Defenses

Title: Modeling Syndromic Surveillance and Outbreaks in Subpopulations

Date: Monday, Dec. 16, 2019

Time: 12:00pm

Location: Martin Hall  EGR-2164

Committee Members:

Professor Jeffrey Herrmann

Professor Robert Gold
Assistant Professor Allison Reilly

Professor Linda Schmidt

Assistant Professor Monifa Vaughn-Cooke

Abstract:

This research is motivated by the need to assist resource limited communities by enhancing the use of syndromic surveillance (SyS) systems and data. Public health agencies and academic researchers have developed and implemented SyS systems as a pattern recognition tool to detect a potential disease outbreak using pre-diagnostic data. SyS systems collect data from multiple types of sources: absenteeism records, over the counter medicine sales, chief complaints, web queries, and more. It could be expensive, however, to gather data from every available source; subsequently, gathering information about only some subpopulations may be a desirable option. This raises questions about the differences between subpopulation behavior and which subpopulations’ data would give the earliest, most accurate warning of a disease outbreak.

To investigate the feasibility of using subpopulation data, this research will gather and organize SyS data by subpopulation (separated by population characteristics such as age or location) and identify how well the SyS data correlates to the real world disease progression. This research will study SyS how reports of Influenza-like-illness (ILI) in subpopulations represent the disease behavior. The first step of the research process is to understand how SyS is used in environments with varying levels of resources and what gaps are present in SyS modeling techniques. Various modeling techniques and applications are assessed, specifically the Susceptible Infected Recovered “SIR” model and associated modifications of that model. Through data analysis, well correlated subpopulations will be identified and compared to actual disease behavior and SyS data sets.  A model referred to as ModSySIR will be presented that uses real world community data ideal for ease of use and implementation in a resource limited community. The highest level research objective is to provide a potential data analysis method and modeling approach to inform decision making for health departments using SyS systems that rely on fewer resources.

Title: Phonon mediated thermal transport in transition-metal dichalcogenides

Date: Tuesday, Dec. 3rd, 2019

Time: 11:00am

Location: Martin Hall  EGR-2164

Committee Members:

Professor Peter Chung (Chair)

Professor Bao Yang

Professor Agis Iliadis (Dean’s Representative, Electrical and Computer Science Department)

Professor Abhijit Dasgupta

Professor Patrick McCluskey

Dr. Sina Najmaei (Special Member for the committee, ARL research scientist)

Title: New Methodology for Predicting Ultimate Capacity of One-Sided Composite Patch Repaired Cracked Aluminum Plate

Date: Wednesday, Dec 11^th, 2019

Time: 10:00am

Location: Martin Hall, EGR-2164

Committee:

Professor Hugh Bruck (Chair)

Professor Peter Chung

Professor Abhijit Dasgupta

Professor Teng Li

Professor Sung Lee (Dean’s Representative, Aerospace Department)

Abstract

Composite patch repairs are an alternative to traditional weld repair methods to address cracking in aluminum plates. Analytical and numerical design methods use linear elastic fracture mechanics (LEFM) that do not account for elastic-plastic crack tip behavior demonstrated in static tests of one-sided patch repaired ductile panels. This research used digital image correlation (DIC) and three-dimensional finite element analysis (FEA) with first order elements to study crack tip effects due to the one-sided composite patch applied to center crack tension (CCT) specimens loaded monotonically to failure. The measurable effects on crack tip behavior due to the composite patch were ultimate tensile load increase of more than 100% and a total achieved crack opening displacement (COD) increase of 20% over the unpatched behavior. Crack tip fracture behavior was found to be an intrinsic property of the aluminum and directly related to the COD independent of the one-sided composite patch. Increased capacity was related to accumulation of large-strain free surface area and through thickness volume ahead of the crack tip. Test data and numerical predictions correlated with measured load, strain, displacement fields, and J-integral behavior. Correlation of displacement fields with HRR and K fields established a state of small scale yielding prior to failure. Data and predictions indicated critical COD occurs when unpatched and patched large strain area is equivalent, which occurs before crack tip behavior transitions from small scale to large scale yielding and crack growth. Identifying a critical COD for both small and large scale one-sided patch repaired cracked ductile panels results in a predicted failure closer to the ultimate tensile load and 80% greater than predicted with LEFM methods.

Observations and predictions demonstrated in this research resulted in three scientific contributions: (1) development of criteria to determine crack growth in cracked ductile panels repaired with a one-sided composite patch using a critical COD, (2) development of a three-dimensional FEA to study development of the plastic zone and evolution of the large-strain region ahead of the crack tip, and (3) development of a numerical methodology to predict ultimate tensile load capacity of cracked ductile panels repaired with a one-sided composite patch

Title: Design and Development of potassium formate based Atmospheric Water Harvester

Date: Monday, Nov. 25, 2019

Time: 1:30PM

Location: EGR-3164 Martin Hall (Aerospace conference room)

Committee Members: 

Dr. Jungho Kim, Chair

Dr. Yunho Hwang

Dr. Gary Pertmer

Title: MAXIMIZING THE FINANCIAL RETURNS OF USING LIDAR SYSTEMS IN WIND FARMS FOR YAW ERROR CORRECTION APPLICATIONS 

Date: Tuesday, November 5th, 2019

Time: 8:00am

Location: DeWalt Conference Room Martin Hall (EGR-2162

Abstract:

Wind energy is an important source of renewable energy with significant untapped potential around the world. However, the cost of wind energy production is high and efforts to lower the cost of energy generation will help enable more widespread use of wind energy. Ideally, wind turbines have to be aligned with wind flow at all times. However, this is not the case and there exists and angle between a wind turbine nacelle’s central axis and the wind flow. This angle is called yaw error. Yaw error lowers the efficiency of turbines as well as lowers the reliability of key components in turbines. LIDAR devices can correct the yaw error; however, they are expensive and there is a trade-off between their costs and benefits. In this dissertation, a stochastic discrete-event simulation is developed that models the operation of a wind farm. By maximizing the Net Present Value (NPV) changes associated with using LIDAR devices in a wind farm, the optimum number of LIDAR devices and their associated turbine stay time will be determined. These optimum values are a function of number of turbines in the wind farm for specific turbine sizes. The outcome of this dissertation will help wind farm owners and operators to make informed decisions about purchasing LIDAR devices for their wind farms.

Title: WATER, ION, AND GRAPHENE: AN ODYSSEY THROUGH THE MOLECULAR SIMULATIONS

Date: Wednesday, November 6th, 2019

Time: 10:00am

Location: DeWalt Martin Hall (EGR2162)

Committee Members: 

Associate Professor Siddhartha Das, Chair

Associate Professor Amir Riaz

Associate Professor Peter Chung

Associate Professor Yifei Mo

Minta Martin Professor Liangbing Hu, Dean’s Representative

Title of thesis: Investigation of Swirl Assisted Colorless Distributed Combustion (CDC) for Gas Turbine Application

Date: Friday, October 25th, 2019

Time: 3:30pm

Location: EGR 2164

Committee Member:

Professor Ashwani Gupta, Chair

Professor Bao Yang

Associate Professor Gary Pertmer

Abstract: 

Colorless Distributed Combustion (CDC) is a novel method to enhance flame stability and thermal field uniformity, increase combustion efficiency and reduce pollutants emission, including noise. The focus of this thesis is to investigate swirl-assisted distributed combustion at high thermal intensity for gas turbine application. This thesis investigates the impact of fuel enrichment on CDC conditions by using naphthalene as a fuel additive in ethanol to increase the heating value without compromising ultra-low emissions, in addition to investigating how CDC fuel flexibility can mitigate instability associated with hydrogen enriched alternate fuels. To better predict and implement CDC design in future gas turbine combustors a distributed combustion index (DCI) will be developed to determine the impact of heat release intensity, equivalence ratio, preheat temperature and entrainment gas on distributed conditions. Lastly, the impact of flowfield interaction on achieving CDC condition will be examined for enhanced understanding of mixing required for CDC. 

Title: DEVELOPING HYBRID PHM MODELS FOR PIPELINE PITTING CORROSION, CONSIDERING DIFFERENT TYPES OF UNCERTAINTY AND CHANGES IN OPERATIONAL CONDITIONS

Date: Monday, Oct. 21st, 2019

Time: 11:00 am

Location: Martin Hall EGR-0159

Committee Members:

Assistant Professor Katrina M. Groth, Chair/Advisor

Professor Mohammad Modarres

Professor Ali Mosleh

Assistant Professor Mark D. Fuge

Professor Mohamad Al-Sheikhly, Dean’s Representative