Computational Engineering Commons^™

A Formal Simulation Model For Discrete Rate Simulation, Thomas J. Tracey

Electrical & Computer Engineering Theses & Dissertations

Simulation is an essential tool for virtualizing systems by creating a representative model of real or hypothetical systems and observing how they change over time. Two predominant simulation paradigms include Discrete Event Simulation (DES) and Continuous Simulation, which both have their strengths and weaknesses. DES does not handle continuous state variables, while continuous simulation handles continuous state variables but encounters errors where these variables have discrete changes in their behavior. This difficulty between the two predominant simulation paradigms prompted the creation of a new simulation paradigm to cover this gap: Discrete Rate Simulation (DRS). DRS as a simulation paradigm focuses …

Investigating The Discrepancies Between Acoustic And Radar Measurements Of Water Level Using Data Analysis And Computational Modeling, Ohiedul Haque Mohammad Asad

Civil & Environmental Engineering Theses & Dissertations

Observations indicate that there is a discrepancy between water level measurements from NOAA’s acoustic gauges and radar gauges. NOAA’s acoustic gauges use a downward-looking acoustic sensor that measures the instantaneous distance from the sensor to the water level. To create a calm water surface for measurements, the sensor is placed in a PVC tube that penetrates the water surface to a certain depth. This tube is called the stilling well. In this thesis, discrepancies in water level measurements from acoustic and radar sensors were explored through data analysis and computational modeling. Specifically, the correlations between the error, which is defined …

Testing Autonomy: Hybrid Scenario Synthesis, Benjamin E. Hargis

Electrical & Computer Engineering Theses & Dissertations

Hybrid Scenario Synthesis merges static and adaptive techniques to generate interactions that rigorously assess autonomous performance under multi-factor testing. Multifactor scenarios employ multiple individual stimuli to rigorously test system responses in complex settings. Static Scenario Testing involves scripted test cases that simulate specific conditions or events. These scenarios represent typical situations an autonomous system might encounter. The benefits of static testing include early defect detection, focused review by trained experts, and efficiency. In multi-factor scenarios, however, statically defined scenario factors are not able to guarantee meaningful interactions as the presence of other factors may invalidate underlying assumptions regarding the system …

Unveiling The Transformative Power Of Unsupervised Machine Learning Through Clustering, Vishnu S. Pendyala

Open Educational Resources

Clustering methods demonstrated their transformative potential across various industries through image segmentation, anomaly detection, bioinformatics, and customer segmentation. The presentation explores these techniques in unsupervised machine learning, focusing on foundational clustering algorithms such as K-means, Hierarchical Clustering, and DBSCAN. Through an in-depth analysis of their underlying principles and computational intricacies, the presentation highlights how these methods have evolved to address complex, high-dimensional data problems. The presentation provides insights into how K-means remains a versatile tool for partitioning data in linear spaces. It delves into Hierarchical Clustering's unique approach to building dendrograms and capturing multi-scale data relationships, and how DBSCAN's density-based …

Enhancing Gas Cyclone Performance With Exit Diffusers, Omar Mohamed Mourad Dwidar, Yasser El-Shaer, Khairy Elsayed, Seyyed Hossein Hosseini, Goodarz Ahmadi

Journal of Engineering Research

This study evaluates seven cyclone designs to enhance pressure drop and collection efficiency (CE), using the conventional cyclone as a baseline. While the conventional design is efficient in particle collection, it experiences significant energy losses due to high values of pressure drops. This study introduces exit diffusers with various configurations—A, B, C, D, E, and F—to improve cyclone performance. Computational Fluid Dynamics (CFD) simulations were used to analyse the pressure drop, tangential velocity, and static pressure at different levels of each cyclone. The findings reveal that cyclone D achieves a 41.1% reduction in pressure drop but at the cost …

Collaborative Ai: Oer Materials For Exploring Ai As A Partner Rather Than A Tool, David Smith

Open Educational Resources

The Collaborative AI Open Educational Resource (OER) explores how artificial intelligence can act as a creative and analytical collaborator rather than a tool. Centered on the Balanced Blended Space (BBS) framework and the philosophy of the Center for Holistic Integration (CHI), the OER includes curriculum materials, theoretical models, and live research environments. It offers an interesting approach to blending physical, virtual, and conceptual spaces through shared human–AI agency and invites ongoing participation in interdisciplinary meta-projects.

Modelled Flooding Impacts On Lower Fish River Watershed, Sebastian Loschner

Shelby Hall Graduate Research Forum Posters

This study investigates the impacts of compound flooding in the Lower Fish River watershed, Baldwin County, Alabama, with a focus on the potential effects of sea level rise due to climate change. Coastal flooding, particularly in smaller watersheds, is a growing concern as it results from the interaction of multiple factors, including rainfall, tidal changes, and extreme weather events. Compound flooding, which involves multiple flood drivers, is expected to worsen with climate change, as increased precipitation and rising sea levels create heightened flood risks. However, existing research on compound flooding predominantly focuses on large-scale watersheds, leaving a knowledge gap in …

Evolution Of Lyrics Of Egyptian Songs In The 20th Century, Omar Abdelrafe

The Undergraduate Research Journal

Despite the extensive research by western countries on the song lyrics, almost nothing is known about the evolution of Egyptian song lyrics. The previous studies in the U.S. and U.K. revealed that lyrics were more pessimistic as time passed. In this study, 1891 Egyptian songs from 1920 to 2022 were analyzed using a sentiment analysis tool while searching for offensive words and retrieving their popularity scores from Spotify. The results aligned with those of the other regions in which the negativity of songs and the percentage of songs containing offensive words increased. However, there is a substantial increase in neutral …

Assessing Water Quantity And Quality In The Mississippi River Valley Alluvial Aquifer And Coastal Louisiana Through Integrated Airborne Electromagnetic And Borehole Data, Michael George Henin Attia Khalil

LSU Doctoral Dissertations

Numerical modeling has contributed significantly to the understanding of groundwater systems. Many challenges are associated with constructing groundwater models which include an accurate understanding of the geology and aquifer parameters estimation. Traditionally boreholes are a successful way to capture geological features, however, boreholes often have sparse data. Airborne electromagnetic (AEM) data allows for efficient and cost-effective surveying of large areas, providing valuable information about the subsurface electrical resistivity. By bridging the gap between boreholes, AEM data offers a broader view of the aquifer system's structure and heterogeneity. However, interpreting geophysical AEM data has uncertainties. Developing a framework to apply the …

Optimization Of The Cross-Section Of Generic Flexible Bridges, Manal Kamal Zaki, Mina M. Helmy, Mark M. Tawadros

Journal of Engineering Research

This paper investigates the behavior of flexible bridges prone to aerodynamic instabilities due to wind. Optimal cross-sections that reduce aerodynamic forces are recommended. This is achieved by studying a variety of bridge sections with different widths of upper and lower sloping edges in addition to studying the upper and lower cramps of the deck. The wind velocities are also parameterized. Computations are developed based on the powerful computational fluid dynamics (CFD) method known as FLUENT and embedded in ANSYS software. For parametric study, a design of experiments (DOE) is performed based on the response surface methodology (RSM) combined with the …

An Integrated Approach To Enhance The Performance Of Rainfall Forecasting By Leveraging Stacking Based Machine Learning And Deep Learning Techniques, Umamaheswari P

Theses and Dissertations

Rainfall forecasting is critical for a variety of reasons, the most important of which is the substantial impact it has on many sectors of the community and the environment. It helps farmers with planting schedules, crop choices and irrigation techniques, all of which directly impact food production and agricultural yields. Rainfall forecasting is also vital in sectors such as hydroelectric power generation, since knowledge about water availability is essential for electricity generation. Accurate rainfall forecasts play very important roles in disaster planning and flood control. They enable authorities to take precautionary measures and, where necessary, plan for the evacuation of …

Deep Neural Network Models For Heatsink Performance Prediction And Optimization In Single Phase Immersion Cooling: Framework For Future Design Tools And Digital Twin Integration, Braxton J. Smith

Mechanical and Aerospace Engineering Theses - Archive

The rapidly rising computational power of modern computing components combined with the advanced packaging techniques being implemented has resulted in exponentially increasing thermal design powers (TDP) from CPUs and GPUs. Traditional air-cooling methods are approaching their effective cooling limits for many of these components, requiring lower supply air temperatures, higher supply air flowrates, and much larger heatsinks to remain feasible. Transitioning from air-cooling to single-phase immersion cooling offers numerous benefits in thermal performance, data-center size reduction, and energy efficiency. To leverage the merits of immersion cooling, the performance of a given heatsink must be predicted and optimized for best performance …

Csc 22100 Software Development Laboratory Homework Assignment #1, Mitch Gershonowitz

Open Educational Resources

This is the first homework assignment for an Introduction to Java Programming course, which requires the students to write Java code using industry-accepted conventions. The assignment requires the student to write a Java method that accepts a date in an internationally-recognized format and returns a String object in Julian Date Format (JDF) with format YYDDD.

Csc 22100 Software Development Laboratory Homework Assignment #3, Mitch Gershonowitz

Open Educational Resources

This is the third homework assignment for an Introduction to Java Programming course, which requires the students to write Java code using industry-accepted conventions. The assignment requires the student to write a Java classes and interfaces that demonstrate usage of passing lambda expressions to methods, as well as demonstrating polymorphism and inheritance.

Fast-Sparse-Spanner: A Practical Algorithm For Constructing Low-Stretch Sparse Geometric Graphs, Fnu Shariful

UNF Graduate Theses and Dissertations

When constructing geometric graphs (vertices are points and edges are line segments connecting point pairs) on pointsets, stretch-factor (worst-case detour between any point pair) is often considered a quality metric. A low stretch-factor (a quantity that is usually > 1) guarantees short paths between all vertex pairs. A geometric graph having a stretch-factor of t is known as a t-spanner. Creating low stretch-factor geometric graphs for large pointsets with a low number of edges is an open problem in computational geometry.

In this work, we have designed and engineered a new simple and practical (fast and memory-efficient) algorithm named Fast-Sparse-Spanner algorithm …

Enhancing Risk And Crisis Communication With Computational Methods: A Systematic Literature Review, Madison H. Munro, Ross J. Gore, Christopher J. Lynch, Yvette D. Hastings, Ann Marie Reinhold

VMASC Publications

Recent developments in risk and crisis communication (RCC) research combine social science theory and data science tools to construct effective risk messages efficiently. However, current systematic literature reviews (SLRs) on RCC primarily focus on computationally assessing message efficacy as opposed to message efficiency. We conduct an SLR to highlight any current computational methods that improve message construction efficacy and efficiency. We found that most RCC research focuses on using theoretical frameworks and computational methods to analyze or classify message elements that improve efficacy. For improving message efficiency, computational and manual methods are only used in message classification. Specifying the computational …

Direct Numerical Simulation Of Pulsating Flow In Curved Pipes: Insights Into Aortic Dissection In Humans, Gokul Anugrah Gopakumar

Theses and Dissertations--Mechanical and Aerospace Engineering

This dissertation investigates the hemodynamics of pulsating blood flow in curved vessels through direct numerical simulations (DNS), with the overarching aim of uncovering fluid dynamic mechanisms linked to the onset and progression of aortic dissection in humans. The work is structured in two parts: (i) fundamental studies in idealized geometries and (ii) preliminary investigations in patient-specific anatomies. In the first part, curved pipe models representing the aortic arch are used to isolate the effects of pulsation frequency, amplitude ratio, and curvature ratio on transitional and turbulent flow dynamics. The simulations reveal that curvature-driven centrifugal forces shift the peak velocity toward …

A Comparative Study Of Machine Learning Models For Javanese Wuku Classification: Exploring Svm, Naïve Bayes, And Cnn For Cultural Texts, Danang Arbian Sulistyo, Aji Prasetya Wibawa, Didik Dwi Prasetya, Fadhli Almu'iini Ahda, Agung Bella Putra Utama

Knowledge Engineering and Data Science

This study rigorously evaluates machine learning models for classifying culturally significant Javanese Wuku texts from the “Keagamaan atau Spiritual” category, a domain challenged by unique linguistic nuances and limited digitized resources. We compared Support Vector Machine (SVM), Naïve Bayes, and Convolutional Neural Network (CNN) on texts from five pivotal Wuku types (Sinta, Galungan, Kuningan, Sungsang, Warigalit) sourced from sastra.org, aiming to identify the most effective computational approach. The dataset comprises N = 1419 documents (T = 751.290 tokens), with per-class document counts reported for all five Wuku types. Our evaluation uses accuracy, precision, recall, F1-score, and …

Mapping Of Product Sales Potential Based On Brands In The East Kalimantan Region Using Hybrid Analytical Framework, Achmad F O Gaffar Mr, Mulyanto Mulyanto Mr, Arief Bw Putra Mr, Muhammad Taufiq Sumadi Mr, Emmilya Umma Aziza Gaffar

Knowledge Engineering and Data Science

In geographically dispersed markets, operational costs should be reflected in sales planning to support accurate performance evaluation. However, such considerations are often neglected in practice. This study proposes a hybrid analytical framework to map brand-based product sales potential, with and without operational cost consideration, using historical sales data from PT Karya Inti Total Anugerah (PT KITA) in East Kalimantan. The framework integrates spatial, statistical, and machine learning techniques. Principal Component Analysis (PCA) is used to reduce the dimensionality of variables related to travel distance, total sales, and units sold, where travel distance represents the primary contributor to operational costs. K-Means …

Virtual Environment Creation And Camera Calibration For Soft Target Identification And Assistance In Crowded Spaces With A Sensor Network And A Robotic Dog, Eltan Samoylov

Dissertations and Theses

Crowded places are increasingly targets of violence due to the increased accessibility and covertness of weapons, explosives, and other technology like drones. Addressing the challenges of protecting crowded places and assisting vulnerable individuals requires a multidisciplinary approach, taking inspiration from many different perspectives. Video surveillance of these crowded public facilities, such as train and bus stations, airports, shopping malls, and sports arenas, is very important to public safety, both for identifying threats/terrorist attacks and implementing evacuation plans.

The work of this thesis is part of a larger project aiming to explore the potential of using real-time computer vision and deep …