Engineering Commons^™

Aging Study Of Silver-Exchanged Mordenite And Silver-Functionalized Silica Aerogel In Dry Air, Humid Air, No And No2, Seungrag Choi

Dissertations - ALL

Iodine-129 (129I) is one of the volatile radioactive species in the off-gas streams generated from the spent nuclear fuel reprocessing system, and it is essential to remove 129I vapor because 129I has a long half-life (1.6 x 107 years) and can be fatal to the human body if released to the environment. Radioactive iodine vapor can be effectively captured by silver containing adsorbents such as silver exchanged mordenite (Ag0Z) and silver functionalized silica aerogel (Ag0-aerogel) used in this study. However, the aging impact of off-gas streams on the adsorbents is one of major issues in the removal of radioactive iodine …

Analysis Of Multiple Degree-Of-Freedom Oscillatory Aquatic Propulsion, Seth Alan Brooks

Dissertations - ALL

Propulsive performance and flow field data were experimentally measured for a two degree-of-freedom fish platform. The fish platform was designed and constructed based on the yellowfin tuna (\textit{Thunnus albacares}) that is known to be both fast and efficient. This work extends the current understanding of oscillatory aquatic propulsion to a three-dimensional fish platform with full volume flow field data and propulsive performance. A parametric sweep of trailing-edge amplitude of the caudal fin ($A$), heave-to-pitch ratio ($h^*$), and phase offset between the two degrees-of-freedom ($\phi$) was used to explore a parameter space that encompasses and extends beyond the known biological domain. …

Algorithm Hardware Codesign For High Performance Neuromorphic Computing, Haowen Fang

Dissertations - ALL

Driven by the massive application of Internet of Things (IoT), embedded system and Cyber Physical System (CPS) etc., there is an increasing demand to apply machine intelligence on these power limited scenarios. Though deep learning has achieved impressive performance on various realistic and practical tasks such as anomaly detection, pattern recognition, machine vision etc., the ever-increasing computational complexity and model size of Deep Neural Networks (DNN) make it challenging to deploy them onto aforementioned scenarios where computation, memory and energy resource are all limited. Early studies show that biological systems' energy efficiency can be orders of magnitude higher than that …

Exploiting Building Demand Flexibility Through Machine Learning For Building-To-Grid Integration, Hannah Charlene Fontenot

Dissertations - ALL

Demand flexibility – the ability to adjust a building's load profile across different timescales – is a key aspect of the ongoing effort to increase interconnectivity between buildings and the power grid. By harnessing their demand flexibility, buildings can provide significant benefits to the grid and bolster grid resilience and reliability. To facilitate the transition toward the "smart grid", new and intelligent control approaches are required that can seamlessly integrate building, occupant, and grid data and effectively control multiple building assets to provide grid services while maintaining occupants' required thermal comfort levels and reducing the building's overall energy consumption and …

Adsorption Of Organic Iodides On Reduced Silver Functionalized Silica Aerogel, Siqi Tang

Dissertations - ALL

In the nuclear waste reprocessing, radioactive iodine is released in both organic and inorganic forms into off-gas streams. Due to its properties of long half-life and accumulation in human bodies, the radioactive iodine is required to be removed by the Environmental Protection Agency (EPA) and Nuclear Regulatory Commission (NRC). In this presented work, the removal of organic iodides is studied particularly. Unlike that of inorganic iodine, the organic iodides were not well studied because of the low concentrations and the corresponding technical difficulties. Most of the studies on the organic iodides are semi-quantified, focusing on the performances of the adsorption …

Flow Interaction Between Turbomachine Blade Row And Flow Resistance Medium, Tong Lin

Dissertations - ALL

This research investigates the fluid-dynamic interaction between close-coupled axial turbomachines and surrounding components, e.g., heat-exchangers, filters, or cooling fins in high-density computer servers, and its effects on turbomachine and system performance. The importance of this research is that the flow interaction effect occurs in every scenario that requires system compactness.

Firstly, a combined experimental and 3-D computational study on an off-the-shelf server cooling fan is performed, showing that the fan performance has little changed. However, the system performance can be very different since the server cooling has a large hub-to-tip radius ratio, which effectively blocks the high resistance media's (HRM) …

Design And Development Of 2d Functional Semiconductor Nanocrystals, Andrew Hunter Davis

Dissertations - ALL

Anisotropic nanocrystals (NCs) have become of keen interest in recent years, especially for applications in optoelectronic devices due to their directionally oriented emissions, narrow emission spectra, and suitable morphologies for device integration. Of the desired anisotropic NCs, two-dimensional (2D) NCs are of profound interest, due to their impressive optical and electronic properties as well as their prospective advantages towards applications in layered optoelectronic devices, such as solar cells. However, 2D NCs face many challenges, including limited synthetic derivation, as well as decreased stability and optical response, due to their large surface-to-volume ratio and reactive planar surface increasing surface defect state …

Some New Results In Distributed Tracking And Optimization, Pranay Sharma

Dissertations - ALL

The current age of Big Data is built on the foundation of distributed systems, and efficient distributed algorithms to run on these systems.With the rapid increase in the volume of the data being fed into these systems, storing and processing all this data at a central location becomes infeasible. Such a central \textit{server} requires a gigantic amount of computational and storage resources. Even when it is possible to have central servers, it is not always desirable, due to privacy concerns. Also, sending huge amounts of data to such servers incur often infeasible bandwidth requirements.

In this dissertation, we consider two …

Data-Driven Protection Of Transformers, Phase Angle Regulators, And Transmission Lines In Interconnected Power Systems, Pallav Kumar Bera

Dissertations - ALL

This dissertation highlights the growing interest in and adoption of machine learning approaches for fault detection in modern electric power grids. Once a fault has occurred, it must be identified quickly and a variety of preventative steps must be taken to remove or insulate it. As a result, detecting, locating, and classifying faults early and accurately can improve safety and dependability while reducing downtime and hardware damage. Machine learning-based solutions and tools to carry out effective data processing and analysis to aid power system operations and decision-making are becoming preeminent with better system condition awareness and data availability.

Power transformers, …

The Influence Of Trailing Edge Shape And Kinematics On Bio-Inspired Pitching Panels, Justin Thomas King

Dissertations - ALL

Recently, some engineers have turned to the study of swimming and flying animals to provide insight into the design of vehicles that move through air or water. For certain animals swimming in water, thrust is generated primarily by either a caudal fin or fluke located at the posterior end of the swimmer. It has been argued extensively in the existing research literature that biological propulsors of high aspect ration that also display forked, or lunate, planforms are representative of optimized propulsor geometries with respect to propulsive performance. However, recent experimental and computational work on purely pitching panels has demonstrated that …

Mitigating Insider Threat Risks In Cyber-Physical Manufacturing Systems, Jinwoo Song

Dissertations - ALL

Cyber-Physical Manufacturing System (CPMS)—a next generation manufacturing system—seamlessly integrates digital and physical domains via the internet or computer networks. It will enable drastic improvements in production flexibility, capacity, and cost-efficiency. However, enlarged connectivity and accessibility from the integration can yield unintended security concerns. The major concern arises from cyber-physical attacks, which can cause damages to the physical domain while attacks originate in the digital domain. Especially, such attacks can be performed by insiders easily but in a more critical manner: Insider Threats.

Insiders can be defined as anyone who is or has been affiliated with a system. Insiders have knowledge …

Effects Of Acid Deposition And Changing Climate On The Hydrochemistry And Critical Loads Of Watersheds In The Adirondack Region Of New York, Shuai Shao

Dissertations - ALL

Despite decreases in acidic deposition since the 1970s, the recovery of surface waters from acidification has been limited primarily due to the depletion of exchangeable base cations, net mineralization of organic sulfur and nitrogen and release of previously retained SO42- and NO3-, and increases in concentrations of naturally occurring organic acids from soil. The future recovery of stream chemistry from acidic deposition may be altered by projected increases in temperature and precipitation associated with a changing climate. The goals of this study were to conduct a modeling analysis of the response of soils and streams in the Adirondack Park, New …

Mathematical Optimization Algorithms For Model Compression And Adversarial Learning In Deep Neural Networks, Tianyun Zhang

Dissertations - ALL

Large-scale deep neural networks (DNNs) have made breakthroughs in a variety of tasks, such as image recognition, speech recognition and self-driving cars. However, their large model size and computational requirements add a significant burden to state-of-the-art computing systems. Weight pruning is an effective approach to reduce the model size and computational requirements of DNNs. However, prior works in this area are mainly heuristic methods. As a result, the performance of a DNN cannot maintain for a high weight pruning ratio. To mitigate this limitation, we propose a systematic weight pruning framework for DNNs based on mathematical optimization. We first formulate …

Optical Printing Of Multiscale Hydrogel Structures, Zheng Xiong

Dissertations - ALL

Hydrogel has been a promising candidate to recapitulate the chemical, physical and mechanical properties of natural extracellular matrix (ECM), and they have been widely used for tissue engineering, lab on a chip and biophotonics applications. A range of optical fabrication technologies such as photolithography, digital projection stereolithography and laser direct writing have been used to shape hydrogels into structurally complex functional devices and constructs. However, it is still greatly challenging for researchers to design and fabricate multiscale hydrogel structures using a single fabrication technology.

To address this challenge, the goal of this work is the design and develop novel multimode …

Augmented Human Machine Intelligence For Distributed Inference, Baocheng Geng

Dissertations - ALL

With the advent of the internet of things (IoT) era and the extensive deployment of smart devices and wireless sensor networks (WSNs), interactions of humans and machine data are everywhere. In numerous applications, humans are essential parts in the decision making process, where they may either serve as information sources or act as the final decision makers. For various tasks including detection and classification of targets, detection of outliers, generation of surveillance patterns and interactions between entities, seamless integration of the human and the machine expertise is required where they simultaneously work within the same modeling environment to understand and …

One-Bit Compressed Sensing In The Presence Of Noise, Swatantra Kafle

Dissertations - ALL

Many modern real-world systems generate large amounts of high-dimensional data stressing the available computing and signal processing systems. In resource-constrained settings, it is desirable to process, store and transmit as little amount of data as possible. It has been shown that one can obtain acceptable performance for tasks such as inference and reconstruction using fewer bits of data by exploiting low-dimensional structures on data such as sparsity. This dissertation investigates the signal acquisition paradigm known as one-bit compressed sensing (one-bit CS) for signal reconstruction and parameter estimation.

We first consider the problem of joint sparse support estimation with one-bit measurements …

Performance Analysis And Learning Algorithms In Advanced Wireless Networks, Xueyuan Wang

Dissertations - ALL

Over the past decade, wireless data traffic has experienced an exponential growth, especially with multimedia traffic becoming the dominant traffic, and such growth is expected to continue in the near future. This unprecedented growth has led to an increasing demand for high-rate wireless communications.Key solutions for addressing such demand include extreme network densification with more small-cells, the utilization of high frequency bands, such as the millimeter wave (mmWave) bands and terahertz (THz) bands, where more bandwidth is available, and unmanned aerial vehicle (UAV)-enabled cellular networks. With this motivation, different types of advanced wireless networks are considered in this thesis. In …

Development Of Computational Antibiotic Screening Platform Across Bacterial Outer Membrane Proteins, Yinghui Dai

Dissertations - ALL

Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of …

An Intelligent Virtual Design Studio (Vds) For Integrative Design Of Green Buildings, Zhaozhou Meng

Dissertations - ALL

The overall goal of the study was to develop a "Virtual Design Studio (VDS)": a software platform for integrated, coordinated and optimized design of green building systems with low energy consumption, high indoor environmental quality (IEQ), and high level of sustainability. My dissertation research was focused on the development of a key VDS component -- an integrated design process and a near-real time performance simulation approach for fast feedbacks at the early stage of the integrated design process.

A design process module "Magic Cube" (MC) was developed for the VDS as the core for the design integration and coordination. It …

Inference And Learning In Spiking Neural Networks For Neuromorphic Systems, Amar Shrestha

Dissertations - ALL

Neuromorphic computing is a computing field that takes inspiration from the biological and physical characteristics of the neocortex system to motivate a new paradigm of highly parallel and distributed computing to take on the demands of the ever-increasing scale and computational complexity of machine intelligence esp. in energy-limited systems such as Edge devices, Internet-of-Things (IOT), and cyber physical systems (CPS). Spiking neural network (SNN) is often studied together with neuromorphic computing as the underlying computational model . Similar to the biological neural system, SNN is an inherently dynamic and stateful network. The state and output of SNN do not only …

A Building Information Modeling (Bim)-Centric Digital Ecosystem For Smart Airport Life Cycle Management, Basak Keskin

Dissertations - ALL

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today's modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today's Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical …

Impact Assessment, Detection, And Mitigation Of False Data Attacks In Electrical Power Systems, Sagnik Basumallik

Dissertations - ALL

The global energy market has seen a massive increase in investment and capital flow in the last few decades. This has completely transformed the way power grids operate - legacy systems are now being replaced by advanced smart grid infrastructures that attest to better connectivity and increased reliability. One popular example is the extensive deployment of phasor measurement units, which is referred to PMUs, that constantly provide time-synchronized phasor measurements at a high resolution compared to conventional meters. This enables system operators to monitor in real-time the vast electrical network spanning thousands of miles. However, a targeted cyber attack on …

Neuromorphic Systems For Pattern Recognition And Uav Trajectory Planning, Yilan Li

Dissertations - ALL

Detection and control are two essential components in an intelligent system. This thesis investigates novel techniques in both areas with a focus on the applications of handwritten text recognition and UAV flight control. Recognizing handwritten texts is a challenging task due to many different writing styles and lack of clear boundary between adjacent characters. The difficulty is greatly increased if the detection algorithms is solely based on pattern matching without information of dynamics of handwriting trajectories. Motivated by the aforementioned challenges, this thesis first investigates the pattern recognition problem. We use offline handwritten texts recognition as a case study to …

Effects Of Air Pollution, Temperature And Moisture Content On Copper And Silver Corrosions And The Reliability Of Data Center Equipment, Rui Zhang

Dissertations - ALL

The effects of moisture content, temperature, and pollutant mixture on atmospheric corrosion of copper and silver were investigated by exposing test specimens to different environmental conditions, followed by surface characterization using the coulometric reduction, Scanning Electron Microscopy, and Energy Dispersive Spectrometry (SEM/EDS). Printed circuit board test cards (PCBs) with bare copper were also used to investigate the effects of voltage bias on the PCBs on the corrosion rate. The test specimens were exposed to mixed flowing gases (MFG) environment with eight different combinations of the following five pollutants at the fixed concentration levels: 60 ppb O3, 80 ppb NO2, 40 …

Experience-Driven Control For Networking And Computing, Zhiyuan Xu

Dissertations - ALL

Modern networking and computing systems have become very complicated and highly dynamic, which makes them hard to model, predict and control. In this thesis, we aim to study system control problems from a whole new perspective by leveraging emerging Deep Reinforcement Learning (DRL), to develop experience-driven model-free approaches, which enable a network or a device to learn the best way to control itself from its own experience (e.g., runtime statistics data) rather than from accurate mathematical models, just as a human learns a new skill (e.g., driving, swimming, etc). To demonstrate the feasibility and superiority of this experience-driven control design …

Multi-Label/Multi-Class Deep Learning Classification Of Spatiotemporal Data, Natalie Sommer

Dissertations - ALL

Human senses allow for the detection of simultaneous changes in our environments. An unobstructed field of view allows us to notice concurrent variations in different parts of what we are looking at. For example, when playing a video game, a player, oftentimes, needs to be aware of what is happening in the entire scene. Likewise, our hearing makes us aware of various simultaneous sounds occurring around us. Human perception can be affected by the cognitive ability of the brain and acuity of the senses. This is not a factor with machines. As long as a system is given a signal …

Person Re-Identification And An Adversarial Attack And Defense For Person Re-Identification Networks, Yu Zheng

Dissertations - ALL

Person re-identification (ReID) is the task of retrieving the same person, across different camera views or on the same camera view captured at a different time, given a query person of interest. There has been great interest and significant progress in person ReID, which is important for security and wide-area surveillance applications as well as human computer interaction systems. In order to continuously track targets across multiple cameras with disjoint views, it is essential to re-identify the same target across different cameras. This is a challenging task due to several reasons including changes in illumination and target appearance, and variations …

Computational Algorithms For Predicting Membrane Protein Assembly From Angstrom To Micron Scale, Nandhini Rajagopal

Dissertations - ALL

Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications …

A Building Information Modeling (Bim)-Centric Digital Ecosystem For Smart Airport Life Cycle Management, Basak Keskin

Dissertations - ALL

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today’s modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today’s Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical …

An Examination Of Γ-Valerolactone Ring Opening And Decarboxylation In Multiphase System And Over Various Solid Acid Catalysts, Xinlei Huang

Dissertations - ALL

Lignocellulosic biomass is an alternative carbon source for industrial applications. γ-valerolactone (GVL) is an example of biomass-derived platform chemicals that provides multiple commercial potentials. Of interest here is the acid-catalyzed ring opening of GVL to form pentenoic acid (PEA) isomers and following decarboxylation to produce butenes. In this study, GVL ring opening, and decarboxylation are examined in both liquid and gas phases over various catalytic systems aiming at improving the efficiency in selective preparation of target product. An initial attempt was made in a biphasic reactor to improve the yield to PEA catalyzed by mineral acids (H2SO4). A wide range …