Engineering Commons^™

Program And Proceedings: Nebraska Academy Of Sciences 1880–2023, 143rd Anniversary Year, One Hundred-Thirty-Third Annual Meeting, April 21, 2023

Nebraska Academy of Sciences: Programs and Proceedings

Program

Aeronautics and Space Science

Humans Past and Present

Applied Science and Technology Section

Biology

Biomedical Sciences

Chemistry

Earth Sciences

Environmental Science

Physics

Science Education

2023 Maiben Lecture: Jason Bartz

2023 Friend of Science Award: Ray Ward and Jim Lewis

A Comparison Of Optical Measurement Methods For The Growth Of S. Cerevisiae, Jackson Black

Chemical Engineering Undergraduate Honors Theses

Genetic engineering of living organisms provides the opportunity to express and harvest different proteins from cell surfaces. Yeast (S. cerevisiae) is one such organism and is capable of being grown on an industrial scale. Cellular concentration is an important parameter to monitor while fermentation processes are underway, in order to control the environment inside the growth medium and maximize yields. Spectrophotometry is a conventional method for measuring concentration, but is limited by a narrow absorbance range, and the need for on-site periodic sampling. A continuous method of measurement, as provided by Bug Labs BE2100 non-invasive biomass monitor, would …

Optimal Offering Strategy Of Genco With Joint Participation In Ftr Auction And Day-Ahead Market Considering Virtual Bidding, Hossein Mehdipourpicha, Rui Bo, Siyuan Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Nodal price separations in Day-Ahead (DA) market caused by transmission congestion create congestion charges/surplus that are reallocated to the market participants through the financial transmission right (FTR) auction. From a market participant's viewpoint, these two markets are interrelated because the revenue of market participant in FTR auction is determined based on the day-ahead locational marginal prices. Furthermore, virtual transactions which are designed to improve price convergence between the day-ahead and real-time markets can directly impact day-ahead prices. This impact through virtual transactions may be utilized by a market participant to increase its FTR value and improve its overall strategy in …

Machine Learning For A Vernier-Effect-Based Optical Fiber Sensor, Chen Zhu, Osamah Alsalman, Wassana Naku

Electrical and Computer Engineering Faculty Research & Creative Works

In recent years, the optical Vernier effect has been demonstrated as an effective tool to improve the sensitivity of optical fiber interferometer-based sensors, potentially facilitating a new generation of highly sensitive fiber sensing systems. Previous work has mainly focused on the physical implementation of Vernier-effect-based sensors using different combinations of interferometers, while the signal demodulation aspect has been neglected. However, accurate and reliable extraction of useful information from the sensing signal is critically important and determines the overall performance of the sensing system. In this Letter, we, for the first time, propose and demonstrate that machine learning (ML) can be …

Design And Analysis Of Gold-Nanowires Based Multi-Channel Spr Sensor, Nasir Mahmood Anjum, Farhan Mumtaz, Muhammad Aqueel Ashraf

Electrical and Computer Engineering Faculty Research & Creative Works

This research reports the simultaneous multi-analyte sensing capabilities of a D-shaped multi-channel surface plasmon resonance (SPR) sensor. Three channels are truncated in a U-shaped pattern at the side-polished surface of the D-shaped three-core fiber. Three Gold-nanowires (AuNWs) are positioned at the bottom of each sensing channel. To examine the SPR sensor's multi-channel characteristics, a finite element method (FEM) is applied. In order to detect a variety of analytes, y-polarized modes-multiplexing is used, which offers a sufficient wavelength range. At an infiltrated refractive index (RI) of 1.35, 1.38, and 1.41, respectively, the maximal RI sensitivities of c-1 (channel-one), c-2 (channel-two), and …

Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan

Turkish Journal of Electrical Engineering and Computer Sciences

With the rapid development of 5G and the Internet of Things (IoT), the traditional cloud computing architecture struggle to support the booming computation-intensive and latency-sensitive applications. Mobile edge computing (MEC) has emerged as a solution which enables abundant IoT tasks to be offloaded to edge services. However, task offloading and resource allocation remain challenges in MEC framework. In this paper, we add the total number of offloaded tasks to the optimization objective and apply algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA) to maximize the value function, which is defined as a weighted sum of energy consumption, latency, and …

Breath Analysis For Detection Of Lung Cancer With Hybrid Sensor-Based Electronic Nose, Ümi̇t Özsandikcioğlu, Ayten Atasoy

Turkish Journal of Electrical Engineering and Computer Sciences

Lung cancer has the highest death rates among all types of cancer worldwide. Detection of lung cancer in its early stages significantly increases the survival rate. In this study, the aim is to improve the lung cancer detection performance of electronic noses (e-noses) with breath analysis by using two different types of gas sensor-based e-nose. The developed e-nose system consists of 14 quartz crystal microbalance (QCM) sensors and 8 metal oxide semiconductor (MOS) sensors. Breath samples were collected from a total of 100 volunteers, including 60 patients with lung cancer, 20 healthy nonsmokers, and 20 healthy smokers, and were classified …

Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines, Linh Tran

Turkish Journal of Electrical Engineering and Computer Sciences

Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still …

Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation, Zuhal Taş, Fahreddi̇n Şükrü Torun

Turkish Journal of Electrical Engineering and Computer Sciences

The block Cimmino method is successfully used for the parallel solution of large linear systems of equations due to its amenability to parallel processing. Since the convergence rate of block Cimmino depends on the orthogonality between the row blocks, advanced partitioning methods are used for faster convergence. In this work, we propose a new partitioning method that is superior to the state-of-the-art partitioning method, GRIP, in several ways. Firstly, our proposed method exploits the Mongoose partitioning library which can outperform the state-of-the-art methods by combining the advantages of classical combinatoric methods and continuous quadratic programming formulations. Secondly, the proposed method …

Unbiased Federated Learning In Energy Harvesting Error-Prone Channels, Zeynep Çakir, Eli̇f Tuğçe Ceran Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Federated learning (FL) is a communication-efficient and privacy-preserving learning technique for collaborative training of machine learning models on vast amounts of data produced and stored locally on the distributed users. This paper investigates unbiased FL methods that achieve a similar convergence as state-of-the-art methods in scenarios with various constraints like an error-prone channel or intermittent energy availability. For this purpose, we propose FL algorithms that jointly design unbiased user scheduling and gradient weighting according to each user's distinct energy and channel profile. In addition, we exploit a prevalent metric called the age of information (AoI), which quantifies the staleness of …

Efficient Modelling Of Random Access Memory Cell: An Approach Using Qca Nanocomputing, Ali Newaz Bahar, Angshuman Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Quantum-dot cellular automata (QCA) is innovative and potentially fruitful nanotechnology that provides a solution for transistor-based circuits with enhanced switching frequency, large-scale integration, and low power consumption. The random-access memory (RAM) cell is a fundamental component that is designed to operate quickly and effectively since memory is a core part of the semiconductor industry, thus the QCA family. The RAM cell design in this work is based on a multiplexer structure and is implemented without using coplanar crossovers of QCA technology. QCADesigner-2.0.3, a standard QCA layout design and verification tool, is used in the simulation and validation processes for the …

An Analytical Solution Of Fractional Order Pi Controller Design For Stable/Unstable/Integrating Processes With Time Delay, Erdal Çökmez, İbrahi̇m Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to put forward an analytical solution for tuning parameters of a fractional order PI (FOPI) controller for stable, unstable, and integrating processes with time delay. Following this purpose, the analytical weighted geometrical center (AWGC) method has been extended to the design of fractional order PI controllers. To apply AWGC, the stability equations of the closed-loop system are written in terms of process and fractional order PI controller parameters. With the proposed method, the centroid can be calculated analytically, and the controller parameters can be easily calculated without the need of repetitive drawings of the stability boundary regions. …

More Wifi For Everyone: Increasing Spectral Efficiency In Wifi6 Networks Using A Distributed Obss/Pd Mechanism, Ali̇ Karakoç, Hüseyi̇n Bi̇rkan Yilmaz, Mehmet Şükrü Kuran

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a distributed algorithm that determines effective Overlapping Basic Service Set/Preamble Detection (OBSS/PD) threshold levels in each WiFi6 device to maximize the total throughput by increasing the spectral efficiency. Within WiFi6 standard, OBSS/PD mechanism is introduced to increase the overall efficiency of WiFi networks by tuning the receiver sensitivity as well as the transmission power. In a nutshell, the proposed algorithm, RACEBOT, tunes the hearing (i.e. reception) and speaking (i.e. transmission) parameters of each WiFi device individually for the betterment of the WiFi experience of all WiFi networks in a neighborhood. WiFi experience is not only …

Interaction Effects And Selecting Regression Models Of Taylor Swift Song Popularity, Halle Schneidewind

Industrial Engineering Undergraduate Honors Theses

Understanding music popularity and what drives it is important not only for artists but for other individuals who are financially tied to music sales including producers, writers, and record labels. Studies have been done to define how a song’s popularity can be measured, what attributes or features are drivers for popularity, and to what extent can a song’s popularity even be predicted. This paper takes two linear regression approaches to predicting the popularity of a Taylor Swift song on Spotify based on auditory features the Spotify API estimates and historic popularity of songs on Spotify. One model takes into consideration …

Control And Design Of A Passive Solar Lumber Drying Kiln, Peter Chardavoyne

Honors Scholar Theses

The passive solar lumber drying kiln design, developed by EE Senior Design Team 2317 is presented, tested, and discussed. The design incorporates solar power and a custom control system to dry 12’ lumber boards inside a shipping container much faster than air-drying methods, which can take up to a year for thorough drying, though this can be extended due to the unpredictability of weather events and conditions. This work presents the design as in the final report provided by the team, but provides a more detailed explanation and analysis of the microcontroller system, testing methods and outcomes, alternate solutions and …

Light Sheet Microscopy Incubation Design And Control Scheme, Venkatanathan Kidambi

Honors Scholar Theses

The focus of the following paper is the development of a light sheet or selective plane illumination microscopy (LSM / SPIM) platform to support long duration three dimensional imaging of various cells and tissues. This paper describes the complete design and fabrication process behind the prototype, including a definition of light sheet microscopy and its differences from confocal microscopy, as well as existing open source selective plane microscopy literature and designs. The complete engineering design process as applied to the microscope design is described in detail. Specifically, this paper will focus on the development of an incubation chamber for light …

Characterizing Energy Dissipation Of Shallow-Water Wave Breaking In A Storm Surge, Hunter Boswell, Guirong Grace Yan, Wouter Mostert

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

While understanding breaking waves is crucial for the development of parametrizations used in ocean wave modeling for both deep and shallow water, the complete process of wave breaking is not well understood. Here we present direct numerical simulations of two-dimensional solitary waves that shoal and break on a uniform beach in shallow water, with the presence of storm surge represented by an inshore region. The storm surge depth, beach slope, and wave amplitude are varied to study the dependence of energy dissipation in the breaker on wave and bathymetric parameters. We classify wave breaker types and find a separation between …

Engineered Material Systems For Mimicking Tissue And Disease, Margrethe Ruding

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis comprises two studies involving design and application of soft material systems. The goal of the first study was to design, fabricate, and characterize hydrogel lattice structures with consistent, controllable, anisotropic mechanical properties. Lattices, based on four types of unit cells (cubic, diamond, vintile, and Weaire-Phelan), were printed using stereolithography (SLA) of polyethylene glycol diacrylate (PEGDA). In order to create structural anisotropy in the lattices, unit cell design files were scaled in one direction by a factor of two in each layer and then printed. The mechanical properties of the scaled lattices were measured in shear and compression and …

Peak To Average Power Ratio Reduction In Spectrally Efficient Fdm Using Repeated Clipping And Filtering, Buthaina Mosa Omran, Yamaan Esmiel Majeed, Iftekhar Ahmad

Research outputs 2022 to 2026

Multi-carrier transmission may be considered one of the important developments in wireless communications. Spectrally efficient frequency division multiplexing (SEFDM) is a promising multi-carrier modulation which can significantly improve utilization of spectral. The SEFDM has high peak to average power ratio (PAPR) like any multicarrier system. High PAPR reduces the random forest (RF) transmitter power amplifier efficiency, which minimize the use of this technique in limited power supply transmitters. In this work, a repeated clipping and filtering method is introduced to reduce the PAPR in SEFDM with minimum or no out of band radiation. The results of the simulated approach show …

Evaluating The Role Of Magnetic Materials In Mediating The Abiotic Degradation Of Chlorinated Ethenes At Tcaap-A Using A C14-Assay, Olivia Dunn

All Theses

Among the most challenging sites to remediate are those where the groundwater is contaminated with large, dilute plumes of tetrachloroethene (PCE), trichloroethene (TCE), dichloroethene isomers (cDCE, tDCE, 1,1-DCE) and vinyl chloride (VC). Monitored Natural Attenuation (MNA) by abiotic processes may be a viable strategy, but it can be difficult to document. The overall objective of this project is to develop a deeper understanding of the role of magnetic materials in mediating abiotic degradation of low concentrations of chlorinated ethenes in aquifers. Authentic core aquifer sediment has been collected from Site A at the former Twin Cities Army Ammunition Plant (TCAAP) …

Comparative Design Space For Bistable Composites: An Integrated Framework Of Optimization, Finite Element Analysis, And Experimental Testing, Jonathan Bolanos

All Theses

Bistable composites are a class of advanced materials that can actuate between two stable shapes, making them attractive for a wide range of engineering applications. However, designing these composites to achieve optimal performance remains a challenging task. To address the challenge, this research develops an integrated framework that combines a genetic algorithm optimization technique, finite element analysis in Abaqus, and experimental testing to explore the design comparative space for square bistable composites composed of DA 409 carbon fibers. This leads to the study of generating an optimization algorithm to account for the relationship between the chances of a successful maximum …

Analyzing The Influence Of Stale Data On Autonomous Intelligent Transportation Systems, August St. Louis

All Theses

Intelligent transportation has been at the forefront of recent technological advancement. Individuals have developed a number of algorithms intended to automate and improve essential intelligent transportation functions. New developments include the incorporation of vehicle platooning and path planning algorithms within a number of use cases. Data perturbation can affect both algorithms significantly. We define data perturbation as any natural or unnatural phenomenon that causes the data to be skewed in any way. Perturbations within either system can cause its respective algorithm to operate with stale or incorrect data. This can significantly affect performance. This paper conducts a fault injection campaign …

Force Coefficients And Wind Loads For Wide Flange Section And Retrofitted Pipe Racks, Sovanroth Ou

All Theses

While relatively rare, the failures of steel structures occasionally occur due to extreme wind events such as hurricanes and tornadoes. The American Society of Civil Engineers (ASCE) provides well-defined guidelines for determining wind loads for regular buildings; nonetheless, the actual wind loads for complex open-frame steel structures are not as clearly understood by practicing engineers. Pipe bridges and pipe racks are open-frame structures, commonly used in many petrochemical plants. Over the years, additional pipes are often added to existing pipe racks or pipe bridges to accommodate changes in the operation needs of the petrochemical plant. The objectives of this study …

Mapping Information Flows That Support Adaptive Capacity In The Sterile Processing Department (Spd), Jacob Hionis

All Theses

The Sterile Processing Department (SPD) is the part of the hospital that is responsible for decontaminating, assembling, and sterilizing surgical trays for use in the Operating Rooms (ORs). Errors in the SPD can lead to delayed surgeries or patient harm. The SPD is a complex system, with multiple interconnected subdepartments and roles. Complex systems require coordination between stakeholders. This study aims to discover how an organization can adapt to scale, and how information flows support these adaptations. In this study, observations, semi-structured interviews, and on-the-job interviews were conducted with members across the SPD and OR to elicit pressures, adaptations, and …

Considerations Of The Impacts And System-Level Mitigation Of Electric Vehicle Charging On The Integrated Resource Planning Process, Grant Wollam

All Theses

Electric vehicles (EV) are growing in popularity and therefore adoption rate. Best estimates predict a 6.2% EV adoption rate by 2035 in the southeastern United States. With this level of EV adoption, utility planners must begin to consider the impact that EVs will have on the power grid. This paper aims to help predict these EV impacts on the power grid. Specifically, an urban-commercial feeder is analyzed in detail to provide worst-case and most-likely results of varying levels of EV impact. Results show that a 26.2% peak increase is the most likely result for this feeder in 2035.

Mitigation techniques …

Development And Evaluation Of Machine Learning Models For Fugitive Methane Detection And Intensity Prediction, Jacquan Pollard

All Theses

The environmental impacts of global warming driven by fugitive methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4 emissions. This study evaluated the performance of data-driven machine learning (ML) models using support vector machines (SVM) to detect the presence of trace CH4 emissions and the corresponding intensity amongst various meteorological conditions. The author used simulation data comprising various meteorological parameters such as temperature, relative humidity, wind speed, water vapor, pressure, precipitation rate, and a parameter possessing trace concentrations of CH4 emissions. The novelty of the SVM models developed in …

Assessing Key Factors Influencing Fire-Induced Spalling Of Concrete Using Explainable Artificial Intelligence (Xai), Mohammad Khaled Gazi Albashiti

All Theses

This thesis adopts eXplainable Artificial Intelligence (XAI) to identify the key factors influencing the fire-induced spalling of concrete and to extract new insights into the fire-induced spalling phenomenon. In this pursuit, an XAI model was developed, validated, and then augmented with two explainability measures, namely, Shapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). The proposed XAI model not only can predict the fire-induced spalling with high accuracy (i.e., >92 %) but can also articulate the reasoning behind its predictions (as in, the proposed model can specify the rationale for each prediction instance); thus, providing us with valuable insights …

Biodegradable Magnesium Materials Regulate Ros-Rns Balance In Pro-Inflammatory Macrophage Environment, Maria Paula Kwesiga, Amani A. Gillette, Seyedehfatemeh Razaviamri, Margaret E. Plank, Alexia L. Canull, Zachary Alesch, Weilue He, Bruce Lee, Roger J. Guillory Ii

Michigan Tech Publications, Part 1

The relationship between reactive oxygen and nitrogen species (ROS-RNS) secretion and the concomitant biocorrosion of degradable magnesium (Mg) materials is poorly understood. We found that Mg foils implanted short term in vivo (24 h) displayed large amounts of proinflammatory F4/80+/iNOS + macrophages at the interface. We sought to investigate the interplay between biodegrading Mg materials (98.6% Mg, AZ31 & AZ61) and macrophages (RAW 264.7) stimulated with lipopolysaccharide (RAW 264.7LPS) to induce ROS-RNS secretion. To test how these proinflammatory ROS-RNS secreting cells interact with Mg corrosion in vitro, Mg and AZ61 discs were suspended approximately 2 mm above a monolayer of …

Cycle Time Reduction In Additive Manufacturing Using Peltier Thermoelectric Cooling Devices, Trevor Carlton

Honors College Theses

Thermoelectric cooling and the Peltier effect were discovered in 1834, over 188 years ago. Additionally, the first iterations of additive manufacturing (i.e., 3D printing) began in the early 1980s, more than 40 years ago. Despite these technologies’ age and years of advancements, the application of Peltier cooling-based devices in additive manufacturing has not yet been realized. These devices can be used for the active thermal management of print beds in 3D printers. Developing a mechanism to heat and cool a print bed can reduce the cycle time to manufacture a part. In 3D printing, waiting for the heated bed to …

Probabilistic Machine Learning For Battery State Of Health Prognostics, Charli Zaretsky

Honors Scholar Theses

The ability to understand and predict the state of health (SOH) of lithium-ion batteries is an integral component of their widespread commercial use. There are various methods through which SOH can be analyzed and predicted, and this paper discusses these different methods, and the strengths and weaknesses of each. This paper also details an analysis of lithium-ion battery SOH through two data-driven machine learning methods: XGBoost and Gaussian process regression. A comparison is made between each method’s accuracy in predicting next-cycle discharge capacity using electrochemical impedance spectroscopy (EIS) readings and battery charge and discharge rates, from a dataset given in …