Engineering Commons^™

Testing And Characterization Of Polymer Laminates For Swelling, Absorption, And Cracking, Matthew W. Carlson

Master's Theses

A polymer laminate consisting of multiple layers of proprietary blends of Ethylene Vinyl Alcohol (EVOH) and Thermoplastic Polyurethane (TPU) and used in the construction of air bladders was evaluated for hygroscopic effects driving delamination and multiple layer fragmentation. These air bladders are observed to suffer delamination during a manufacturing process that involves immersion in an alcohol/water solution. A plausible underlying mechanism is differential swelling and absorption by the laminate constituents. Both room and elevated temperature swelling tests were carried out to find the absorption and swelling coefficients of the constituents. These coefficients served as input into a Finite Element Analysis …

Building Services Engineering September/October 2021

Building Services Engineering

No abstract provided.

Tools And Strategies For The Patterning Of Bioactive Molecules And Macromolecules, Daniel J. Valles

Dissertations, Theses, and Capstone Projects

Hypersurface Photolithography (HP) is a printing method for fabricating structures and patterns composed of soft materials bound to solid surfaces and with ~1 micrometer resolution in the x, y, and z dimensions. This platform leverages benign, low intensity light to perform photochemical surface reactions with spatial and temporal control of irradiation, and, as a result, is particularly useful for patterning delicate organic and biological material. In particular, surface- initiated controlled radical polymerizations can be leveraged to create arbitrary polymer and block- copolymer brush patterns. Chapter 1 will review the advances in instrumentation architectures from our group that have made these …

Laser-Defined Graphene Strain Sensor Directly Fabricated On 3d-Printed Structure, Tyler M. Webb, Twinkle Pandhi, David Estrada

Materials Science and Engineering Faculty Publications and Presentations

A direct-write method to fabricate a strain sensor directly on a structure of interest is reported. In this method, a commercial graphene ink is printed as a square patch (6 mm square) on the structure. The patch is dried at 100 °C for 30 min to remove residual solvents but the printed graphene remains in an insulative state. By scanning a focused laser (830 nm, 100 mW), the graphene becomes electrically conductive and exhibits a piezoresistive effect and a low temperature coefficient of resistance of −0.0006 °C⁻¹. Using this approach, the laser defines a strain sensor pattern on …

Neutron Energy Tuning Assemblies For Nuclear Weapon Environment Applications At The National Ignition Facility, Nicholas J. Quartemont

Theses and Dissertations

An energy tuning assembly was developed to spectrally shape the National Ignition Facility deuterium-tritium fusion neutron source to a notional thermonuclear and prompt fission neutron spectrum to fulfill neutron source capability gaps. The experimental neutron environment was characterized with activation dosimetry, neutronics and covariance models, and unfolded to determine the as-fielded neutron spectrum. The first energy tuning assembly was demonstrated to create synthetic spectrally accurate post-detonation fission products, enhancing U.S. technical nuclear forensics capabilities. ATHENA, a second-generation energy tuning assembly, was also optimized to meet similar objectives, but the new platform neutron fluence efficiency was increased by a factor of …

Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood

Theses and Dissertations

This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …

Evaluating Testing Procedures For Openflow Controller Network Re-Provisioning Time, Steven J. Jensen

Theses and Dissertations

Software-Defined Networking promises several advantages over traditional networking architectures, but has seen little adoption. Recently codified controller evaluation methodologies have seen little validation without strong statistical analysis of the results. The research developed an environment testing implementing a published Network Re-provisioning Time methodology to evaluate five OpenFlow controllers. The methodology is strong with required parameters but had issues with some edge cases. Further refinement and adding a convergence metric may close the gaps.

Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge

Theses and Dissertations

Clustering weather data is a valuable endeavor in multiple respects. The results can be used in various ways within a larger weather prediction framework or could simply serve as an analytical tool for characterizing climatic differences of a particular region of interest. This research proposes a methodology for clustering geographic locations based on the similarity in shape of their temperature time series over a long time horizon of approximately 11 months. To this end an emerging and powerful class of clustering techniques that leverages deep learning, called deep representation clustering (DRC), are utilized. Moreover, a time series specific DRC algorithm …

New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams

Theses and Dissertations

A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …

Physically Unclonable Characteristics For Verification Of Transmon-Based Quantum Computers, Leleia A. Hsia

Theses and Dissertations

Future national security can be strengthened by verifying and securing the quantum computing supply chain. This dissertation proposes physically unclonable characteristics (PUCs), a method of quantum hardware verification inspired by classical physically unclonable functions, for future application to quantum processors implemented with transmon qubits. Qualitative and quantitative analysis is provided on the development of PUCs, including identifying qubit characteristics and qubit discrimination methods suitable for PUCs. Characteristics tested on IBM Quantum services include T1 and T2 coherence times, single-qubit and multi-qubit gate error rates, readout error rates, quantum process tomography metrics, and random benchmarking metrics. Results show that non-parametric qubit …

Stochastic Satellite Air Drag With The Ballistic Coefficient As A Random Variable, Everett B. Palmer Iv

Theses and Dissertations

The drag acceleration caused by the Earth's atmosphere is a significant cause of prediction uncertainty for low Earth orbit satellites. Most existing research has focused on improving deterministic atmospheric density predictions or on density as a random variable. This research investigates a new paradigm and focuses on modeling the uncertainty caused by air drag using the ballistic coefficient, a component of air drag that is independent of the model used to predict atmospheric density. Time series of ballistic coefficient values were calculated and analyzed as random processes. These random processes were then used as the foundation of a stochastic satellite …

A Real-Time Algorithm To Achieve Precise Coordinated Arrival Times In A Time-Variant Environment, Shawn S. Stephens

Theses and Dissertations

The coordinated arrival time problem seeks to control a vehicle's trajectory to achieve some pre-defined final state at a desired arrival time. The persistent monitoring problem is a type of coordinated arrival problem where a stationary or moving ground target must be constantly observed by a group of aircraft. This research simplifies the problem to overfly the target at specific time intervals relative to the other aircraft in the group while increasing the difficulty of the problem by considering aircraft traveling at vastly different airspeeds. The result of this research is a real time guidance algorithm which accurately guides a …

Evaluation Of Additively Manufactured Lattices Under High Strain Rate Impact, Derek G. Spear

Theses and Dissertations

Several additively manufactured lattice designs and configurations were evaluated under compression loads under various strain rates from quasi-static to highly dynamic. These experiments examined how the mechanical behavior of the lattice changed based on the lattice design properties and the applied strain rates. The modulus of elasticity, yield strength, plateau stress, and toughness were observed to decrease with an increase in strain rate, revealing that the lattice designs exhibit a negative strain rate sensitivity. A new lattice flow stress model was developed to account for the mechanical response of the lattice and was incorporated into a computational model for simulation. …

Verification And Validation Of Radiation Protection Factors From Monte Carlo Simulations, William J. Erwin

Theses and Dissertations

This dissertation describes the verification and validation of methods for producing radiation protection factors (RPFs) using experiments and Monte Carlo N-Particle 6 (MCNP6) simulations. RPF validation of a steel enclosure using a plutonium-beryllium source produced a validated RPF with statistically significant agreement between neutron MCNP6 models and experiments and a gamma protection factor (GPF) with statistically significant agreement to the measured GPF. Efforts to validate more complex enclosures using the Fast Burst Reactor (FBR) yielded the first-ever direct measurements of this reactor’s prompt gamma emission spectrum and revealed irreconcilable differences between the FBR facility-provided source spectrum and spectrometer measurements, resulting …

Visual Navigation And Control For Spacecraft Proximity Operations With Unknown Targets, Wyatt J. Harris

Theses and Dissertations

Many current and future spacecraft missions must conduct rendezvous and proximity operations (RPO) with resident space objects (RSOs). An important subset of spacecraft RPO that is yet to be demonstrated on-orbit involves final approach maneuvers with respect to RSOs where no information (such as geometry, inertia, relative velocity, etc.) is known about the target a priori, and no information is actively provided by the target during maneuvering. Such operation with respect to ‘unknown’ targets represents an important possible mission set for Department of Defense spacecraft and is the subject of this research. Two visual servoing frameworks capable of autonomously controlling …

Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom

Theses and Dissertations

Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used to …

An Examination Of The Fuzzy Inference System On Probabilistic Roadmap Path Planning, Brandon Replogle

Master's Theses

In recent years, multi-robot systems have been widely used in many applications such as warehouse inventory tracking and automatic search and rescue operations. Probability roadmap (PRM) is a typical path planning algorithm that can determine an optimal trajectory once the robot start and goal positions are specified. However, when the number of robots in the system increases, it converges slowly and may even fail to find the solution.

In this thesis, a fuzzy inference system is proposed and combined with the probability roadmap algorithm for robot path planning. Computer simulation results in five different environments show this approach is very …

Electro-Oxidation To Convert Dissolved Organic Nitrogen And Soluble Non-Reactive Phosphorus To More Readily Removable And Recoverable Forms, Synthia P. Mallick, Donald R. Ryan, Kaushik Venkiteshwaran, Patrick J. Mcnamara, Brooke K. Mayer

Civil and Environmental Engineering Faculty Research and Publications

Conventional wastewater treatment processes cannot effectively remove dissolved organic nitrogen (DON) and soluble non-reactive phosphorus (sNRP), which can pose regulatory compliance challenges for total nitrogen and total phosphorus discharges. Moreover, DON and sNRP are not easily recoverable for beneficial reuse as part of the waste to resource paradigm. Conversion of DON and sNRP to more readily removable dissolved inorganic nitrogen (DIN) and soluble reactive phosphorus (sRP), respectively, will help meet stringent nutrient limits and facilitate nutrient recovery. In this study, electro-oxidation (EO) was evaluated for conversion of four DON compounds to DIN and five sNRP compounds to sRP. EO was …

Autonomous Vehicle Communication Strategies Modeled In Virtual Reality, Nick N. Ferenchak Ph.D

Publications

We sought to better understand how autonomous vehicle (AV) communication strategies impact human road users’ perceptions and behaviors. More specifically, we explored the impact of different external human-machine interface (eHMI) designs on understanding, task load, comfort, trust, acceptance, and reaction time. To accomplish this, we created virtual reality (VR) scenarios where human participants interacted with AVs. Participants experienced biking, driving, and pedestrian simulators and were brought back after initial testing to explore acclimation and learning effects. In terms of perceptions, the presence of an eHMI was the strongest predictor of understanding, comfort, trust, and acceptance outcomes in the statistical models …

Development Of Novel Ultra-High Performance Engineered Cementitious Composites (Uhp-Ecc) For Durable And Resilient Transportation Infrastructure, Gabriel A. Arce, Marwa Hassan, Daniel E. Game

Publications

The objective of this study was to develop novel UHP-ECC materials utilizing readily available ingredients in Region 6 for the construction and repair of transportation infrastructure. Phase one of this study focused on the development of ultra-high strength cementitious matrices by evaluating the effects of ingredient selection and mixture proportioning on the materials’ compressive strength. Variables evaluated included the mass ratios of silica fume to fly ash (SF/FA), supplementary cementitious materials to cement (SCMs/C), and ordinary sand to microsilica sand (OS/MS). Phase two of the study focused on the development of UHP-ECC materials. To this end, based on the knowledge …

Deep Reinforcement Learning-Based Project Prioritization For Rapid Post-Disaster Recovery Of Transportation Infrastructure Systems, Yongcheol Lee, Kunhee Choi Ph.D, Pedram Ghannad

Publications

Among various natural hazards that threaten transportation infrastructure, flooding represents a major hazard in Region 6's states to roadways as it challenges their design, operation, efficiency, and safety. The catastrophic flooding disaster event generally leads to massive obstruction of traffic, direct damage to highway/bridge structures/pavement, and indirect damages to economic activities and regional communities that may cause loss of many lives. After disasters strike, reconstruction and maintenance of an enormous number of damaged transportation infrastructure systems require each DOT to take extremely expensive and long-term processes. In addition, planning and organizing post-disaster reconstruction and maintenance projects of transportation infrastructures are …

Enterprise Environment Modeling For Penetration Testing On The Openstack Virtualization Platform, Vincent Karovic Jr., Jakub Bartalos, Vincent Karovic, Michal Gregus

Journal of Global Business Insights

The article presents the design of a model environment for penetration testing of an organization using virtualization. The need for this model was based on the constantly increasing requirements for the security of information systems, both in legal terms and in accordance with international security standards. The model was created based on a specific team from the unnamed company. The virtual working environment offered the same functions as the physical environment. The virtual working environment was created in OpenStack and tested with a Linux distribution Kali Linux. We demonstrated that the virtual environment is functional and its security testable. Virtualizing …

Routing Policy Choice Prediction In A Stochastic Network: Recursive Model And Solution Algorithm, Tien Mai, Xinlian Yu, Song Gao, Emma Frejinger

Research Collection School Of Computing and Information Systems

We propose a Recursive Logit (STD-RL) model for routing policy choice in a stochastic time-dependent (STD) network, where a routing policy is a mapping from states to actions on which link to take next, and a state is defined by node, time and information. A routing policy encapsulates travelers’ adaptation to revealed traffic conditions when making route choices. The STD-RL model circumvents choice set generation, a procedure with known issues related to estimation and prediction. In a given state, travelers make their link choice maximizing the sum of the utility of the outgoing link and the expected maximum utility until …

A Learning And Optimization Framework For Collaborative Urban Delivery Problems With Alliances, Jingfeng Yang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The emergence of e-Commerce imposes a tremendous strain on urban logistics which in turn raises concerns on environmental sustainability if not performed efficiently. While large logistics service providers (LSPs) can perform fulfillment sustainably as they operate extensive logistic networks, last-mile logistics are typically performed by small LSPs who need to form alliances to reduce delivery costs and improve efficiency, and to compete with large players. In this paper, we consider a multi-alliance multi-depot pickup and delivery problem with time windows (MAD-PDPTW) and formulate it as a mixed-integer programming (MIP) model. To cope with large-scale problem instances, we propose a two-stage …

The Empathetic Car: Exploring Emotion Inference Via Driver Behaviour And Traffic Context, Shu Liu, Kevin Koch, Zimu Zhou, Simon Foll, Xiaoxi He, Tina Menke, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

An empathetic car that is capable of reading the driver’s emotions has been envisioned by many car manufacturers. Emotion inference enables in-vehicle applications to improve driver comfort, well-being, and safety. Available emotion inference approaches use physiological, facial, and speech-related data to infer emotions during driving trips. However, existing solutions have two major limitations: Relying on sensors that are not built into the vehicle restricts emotion inference to those people leveraging corresponding devices (e.g., smartwatches). Relying on modalities such as facial expressions and speech raises privacy concerns. By contrast, researchers in mobile health have been able to infer affective states (e.g., …

A Cdzntese Gamma Spectrometer Trained By Deep Convolutional Neural Network For Radioisotope Identification, Sandeep K. Chaudhuri, Joshua W. Kleppinger, Ritwik Nag, Kaushik Roy, Rojina Panta, Forest Agostinelli, Amit Sheth, Utpal N. Roy, Ralph B. James, Krishna C. Mandal

Publications

We report the implementation of a deep convolutional neural network to train a high-resolution room-temperature CdZnTeSe based gamma ray spectrometer for accurate and precise determination of gamma ray energies for radioisotope identification. The prototype learned spectrometer consists of a NI PCI 5122 fast digitizer connected to a pre-amplifier to recognize spectral features in a sequence of data. We used simulated preamplifier pulses that resemble actual data for various gamma photon energies to train a CNN on the equivalent of 90 seconds worth of data and validated it on 10 seconds worth of simulated data.

Deep Learning-Based Penetration Depth Prediction In Al/Cu Laser Welding Using Spectrometer Signal And Ccd Image, Sanghoon Kang, Minjung Kang, Yong Hoon Jang, Cheolhee Kim

Mechanical and Materials Engineering Faculty Publications and Presentations

In the laser welding of thin Al/Cu sheets, proper penetration depth and wide interface bead width ensure stable joint strength and low electrical conductance. In this study, we proposed deep learning models to predict the penetration depth. The inputs for the prediction models were 500 Hz-sampled low-cost charge-coupled device (CCD) camera images and 100 Hz-sampled spectral signals. The output was the penetration depth estimated from the keyhole depth measured coaxially using optical coherence tomography. A unisensor model using a CCD image and a multisensor model using a CCD image and the spectrometer signal were proposed in this study. The input …

Evaluation Of In-Cab Air Quality For Nonroad Diesel Construction Equipment, Phil Lewis, Sherif El Khouly, Adam Mayer, Jeremy Johnson

The Professional Constructor

Previous research indicates that air quality near the cabs of nonroad diesel equipment may exceed recommended exposure limits for certain pollutants. The objective of this case study was to collect and analyze air pollutant data near the cabs of nonroad diesel equipment while performing real world activities. Using state-of-the-art instrumentation, the research team conducted 24 tests on nine different items of nonroad equipment. The team collected data related to pollutant concentrations of carbon monoxide, carbon dioxide, nitric oxide, nitrogen dioxide, particulate matter, and black carbon. Average concentrations of carbon monoxide and nitric oxide did not exceed published exposure limits on …

Understanding And Avoiding Ai Failures: A Practical Guide, Robert Williams, Roman Yampolskiy

Faculty and Staff Scholarship

As AI technologies increase in capability and ubiquity, AI accidents are becoming more common. Based on normal accident theory, high reliability theory, and open systems theory, we create a framework for understanding the risks associated with AI applications. This framework is designed to direct attention to pertinent system properties without requiring unwieldy amounts of accuracy. In addition, we also use AI safety principles to quantify the unique risks of increased intelligence and human-like qualities in AI. Together, these two fields give a more complete picture of the risks of contemporary AI. By focusing on system properties near accidents instead of …

Potential Impact Of Contour Bunds On Diclofenac Removal For Stormwater Control In Rangeland Applications, Braden Alan Whitehead

Master's Theses

Diclofenac (DCF) and other emerging contaminants have been found in environments worldwide. These contaminants may enter the environment due to the application of treated wastewater, biosolids and direct excrement related to veterinary application. Leakage from the soils toward the groundwater is largely controlled by sorption and microbial degradation. Most studies on the environmental fate of DCF have focused on degradation during wastewater treatment processes. However, little is known about their behavior in soil. In this study, the combined effect of adsorption and degradation of diclofenac has been investigated in four (4) 24 ft³ agricultural soil-filled beds designed to mimic …