growth in ILC, similar results cannot always be obtained in RPC. The emergence of additive …

Characterization Of The Kansas River Alluvial Aquifer Using Towed Transient Electromagnetic Geophysical Method, Jonathon Daniel Voss

Masters Theses

"Forecasted urban development areas west of Kansas City, Kansas in the coming decades has caused an increase of research into water resources (Butler et al. 2022). A location of investigation has been the Kansas River Alluvial Aquifer (KRAA) for shallow ground water resources. To investigate the KRAA structure and grain texture, the towed transient electromagnetic system (tTEM) in conjunction with direct push electrical conductivity logs and lithology wells were used to investigate four locations between Lawrence and Manhattan, Kansas. In total, 110 line-kilometers of tTEM data was collected. The tTEM data collected were high quality and through inversions of the …

Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan

Masters Theses

"Anomaly detection is widely used in network intrusion detection, autonomous driving, medical diagnosis, credit card frauds, etc. However, several key challenges remain open, such as lack of ground truth labels, presence of complex temporal patterns, and generalizing over different datasets. In this work, we propose TSI-GAN, an unsupervised anomaly detection model for time-series that can learn complex temporal patterns automatically and generalize well, i.e., no need for choosing dataset-specific parameters, making statistical assumptions about underlying data, or changing model architectures. To achieve these goals, we convert each input time-series into a sequence of 2D images using two encoding techniques with …

Simulation Of Lc Circuits In Cylindrical Photoemission Driven Cavities Using Coupled Monte Carlo And Particle-In-Cell Codes, Ravi Sanjay Shastri

Masters Theses

"This work presents a computational experiment simulating irradiation of gold in a cylindrical cavity. The full 3-D simulation with a B-Dot diagnostic is modeled, and a subset of the results are compared to modeling the system as a coupled anode/cathode (AK) gap and transmission line. The cavity is filled with N2 and Ne gasses at pressures ranging from vacuum to 1000 mTorr. Space-charge limited emission physics, electric discharge physics, LC circuit physics, and Monte-Carlo methods are explored.

The computation process happens in two steps. First, the electron emission material is irradiated with an input x-ray photon spectrum to produce a …

Evaluating The Influence Of Operator Practices On Hydraulic Shovel Productivity And Energy Consumption Using Telemetry Data, Noah Adekunle Aluko

Masters Theses

"Hydraulic shovels are increasingly being adopted in the mining industry, which is known for its significant energy consumption and carbon emissions. Technological improvements in hydraulic shovels aim at bolstering energy efficiency and productivity because of the drive to curb energy consumption and enhance energy efficiency. However, one aspect that is often overlooked is the vital role of operators. Although the influence of operators’ practices on excavators’ energy efficiency has been acknowledged in past studies, there is a paucity of quantitative research assessing this influence in the context of hydraulic shovels.

The main objectives of this study are to 1) develop …

A New Proper Orthogonal Decomposition Method With Second Difference Quotients For The Wave Equation, Andrew Calvin Janes

Masters Theses

"Recently, researchers have investigated the relationship between proper orthogonal decomposition (POD), difference quotients (DQs), and pointwise in time error bounds for POD reduced order models of partial differential equations. In \cite {Sarahs}, a new approach to POD with DQs was developed that is more computationally efficient than the standard DQ POD approach and it also retains the guaranteed pointwise in time error bounds of the standard method. In this thesis, we extend the new DQ POD approach from \cite {Sarahs} to the case of second difference quotients (DDQs). Specifically, a new POD method utilizing DDQs and only one snapshot and …

A Binary Integer Linear Programming Model For Optimizing Underground Stope Layout, Theophilus Mensah

Masters Theses

"Underground mine planning engineers face significant challenges when determining what geometry provides the most profitable and safe stope for extraction. Several techniques and optimization algorithms have been developed in recent years, but most fail to find optimal solutions because they are heuristic or LP-based without efficient geometric constraints. This thesis work proposes a two-dimensional binary linear programming (BILP) model for determining the optimal combination of blocks in a stope that maximizes the economic value of the layout of stopes for a sublevel deposit. The work draws from Queyranne and Wolsey’s (2017 & 2018) formulations of tight constraints for bounded up/down …

Validation Of Athlet With Purdue University Multi-Dimensional Integral Test Assembly (Puma) Test, Emin Fatih Ozdem

Masters Theses

"Following the Three Mile Island Unit 2 (TMI-2) disaster, the development of a diagnostic system for emergency situations in a nuclear power plant was identified as an essential research area to strengthen the safety of nuclear power plants. A real-time estimation system of vital safety parameters on the main side of a PWR (Pressurized Water Reactor) facility was investigated since precise post-event scenario estimations are thought to be a crucial component of the diagnostic system. The alarm system of the plant can detect an SB-LOCA (Small Break Loss-Of-Coolant-Accident), but there were a couple of potential long-term transient occurrences. The accident …

The Deep Bsde Method, Daniel Kovach

Masters Theses

"The curse of dimensionality is the non-linear growth in computing time as the dimension of a problem increases. Using the Deep Backwards Stochastic Differential Equation (Deep BSDE) method developed in [HJE18], I approximate the solution at an initial time to a one-dimensional diffusion equation. Although we only approximate a one-dimensional equation, this method extends well to higher dimensions because it overcomes the curse of dimensionality by evaluating the given partial differential equation along "random characteristics''. In addition to the implementation, I also present most of the mathematical theory needed to understand this method"-- Abstract, p. iii

Upa-Mediated Polyamidoamine Dendrimer-Based Targeted Gene Delivery System On Triple-Negative Breast Cancer, Hsin-Yin Chuang

Masters Theses

"Around 15% of breast cancers are triple-negative breast cancer (TNBC), which is characterized by the absence of three common receptors—ER, PR, and HER2, and therefore do not respond to hormonal or anti-HER2 therapies. It is urgent to explore targeted therapeutic strategies for TNBC due to its poor prognosis and rare effective targeted therapy. In this study, we developed a polyamidoamine (PAMAM) dendrimer-based targeted gene delivery system—GDP-uPA, to utilize urokinase-type plasminogen activator (uPA) to target uPA receptor (uPAR), which is highly expressed in both TNBC cells and cancer-associated stromal cells. Our results of 1H NMR spectrum, TEM imaging, and MTT assay …

Hysplit In Simulating The Atmospheric Dispersion Of Hazardous Aerosols: A Case Study In St. Louis, Missouri, Ahmet Tolga Odabasi

Masters Theses

"Atmospheric dispersion and transmission play an important role in the behavior and effects of air pollution. Human health can be adversely affected by air pollution in a variety of ways, both immediately and over time. The Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) modeling program, a computer model and software package, tracks the transport trajectories and distributions of air pollution and various pollutants, including radioactive pollutants, in the atmosphere. It also facilitates research on pollution sources. This study simulated the transport of hazardous aerosols in St. Louis region for the years 2020, 2021, and 2022 using the HYSPLIT modeling …

High Strain Rate Analysis Of 3d Printed Concrete As Compared To Conventionally Cast Concrete, Weston Mcleod Thomsen

Masters Theses

"3D Printed Concrete (3DPC) is a developing method of construction that has advantages over conventional methods, including formwork reduction, complex geometry, and expedited construction. This technology has potential benefits for the military when considering the austere environments that forward operating bases are built in. This study aims to assess 3DPC applications in protective structures that protect critical assets from explosive blasts. These protective structures experience a high-strain rate response during blast loading of the structure, and the effects of this have yet to be analyzed in the literature concerning 3DPC. With the lack of prior research, the focus here will …