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Articles 1 - 12 of 12
Full-Text Articles in Computational Engineering
Influence Of The Sst K-Ω Stress-Limiter Coefficient On Transonic Shock Buffet Prediction For The Oat15a Supercritical Airfoil, Melinawo Vowotor
Influence Of The Sst K-Ω Stress-Limiter Coefficient On Transonic Shock Buffet Prediction For The Oat15a Supercritical Airfoil, Melinawo Vowotor
College of Graduate Studies: Theses & Dissertations
Transonic shock buffet predictions using the Shear Stress Transport (SST) k–ω turbulence model are known to be sensitive to the stress-limiter coefficient a₁, yet no systematic investigation of this sensitivity exists. This thesis presents a parametric study of a₁ for two-dimensional URANS simulation of shock buffet on the OAT15A supercritical airfoil at M = 0.73 and Re = 3 × 10⁶. Eleven a₁ values (0.25–0.37) are examined at α = 3.5°, and a matrix of five a₁ values across five angles of attack (3.0°–3.9°) maps the interaction with incidence. The results reveal that a₁ acts as a bifurcation parameter: a …
Comprehensive Performance Evaluation Of Devops Infrastructure Under Dynamic Workloads, Abdulrazaq Mamud
Comprehensive Performance Evaluation Of Devops Infrastructure Under Dynamic Workloads, Abdulrazaq Mamud
College of Graduate Studies: Theses & Dissertations
This research aims to investigate performance optimization and reliability issues related to cloud-based computing environments through an analysis of three key infrastructure components: virtualized CPU resource management, distributed API rate limiting, and web server deployment architectures. This research combines machine learning and system experimentation as a way of exploring the impact of infrastructure-level behaviors on overall system performance and scalability. The first component of the research focuses on analyzing CPU Fragmentation in Virtualized Environments, where unbalanced workload allocation on Virtual CPU Cores causes increased tail latency, resulting in Service Level Agreement violations. Metrics are analyzed using the Random Forest classifier …
Multiphysics Modeling Of Solid Oxide Fuel Cells For Gradient Minimization And Inductive Loop Analysis In Impedance Spectroscopy Using Machine Learning-Based Microstructural Property Estimation, Muhammad Usman Khan
College of Graduate Studies: Theses & Dissertations
Solid oxide fuel cells have significant advantages in renewable energy utilization due to their high efficiency, fuel flexibility, and low emissions. However, despite the numerous efforts of technology, thermal and current density gradients and impedance behavior fluctuations are still causing performance degradation. A combined computational framework that integrates machine learning and three-dimensional Multiphysics modeling is needed to investigate and optimize the performance of solid oxide fuel cells. A machine learning model, trained on synthetic microstructure data by percolation analysis, is used to predict important microstructural parameters like triple phase boundary density and geometric tortuosity. These are then employed in a …
Hybrid Rans-Les Analysis Of Turbulent Flame Under Near Blow-Off Condition In A Multi-Stage Swirl Combustor, Brandon O'Brien
Hybrid Rans-Les Analysis Of Turbulent Flame Under Near Blow-Off Condition In A Multi-Stage Swirl Combustor, Brandon O'Brien
College of Graduate Studies: Theses & Dissertations
Advances in computational resources are making computational fluid dynamics (CFD) increasingly accessible for a variety of engineering applications. However, certain complex problems, such as simulating detailed flame kinetics, remain computationally prohibitive for many users. Developing cost-effective methods to simulate these challenges would greatly benefit applications involving flame dynamics, such as turbine engines or industrial burners. This study investigates the effect of main stage swirler intensity on near lean blow-off characteristics in a multi-staged swirl combustor using Ansys Fluent. The hybrid RANS-LES turbulence model, Stress Blended Eddy Simulation (SBES) coupled with Flamelet Generated Manifold (FGM) combustion model was selected to model …
Contextual Augmentation In Artificial Intelligence, Emmanuel Joshua Balogun
Contextual Augmentation In Artificial Intelligence, Emmanuel Joshua Balogun
College of Graduate Studies: Theses & Dissertations
Contextual understanding is a significant challenge of Large Language Models (LLMs), which are typically trained on general-purpose datasets. Due to this, LLMs fail to capture nuanced or domain-specific information and may struggle to interpret user queries accurately. Consequently, prompt engineering can become complex in automating, and LLMs are prone to “hallucinating”—generating random or irrelevant texts—when they lack sufficient context. This undermines their ability to provide focused, accurate responses. Accordingly, this thesis seeks to enhance the contextual understanding capabilities of Artificial Intelligence systems to facilitate more precise and relevant answer generation. Study A looks into a new approach to combating misinformation …
Simulation Of Wave Propagation In Granular Particles Using A Discrete Element Model, Syed Tahmid Hussan
Simulation Of Wave Propagation In Granular Particles Using A Discrete Element Model, Syed Tahmid Hussan
College of Graduate Studies: Theses & Dissertations
The understanding of Bender Element mechanism and utilization of Particle Flow Code (PFC) to simulate the seismic wave behavior is important to test the dynamic behavior of soil particles. Both discrete and finite element methods can be used to simulate wave behavior. However, Discrete Element Method (DEM) is mostly suitable, as the micro scaled soil particle cannot be fully considered as continuous specimen like a piece of rod or aluminum. Recently DEM has been widely used to study mechanical properties of soils at particle level considering the particles as balls. This study represents a comparative analysis of Voigt and Best …
Comparative Analysis Of Fullstack Development Technologies: Frontend, Backend And Database, Qozeem Odeniran
Comparative Analysis Of Fullstack Development Technologies: Frontend, Backend And Database, Qozeem Odeniran
College of Graduate Studies: Theses & Dissertations
Accessing websites with various devices has brought changes in the field of application development. The choice of cross-platform, reusable frameworks is very crucial in this era. This thesis embarks in the evaluation of front-end, back-end, and database technologies to address the status quo. Study-a explores front-end development, focusing on angular.js and react.js. Using these frameworks, comparative web applications were created and evaluated locally. Important insights were obtained through benchmark tests, lighthouse metrics, and architectural evaluations. React.js proves to be a performance leader in spite of the possible influence of a virtual machine, opening the door for additional research. Study b …
Evaluation Of Supervised Deep-Learning For Improved Pneumonia Diagnosis, Andrew Kalaani
Evaluation Of Supervised Deep-Learning For Improved Pneumonia Diagnosis, Andrew Kalaani
College of Graduate Studies: Theses & Dissertations
Pneumonia is one of the leading causes of infections in the lung area and deaths worldwide. The mortality rate is 24.8% for patients over 70 years of age due to other health complications present along with it. In least fortunate countries, pneumonia can often times go untreated because of how cost extensive it is to diagnose, especially severe cases that cannot be seen by a plain X-ray. Other scanning methods can find the lung abnormality but are time-extensive and not cost effective. An autonomous approach however can help aid diagnosing pneumonia with a plain X-ray scan due to the structural …
Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications, David M. Mothershed
Quantitative Performance Assessment Of Lidar-Based Vehicle Contour Estimation Algorithms For Integrated Vehicle Safety Applications, David M. Mothershed
College of Graduate Studies: Theses & Dissertations
Many nations and organizations are committing to achieving the goal of `Vision Zero' and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented …
Digital Forensic Tools & Cloud-Based Machine Learning For Analyzing Crime Data, Majeed Kayode Raji
Digital Forensic Tools & Cloud-Based Machine Learning For Analyzing Crime Data, Majeed Kayode Raji
College of Graduate Studies: Theses & Dissertations
Digital forensics is a branch of forensic science in which we can recreate past events using forensic tools for legal measure. Also, the increase in the availability of mobile devices has led to their use in criminal activities. Moreover, the rate at which data is being generated has been on the increase which has led to big data problems. With cloud computing, data can now be stored, processed and analyzed as they are generated. This thesis documents consists of three studies related to data analysis. The first study involves analyzing data from an android smartphone while making a comparison between …
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
College of Graduate Studies: Theses & Dissertations
Electroencephalogram (EEG) has been used in a wide array of applications to study mental disorders. Due to its non-invasive and low-cost features, EEG has become a viable instrument in Brain-Computer Interfaces (BCI). These BCI systems integrate user's neural features with robotic machines to perform tasks. However, due to EEG signals being highly dynamic in nature, BCI systems are still unstable and prone to unanticipated noise interference. An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to implement …
Numerical Analysis Of Biodiesel Combustion In A Direct Injection Compression Ignition Engine, Kyle D. Morse
Numerical Analysis Of Biodiesel Combustion In A Direct Injection Compression Ignition Engine, Kyle D. Morse
College of Graduate Studies: Theses & Dissertations
In this work, simulations of the combustion reaction within an optical Sandia/Cummins N14 direct-injection compression ignition engine are conducted. First, validation of the spray model against liquid and vapor penetration data was conducted using a trial and error method. Secondly, the overall engine model was validated against pressure and temperature data across high and low temperature combustion regimes. The third phase of the work was focused on creating a combustion model for biodiesel. The fourth and final phase was to test the biodiesel combustion model in the pertinent combustion regimes. The agreement with common trends in emissions of biodiesel combustion …