Computational Engineering Commons^™

Elevated Temperature Progressive Damage And Failure Of Duplex Stainless Steel, Darren P. Luke

Civil Engineering ETDs

Ductile failure of metals has been the focus of research efforts within academia and industry for many years since it is tremendously important for understanding the failure of structures under extreme loading conditions. However, limited research has been dedicated to elevated temperature ductile failure, which is critical for evaluating catastrophic events such as industrial, structural or shipping vessel fires. A detailed investigation was conducted on the structural response of Duplex Stainless Steel at elevated temperatures. The temperature dependence of elastic modulus, yield strength, ultimate strength, and ductility was measured up to 1000°C and a continuum damage plasticity model was developed. …

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify, Map, Apply, …

Blokus Game Solver, Chin Chao

Computer Engineering

Blokus (officially pronounced as “Block us”) is an abstract strategy board game with transparent Tetris-shaped, color pieces that players are trying to place onto the board. However, the players can only place a piece that touches at least one corner of their own pieces on the board. The ultimate goal of the game is to place as many pieces onto the board as a player can while blocking off the opponent’s ability to place more pieces onto the board. Each player has pieces with different shapes and sizes that can be placed onto the board, where each block within a …

Fingerprint Database Privacy Guard: An Open-Source System That Secures Fingerprints With Locality Sensitive Hashing Algorithms, Enrique Sanchez

Computer Science and Computer Engineering Undergraduate Honors Theses

Fingerprint identification is one of the most accurate sources of identification, yet it is not widely used in public facilities for security concerns. Moreover, the cost of fingerprint system is inaccessible for small-budget business because of their high cost. Therefore, this study created an open-source solution to secure fingerprint samples in the database while using low-cost hardware components. Locality Sensitive Hashing Algorithms such as ORB and Image hash were compared in this study as a potential alternative to SURF. To test the design, fifteen samples were collected and stored in a database without verifying the quality of the samples. Then, …

A Computational Analysis Of The Gradient Concentration Profile Of Deet And The Mosquito Behavioral Response, Brandon Carver

Master's Theses

DEET is a common active ingredient in most spatial repellents. DEET is also a volatile organic compound. DEET prevents mosquitoes from detecting and coming into contact with an human individual. Gas sensing technologies such as metal oxide semiconductor sensors can detect VOCs. The World Health Organization provides the majority of efficacy testing methods. This research adapts methods from the WHO and use of MOS sensors to further understand how and why DEET affects mosquitos. A custom developed system is used to measure DEET dissipation and observe mosquito behavioral response to the DEET. DEET dissipations and mosquito behavior is measured within …

Landmine Detection Using Semi-Supervised Learning., Graham Reid

Electronic Theses and Dissertations

Landmine detection is imperative for the preservation of both military and civilian lives. While landmines are easy to place, they are relatively difficult to remove. The classic method of detecting landmines was by using metal-detectors. However, many present-day landmines are composed of little to no metal, necessitating the use of additional technologies. One of the most successful and widely employed technologies is Ground Penetrating Radar (GPR). In order to maximize efficiency of GPR-based landmine detection and minimize wasted effort caused by false alarms, intelligent detection methods such as machine learning are used. Many sophisticated algorithms are developed and employed to …

A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson

Computer Science and Computer Engineering Undergraduate Honors Theses

Cooperative 3D printing is an emerging technology that aims to increase the 3D printing speed and to overcome the size limit of the printable object by having multiple mobile 3D printers (printhead-carrying mobile robots) work together on a single print job on a factory floor. It differs from traditional layer-by-layer 3D printing due to requiring multiple mobile printers to work simultaneously without interfering with each other. Therefore, a new approach for slicing a digital model and generating commands for the mobile printers is needed, which has not been discussed in literature before. We propose a chunk-by-chunk based slicer that divides …

Fluid Agitation Studies For Drug Product Containers Using Computational Fluid Dynamics, Matthew Hiroki Ichinose

Master's Theses

At Amgen, the Automated Vision Inspection (AVI) systems capture the movement of unwanted particles in Amgen's drug product containers. For quality inspection, the AVI system must detect these undesired particles using a high speed spin-stop agitation process. To better understand the fluid movements to swirl the particles away from the walls, Computational Fluid Dynamics (CFD) is used to analyze the nature of the two phase flow of air and a liquid solution.

Several 2-D and 3-D models were developed using Fluent to create simulations of Amgen's drug product containers for a 1 mL syringe, 2.25 mL syringe, and a 5 …

Population Curation In Swarms: Predicting Top Performers, Ryan W. Heller

Master's Theses

In recent years, new Artificial Intelligence technologies have mimicked examples of collective intelligence occurring in the natural world including flocks of birds, schools of fish, and swarms of bees. One company in particular, Unanimous AI, built a platform (UNU Swarm) that enables a group of humans to make decisions as a single mind by forming a real-time closed-loop feedback system for individuals. This platform has proven the ability to amplify the predictive ability of groups of humans in realms including sports, medicine, politics, finance, and entertainment. Previous research has demonstrated it is possible to further enhance knowledge accumulation within a …

Plataforma Computacional Para El Tratamiento De Habilidades Cognitivas Para Niños Con Autismo, Elkin Leandro Rodriguez Zamudio

Ingeniería en Automatización

En el año 2013 se publicó una nueva versión del manual diagnóstico y estadístico para las enfermedades mentales DSM-V (Manual diagnóstico y estadístico de los trastornos mentales). Entre otros cambios que no son motivo de este trabajo la nueva versión Fusiona varios de los trastornos generalizados del desarrollo, trastorno generalizado del desarrollo no especificado, y el síndrome de asperger en lo que ahora se conoce como ‘trastorno del espectro autista’ (TEA), el cual es un conjunto de alteraciones heterogéneas a nivel del neuro-desarrollo que normalmente inicia desde la infancia y que implica alteraciones en la comunicación e interacción social, también …

Large Eddy Simulations Of Vertical Jets In Crossflow, Pranaya Pokharel

LSU Doctoral Dissertations

Jets in crossflow (JICF) have applications ranging from oil spill to film cooling of turbine blades. Hence, an understanding of the flow physics is important. The majority of the research has been conducted for low velocity ratios between jet and crossflow with round jets. JICF is demonstrated to behave differently for high velocity ratios and different jet shapes. Circular and rectangular jets are commonly used in aircraft applications. Current study focuses on high velocity ratio JICF issuing from both circular and rectangular exit.

For simulating JICF, an in house code “Chem3D” is used with Large Eddy Simulation (LES) to model …

Numerical Study Of Liquid Atomization And Breakup Using The Volume Of Fluid Method In Ansys Fluent, Sai Saran Kandati

LSU Master's Theses

The spherical metal particles produced from the centrifugal atomization process have been the topic of numerous theoretical, experimental and numerical studies from the past few years. This atomization process uses centrifugal force to break-up molten material into spherical droplets, which are quenched into solidified granules by the flow of cold air on the spherical droplets. In the present work, a transient three-dimensional multiphase CFD model is applied to three different materials: Molten slag, aqueous glycerol solution, and molten Ni-Nb to study the influence of the dimensionless parameters on the centrifugal atomization outcome.

Results from numerical experiments indicated that the droplet …

New Methods For Understanding And Controlling The Self-Assembly Of Reacting Systems Using Coarse-Grained Molecular Dynamics, Stephen Thomas

Boise State University Theses and Dissertations

This research aims at developing new computational methods to understand the molecular self-assembly of reacting systems whose complex structures depend on the thermodynamics of mixing, reaction kinetics, and diffusion kinetics. The specific reacting system examined in this study is epoxy, cured with linear chain thermoplastic tougheners whose complex microstructure is known from experiments to affect mechanical properties and to be sensitive to processing conditions. Mesoscale simulation techniques have helped to bridge the length and time scales needed to predict the microstructures of cured epoxies, but the prohibitive computational cost of simulating experimentally relevant system sizes has limited their impact. In …

The Development And Validation Of Sinatra: A Three-Dimensional Direct Simulation Monte Carlo (Dsmc) Code Written In Object-Oriented C++ And Performed On Cartesian Grids, David Matthew Galvez

Master's Theses

The field of Computational Fluid Dynamics (CFD) primarily involves the approximation of the Navier-Stokes equations. However, these equations are only valid when the flow is considered continuous such that molecular interactions are abundant and predictable. The Knudsen number, $Kn$, which is defined as the ratio of the flow's mean free path, $\lambda$, to some characteristic length, $L$, quantifies the continuity of any flow, and when this parameter is large enough, alternative methods must be employed to simulate gases. The Direct Simulation Monte Carlo (DSMC) method is one which simulates rarefied gas flows by directly simulating the particles that compose the …

Data-Driven Uncertainty Quantification Interpretation With High Density Regions, Matthew Gregor Peterson

Computer Science ETDs

In a time when data is being constantly generated by phones, vehicles, sensor net- works, social media, etc. detecting anomalies with in the data can be very crucial. In cases where we know little prior knowledge about the data, it becomes difficult to extract uncertainty about our results. In this thesis, we will propose a framework in which we can extract uncertainty distributions from data-driven modeling prob- lems. We will show some concrete examples of how to apply framework and provide some insight into what the uncertainty distributions are telling us using High Density Regions (HDRs).

Reward Allocation For Maximizing Energy Savings In A Transportation System, Adewale O. Oduwole

Masters Theses

Transportation has a major impact on our society and environment, contributing 70% of U.S petroleum use, 28% of U.S. greenhouse gas (GHG) emissions, over 34,000 fatalities and 2.2 million injuries in 2013. Punitive approaches to used to tackle environmental issues in the transportation sector, such as congestion pricing have been well documented, although the use of incentives or rewards lags behind in comparison. In addition to the use of more fuel-efficient, alternate energy vehicles and various other energy reduction strategies; energy consumption can be lowered through incentivizing alternative modes of transportation. This paper focused on modifying travelers’ behavior by providing …

Predicting River Stage Using Recurrent Neural Networks, Eric Rohli

LSU Master's Theses

River stage prediction is an important problem in the water transportation industry. Accurate river stage predictions provide crucial information to barge and tow boat operators, port terminal captains, and lock management officials. Shallow river levels caused by prolonged drought impact the loading capacity of barges and tow boats. High river levels caused by excessive rainfall or snowmelt allow for greater tow capacities but make downstream transportation and lock management risky. Current academic river height prediction systems utilize either time series statistical analysis or machine learning algorithms to forecast future river heights, but systems that combine these two areas often limit …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …

Effect Of Material Viscoelasticity On Frequency Tuning Of Dielectric Elastomer Membrane Resonators, Liyang Tian

Electronic Thesis and Dissertation Repository

Dielectric elastomers (DEs) capable of large voltage-induced deformation show promise for applications such as resonators and oscillators. However, the dynamic performance of such vibrational devices is not only strongly affected by the nonlinear electromechanical coupling and material hyperelasticity, but also significantly by the material viscoelasticity. The material viscoelasticity of DEs originates from the highly mobile polymer chains that constitute the polymer networks of the DE. Moreover, due to the multiple viscous polymer subnetworks, DEs possess multiple relaxation processes. Therefore, in order to predict the dynamic performance of DE-based devices, a theoretical model that accounts for the multiple relaxation processes is …

Jasmint: Language To User-Friendly Ast With Emphasis On Translation, John E. Bradbury

Computer Science and Software Engineering

The goal of this project was to create a language (JASMINT) which would be easily transformable into other languages. With this, a library could be built which provides a rich set of functions, including typechecking, interpreting, and serialization, in order to make user modules easy to write. These modules are able to translate this AST into other languages and through the translation blocks can add new functionalities to JASMINT. The final state of the project at submission includes a library which handles all features except dynamic memory, transpilers (JasmintCxxTranspiler and JasmintPythonTranspiler) which handle most features except classes and dynamic memory, …

Roborodentia Robot: Treadbot, Stephen C. Schmidt

Computer Science and Software Engineering

This document is a summary of my contest entry to the 2018 Cal Poly Roborodentia competition. It is meant to be a process overview and design outline of the mechanical, electrical, and software components of my robot.

Vehicle Pseudonym Association Attack Model, Pierson Yieh

Master's Theses

With recent advances in technology, Vehicular Ad-hoc Networks (VANETs) have grown in application. One of these areas of application is Vehicle Safety Communication (VSC) technology. VSC technology allows for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that enhance vehicle safety and driving experience. However, these newly developing technologies bring with them a concern for the vehicular privacy of drivers. Vehicles already employ the use of pseudonyms, unique identifiers used with signal messages for a limited period of time, to prevent long term tracking. But can attackers still attack vehicular privacy even when vehicles employ a pseudonym change strategy? The major contribution …

Artificial Neural Network-Based Robotic Control, Justin Ng

Master's Theses

Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.

Automated Pruning Of Greenhouse Indeterminate Tomato Plants, Joey M. Angeja

Master's Theses

Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background …

Towards Autonomous Localization Of An Underwater Drone, Nathan Sfard

Master's Theses

Autonomous vehicle navigation is a complex and challenging task. Land and aerial vehicles often use highly accurate GPS sensors to localize themselves in their environments. These sensors are ineffective in underwater environments due to signal attenuation. Autonomous underwater vehicles utilize one or more of the following approaches for successful localization and navigation: inertial/dead-reckoning, acoustic signals, and geophysical data. This thesis examines autonomous localization in a simulated environment for an OpenROV Underwater Drone using a Kalman Filter. This filter performs state estimation for a dead reckoning system exhibiting an additive error in location measurements. We evaluate the accuracy of this Kalman …

N-Slope: A One-Class Classification Ensemble For Nuclear Forensics, Justin Kehl

Master's Theses

One-class classification is a specialized form of classification from the field of machine learning. Traditional classification attempts to assign unknowns to known classes, but cannot handle novel unknowns that do not belong to any of the known classes. One-class classification seeks to identify these outliers, while still correctly assigning unknowns to classes appropriately. One-class classification is applied here to the field of nuclear forensics, which is the study and analysis of nuclear material for the purpose of nuclear incident investigations. Nuclear forensics data poses an interesting challenge because false positive identification can prove costly and data is often small, high-dimensional, …

Resource Brokering In Grid Computing, Adrian T. Bienkowski

Electronic Thesis and Dissertation Repository

Grid Computing has emerged in the academia and evolved towards the bases of what is currently known as Cloud Computing and Internet of Things (IoT). The vast collection of resources that provide the nature for Grid Computing environment is very complex; multiple administrative domains control access and set policies to the shared computing resources. It is a decentralized environment with geographically distributed computing and storage resources, where each computing resource can be modeled as an autonomous computing entity, yet collectively can work together. This is a class of Cooperative Distributed Systems (CDS). We extend this by applying characteristic of open …

Modeling Of Swimming Cells From Nano-Scale To Micro-Scale, Yicheng Zhao

McKelvey School of Engineering Theses & Dissertations

Certain human genetic diseases -- primary ciliary dyskinesia, infertility, and hydrocephalus -- are characterized by changes in beat frequency and waveform of cilia and flagella. Chlamydomonas reinhardtii, which is a single-cell green alga about ten micrometers in diameter that swims with two flagella, serves as an excellent biological model because its flagella share the same structure and genetic background as mammalian cilia and flagella. This study uses the finite element method to investigate the behavior of C. reinhardtii swimming from nano-scale to micro-scale. At the device-level, micro-scale modeling indicates that well-designed acoustic microfluidic devices can be used to trap groups …

Re-Evaluating Performance Measurement: New Mathematical Methods To Address Common Performance Measurement Challenges, Jordan David Benis

Electronic Theses and Dissertations

Performance Measurement is an essential discipline for any business. Robust and reliable performance metrics for people, processes, and technologies enable a business to identify and address deficiencies to improve performance and profitability. The complexity of modern operating environments presents real challenges to developing equitable and accurate performance metrics. This thesis explores and develops two new methods to address common challenges encountered in businesses across the world. The first method addresses the challenge of estimating the relative complexity of various tasks by utilizing the Pearson Correlation Coefficient to identify potentially over weighted and under weighted tasks. The second method addresses the …

The 3d Abstract Tile Assembly Model Is Intrinsically Universal, Aaron Koch, Daniel Hader, Matthew J. Patitz

Computer Science and Computer Engineering Undergraduate Honors Theses

In this paper, we prove that the three-dimensional abstract Tile Assembly Model (3DaTAM) is intrinsically universal. This means that there is a universal tile set in the 3DaTAM which can be used to simulate any 3DaTAM system. This result adds to a body of work on the intrinsic universality of models of self-assembly, and is specifically motivated by a result in FOCS 2016 showing that any intrinsically universal tile set for the 2DaTAM requires nondeterminism (i.e. undirectedness) even when simulating directed systems. To prove our result we have not only designed, but also fully implemented what we believe to be …