Computational Engineering Commons^™

Modeling Of Supersonic Wave And Shock Propagation Using The Lattice Boltzmann Method, Timothy P. Schroeder

Beyond: Undergraduate Research Journal

The lattice Boltzmann method (LBM) has emerged as a mesoscopic alternative to traditional Navier-Stokes solvers for modeling fluid dynamics offering advantages in computational efficiency, parallelization, and handling of complex boundaries. Despite these strengths, accurately reproducing compressible, shock-driven phenomena remains challenging. This study investigates the performance of LBM in simulating the Sod shock tube problem, a classical benchmark for compressible flow-using both single and double distribution function formulations across one- and two-dimensional lattice stencils. A MATLAB-based solver was developed to model the flow under isothermal conditions and compared to the analytical solution using the L2 norm error. The one-dimensional models achieved …

Exploring Red Palm Oil As A Sustainable Plasticizer For Carbon Black-Filled Ssbr/Br Tire Tread Compounds: A Comparative Evaluation Of Commercial Alternatives, Norma Arisanti Kinasih, Mohamad Irfan Fathurrohman, Santi Puspitasari, Dewi Kusuma Arti, Abdulhakim Masa

Journal of Materials Exploration and Findings

This study investigates the application of red palm oil (RPO) as an alternative vegetable oil resource to substitute petroleum-based plasticizers, which have environmental and health concerns, in carbon black (CB)-filled SSBR/BR tire tread compounds. The plasticizing effects of RPO were thoroughly evaluated by comparing them with a commercial bio-based plasticizer, Epoxidized Soybean Oil (ESBO), and two safer petroleum-based oils, Naphthenic Oil (NYNAS) and Treated Distillate Aromatic Extract (TDAE). The initial investigation shows that fatty acid composition is imposing regarding the plasticizing effect. The higher unsaturated fatty acid content in RPO than in ESBO improved tensile strength and degraded rolling resistance …

Metallurgical Investigation Of A Modified Eye Bolt Failure Caused By Improper Weld Extension, Specification Deviation, And Crevice Corrosion, Dimas Muhammad Fawwaz, Reza Miftahul Ulum, Johny Wahyuadi Soedarsono, Yudha Pratesa

Journal of Materials Exploration and Findings

A modified eye bolt from the David Arm Manhole Storage Tank underwent thorough metallurgical study due to the consequences of the bolt's malfunction during operation. Safety issues arose when the manhole door detached during operation. The mechanical testing and chemical composition analysis of the bolts indicated they were manufactured from an ASTM A193 Grade B7 material used for high-temperature bolting. This material did not conform to the engineering drawing, which mentioned SA 563A, which is about nuts, not bolts. This contradiction clearly shows that the eye bolt which was installed does not conform to the intended design. Welded connections of …

Rejection Of Fe (Iron) And Kmno4 (Organic Substance) Parameters In Peat Water Using Organic Membranes, Muhamad Rafli Sakti Mulia Gonera, Siti Umi Kalsum, Sarah Fiebrina Heraningsih

Journal of Materials Exploration and Findings

Peat water is a surface water source widely used by people in swampy and lowland areas, but it has poor quality characteristics such as high organic matter content, low pH, and dissolved metal levels such as iron that exceed the threshold. These conditions can cause health problems and reduce the quality of clean water so that effective treatment technology is needed. This study aims to analyze the effectiveness of ultrafiltration membranes made from chitosan from shrimp shell waste in rejecting iron (Fe) and organic substances in peat water, and to determine the effect of pressure on separation performance. This study …

From Code To Cube: Interactive Fluid Simulation With Real Time Motion Control, Dominic Ziccardi, Carter Groezinger

Discovery Day - Daytona Beach

This research project explores the use of FluidX3D, an open-source lattice Boltzmann method (LBM) solver, to simulate fluid behavior within a three-dimensional cube container. The system supports both standard water models and rheoscopic fluid visualization, allowing detailed observation of complex flow dynamics in real time. The simulation accurately represents fluid motion, gravity-driven behavior, and rotational response within a bounded cubic domain. The longterm objective is to extend this digital simulation into a physical installation consisting of six synchronized square displays arranged to form a cube. This configuration will create a volumetric illusion of fluid occupying a tangible, handheld structure. An …

Extending The Essentially Entropic Lattice Boltzmann Method To Three-Dimensional Turbulent Flows, Michael Derderian

Discovery Day - Daytona Beach

The Entropic Lattice Boltzmann Method (EELBM) has demonstrated strong numerical stability and accuracy for two-dimensional simulations, particularly at higher resolutions where the entropic formulation introduces only minimal stabilizing turbulent viscosity and eventually converges to the Lattice Bhatnagar–Gross–Krook (LBGK) formulation. This built-in stabilization can be interpreted as an implicit large-eddy simulation (LES) model, allowing EELBM to capture complex turbulent behavior without requiring explicit subgrid-scale closures. While these advantages have been thoroughly validated in 2D, understanding how the entropic constraint regulates dissipation in three dimensions is essential for assessing EELBM’s suitability for practical, turbulence-dominated applications. This work focuses on the development and …

Multi-Dimensional Particle-In-Cell With Monte Carlo Collisions (Pic-Mcc) Simulation For Visualizing Plasma Flow And Secondary Ionization In Constricted-Anode Geometries, Parth Thakar

Discovery Day - Daytona Beach

Constricted-anode plasma sources generate locally intensified electric fields that enhance ionization near the anode, making them valuable in propulsion and laboratory plasma systems. However, the narrow geometry produces complex charge accumulation and secondary ionization effects that remain difficult to measure experimentally. To address this challenge, our research develops and applies a multi-dimensional Particle-in-Cell with Monte Carlo Collisions (PIC-MCC) simulation of a DC discharge in 1-D, 2-D, and 3-D configurations that model a constricted-anode device. PIC-MCC is a first-principles method that tracks electrons and ions individually while computing self-consistent electric fields and incorporating energy-dependent collision processes. This approach enables direct visualization …

Application Of Navier Stokes In Cfd, Hayden Kerkhoff, Gavin Palmer, Garret Seckinger

Discovery Day - Daytona Beach

This project investigates the use of 2-Dimensional Computational Fluid Dynamics (CFD) to analyze aerodynamic behavior, then compare data with the numerical solution of the Navier–Stokes equations run by MATLAB. By leveraging open‑source and possible industry CFD platforms—including OpenFOAM and commercial solvers such as ANSYS Fluent and Inventor Professional—the study evaluates how computational methods simulate, optimize, and predict key aerodynamic quantities such as lift, drag, stall angle, and Reynolds number.   The project focuses on modeling an airflow over specific parameters, such as different angles of attacks and ISA Atmospheric Conditions. Parametric variations in density, angle of attack, chord length, and temperature …

Ensemble Learning Framework For Predicting Close Proximity Tire–Pavement Noise On Expressways, Woo Young Cho, Jin Hwan Kim, Guk Gon Song, Kyungnam Kim, Youngguk Seo

Faculty Articles

Traffic noise is a critical public health concern affecting millions of highway users and adjacent residents worldwide. In response, many transportation agencies have adopted functional surface materials to reduce noise at the source on pavement, but assessing their effectiveness remains expensive and logistically challenging. Close Proximity (CPX) testing quantifies tire-pavement noise but requires specialized equipment costing $50,000-$126,000 and is limited to existing pavement, preventing proactive noise assessment during pavement design. This study develops machine learning models to predict CPX noise levels from readily available pavement characteristics, eliminating the need for costly tests during design and planning phases. To train and …

Graph-Based Machine Learning For Multivariate Time Series Prediction In Scientific Domains: Streamflow Forecasting And Solar Flare Prediction, Kishore Ragul Alagarsamy

All Graduate Reports and Creative Projects, Fall 2023 to Present

Machine learning methods applied to multivariate time series data have emerged as powerful tools across a range of scientific domains. This report examines two distinct application areas in which such methods yield actionable predictive insights: hydrological streamflow forecasting and solar flare prediction in space weather.

In the domain of streamflow forecasting, a Two-Graph Spatio-Temporal Graph Neural Network (Two-Graph STGNN) was developed to predict river discharge across a 20-station network in the Upper Colorado River Basin. The architecture separates hydrological and meteorological feature streams into two complementary graph representations and fuses them through a learned attention mechanism. Systematic evaluation across 23 …

Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark

Master's Theses

Rehabilitation assessment often relies on periodic observation, while many XR prototypes show scripted rather than recorded-motion evidence. iD-MORE Vision is an offline pipeline trained on KIMORE and IRDS and linked through JSON packets to a two-mode Unity desktop prototype. Both datasets include controls and rehabilitation participants with neurologic, musculoskeletal, or mobility impairments. This improves relevance but does not clinically validate the system.

Under fixed subject-wise splits, the primary five-seed Random Forest predicted KIMORE clinician scores with MAE 6.087 ± 0.044 cTS and R² 0.568 ± 0.006; the subject-level R² interval crossed zero. The primary IRDS five-run CUDA GRU averaged 0.877 …

Modeling For You: A Personalized Approach To Residential Energy Simulation And Distributional Reinforcement Learning, Nestor Gabriel Pereira

Electrical and Computer Engineering ETDs

The growing complexity and uncertainty of residential energy use, driven by electric

vehicles and renewable technologies, demand more intelligent and robust

management systems. Traditional methods often fail when faced with unpredictable

electricity prices and user behavior. This dissertation addresses this gap by presenting

a novel personalized framework combining detailed household energy modeling with

a risk-aware reinforcement learning agent for appliance scheduling.

The first contribution is a probabilistic, bottom-up simulation model that captures

the interdependent behaviors of occupants, appliances, and electric vehicles to

generate realistic, high-fidelity load profiles. The second contribution is a lightweight,

tabular Distributional Q-Learning (D-QL) algorithm that schedules …

Structural Design And Finite Element Analysis Of A 54 Ton Freight Wagon Bolster Test Rig Under Vertical Center Plate Load, Shandy Dwi Prayoga, I Dewa Gede Ary Subagia, I Ketut Adi Atmika, Abdul Rohman Farid, Yunior Lanang Satrio

Journal of Mechanical Engineering Science and Technology (JMEST)

Bolster is one of the bogie's components that receives direct loading from the car body and freight movement. One of the problems that occurs in the bolster is permanent deflection during vertical and transversal static loading. Therefore, a static loading test is required to evaluate the structural strength of the bolster. During the static loading test, a rig is required to hold the bolster so that the bolster is in a fixed position. The rig owned by PT. INKA (Persero) showed a plastic deformation at the vertical center plate load (VCP 5.22P). Therefore, a modified design of the rig is …

Numerical Simulation Of Centrifugal Pump Performance Under Impeller Blade And Suction Diameter Variations, Gunawan Budi Santoso, Susanto -, Akhmad Nuriyanis, Anang Budhi Nugroho, Rizka Noor Miftakhul Ulum, Suyono -

Journal of Mechanical Engineering Science and Technology (JMEST)

The objective of this study is to model variations in pump geometry to obtain optimal performance under the effects of cavitation. The resulting geometric variation models were then simulated using ANSYS Fluent software. The first geometric variation model used a standard 5-blade impeller with suction pipe diameter variations of 2, 2 ½, 2 ¾, 3, 3 ¼, 3 ½, and 4 inches. The second geometric variation model for simulation used a standard 3-inch suction pipe with impeller blade variations of 3, 4, 5, 6, 7, 8, and 9. The simulation results indicated that the number of blades without changes in …

Contemporary Cybersecurity Challenges In Emerging Technologies: A Systematic Literature Analysis, Faztudo Languisse Prof

Journal of Cybersecurity Education, Research and Practice

The accelerating convergence of artificial intelligence (AI), the Internet of Things (IoT), cloud computing, blockchain, and quantum computing has fundamentally transformed the global threat landscape, introducing cybersecurity challenges of unprecedented complexity and scale. This systematic literature review synthesizes findings from peer-reviewed publications, institutional reports, and regulatory documents published primarily between 2020 and 2025 to provide an integrated analysis of contemporary cybersecurity challenges across five key emerging technology domains. The review identifies critical vulnerabilities inherent to each domain, documents the evolution of threat actors and attack methodologies — including AI-powered ransomware, adversarial machine learning, and harvest-now-decrypt-later quantum attacks — and evaluates …

Effect Of Naoh Concentration On The Structural, Morphological, And Tensile Properties Of Pineapple Stem Fibers, Ahmad Norca Kurnia Zen, Heru Suryanto, Aminnudin Aminnudin, Fajar Nusantara, Joseph Selvi Binoj

Journal of Mechanical Engineering Science and Technology (JMEST)

Natural fiber reinforced composites are increasingly being developed due to their environmentally friendly nature, low production costs, and safety for human health. However, the presence of lignin and hemicellulose reduces adhesion properties between fiber and composite matrix. Alkalization treatment is an effective way to remove lignin and hemicellulose attached to cellulose. This study aims to determine the optimum concentration of NaOH used during alkalization process of pineapple stem fiber. The methods included the retting process of fibers from pineapple stems. The obtained fibers were soaked in variations of 2%, 4%, 6%, and 8% NaOH for 4 hours,  then dried and …

Experimental-Motion-Driven Cfd Investigation Of Slosh Dynamics In Propellant Tanks Of Spacecraft And Launch Vehicles, Priyanshu Savaliya

Doctoral Dissertations and Master's Theses

Liquid sloshing in partially filled propellant tanks can generate transient forces and moments that affect spacecraft and launch vehicle stability, guidance, and control. This research develops a one-way experimental-to-Computational Fluid Dynamics (CFD) integration framework to investigate free-surface slosh behavior under realistic excitation conditions.

The overarching goal of this thesis is to develop and evaluate a one-way experimental-motion-driven computational framework for predicting liquid slosh response in a partially filled cylindrical tank. Rather than relying on idealized sinusoidal inputs, this work uses experimentally measured actuator-feedback motion as the prescribed excitation for high-fidelity CFD. The central objective is to establish the experimental and …

Jalzap: An Agile Hybrid For Ai-Accelerated Software Development, Pouya Nouri

University Honors Theses

The rapid adoption of generative AI tools allows software teams to quickly code applications, but it comes at a cost: high scope volatility, technical debt, and unrealistic expectations, which break traditional Agile frameworks. This thesis introduces JALZAP, a lightweight, hybrid Agile framework designed to serve small, high-agility teams facing compressed timelines and unpredictable schedules. This framework was evaluated over 16 weeks through a Portland State University Capstone project working for a pre-seed startup sponsor, where a six-person team built Flowmind: an AI-powered iOS task management app meant to serve users with neurodevelopmental disorders like ADD/ADHD. JALZAP implements structural boundaries, including …

A Data Analysis Study Of Temperature Based On California Cooperative Oceanic Fisheries Investigations (Calcofi) Data., Afsana Mimi

Dissertations, Theses, and Capstone Projects

This research presents an integrated analytical framework for predicting ocean temperatures using long-term observations from the California Cooperative Oceanic Fisheries Investigations (CalCOFI) data files. The study applies advanced data engineering and statistical modeling to assess how a variety of indicators, such as salinity, dissolved oxygen, key nutrients, and ocean depth shape oceanic temperature patterns along the California coastline. Using Microsoft SQL Server software for large-scale data integration and the R for statistical packages (R Core Team, 2025) for statistical computation, I developed and compared multiple regression models, including the ridge regression model, to evaluate the relative influence of physical and …

Reproducing And Evaluating Charger Surfing: Robustness Of Smartphone Charging-Line Side-Channels, Colby M. Watts

Master's Theses

Smartphones are frequently connected to external, untrusted charging hardware, creating opportunities for side-channel attacks that do not require malware or direct access to device data. Charger Surfing, a recently proposed charging-line power analysis side-channel attack, reported high accuracy in inferring touchscreen input from voltage measurements collected from a smartphone’s charging cable; however, the reproducibility and robustness of these results under different conditions remain unclear. This thesis presents an independent replication and evaluation of Charger Surfing, including the development of an end-to-end data collection pipeline consisting of a modified charging cable, oscilloscope-based recordings, custom Android app, automated trace processing, and convolutional …

Large Scale Kmer-Based Proteomic Analysis: An Application Towards Evolutionary Constraint Discovery, Matthew Chak

Master's Theses

Large protein databases now make it possible to study short peptides across natural protein sequence space at unprecedented scale, but exhaustively counting k-mers across billions of protein sequences remains computationally difficult. This thesis develops an exact amino-acid k-mer counting method based on direct addressing, in which fixed-length amino-acid strings are encoded as base-20 integers and updated with a sliding-window recurrence. By avoiding key storage and collision resolution, this approach removes overhead inherent to hash-map-based methods when the k-mer space is sufficiently dense. A memory analysis shows when direct addressing is preferable to open-addressing hash tables, and expected-saturation calculations motivate its …

Praxsmith: An Actor-Centric Domain Specific Language For Emergent Narratives In Video Games, Jacob C. Kelleran

Master's Theses

The video game industry is rapidly growing, and interest in game development is growing alongside it. Among this growing interest is a desire to include branching and emergent narratives in games. This subject is understood to be difficult, as every possible trajectory within the story creates exponential complexity. Large studios are sometimes able to create convincing implementations, but that is often with hundreds of developers and writers. Over the years, various solutions have been proposed to create frameworks and languages that aim to tackle this problem, with varying degrees of success. Some frameworks attempt this by placing the focus on …

Machine Learning-Driven Prediction And Mechanistic Insight Into Co2 Adsorption On Biomass-Derived Activated Carbons Using Explainable Ai (Xai), Dalia A. Ali Dr.

Chemical Engineering

To improve CO2 uptake in Biomass-Derived Activated Carbon (BDAC), this study develops a multiscale hybrid digital twin framework. By integrating microscopic descriptors from Density Functional Theory and Molecular Dynamics (DFT/MD) with experimental data from 63 chemically diverse biomass precursors, a Gaussian Process Regression (GPR) model was developed using the Materń 5/2 Automatic Relevance Determination (ARD) kernel. The framework achieved high internal training accuracy (R2 = 0.968) and Root Mean Square Error (RMSE = 0.2552), while providing a realistic generalization baseline across heterogeneous precursors with a 5-fold Cross Validated (CV) R2 of 0.1567 and CV RMSE of 0.283. Explainable Artificial Intelligence …

Evaluating Optimal Capacity And Investment Strategies For Renewable Energy Projects: A Combined Technical And Financial Approach, Helen Josephine, Indhumathi Shanmugasundaram, Sharad Gupta, Manjari Sharma

Northeast Journal of Complex Systems (NEJCS)

The global shift toward clean energy is accelerating, and by 2050 renewable sources are expected to supply more than 85% of the world’s electricity. This transition, however, introduces new layers of complexity. Wind and solar energy behave as interconnected subsystems whose output fluctuates with weather, season, and geography. Their interaction with fixed hourly demand, capital-intensive investments, and financing structures creates a multi-dimensional system in which small changes can trigger significant operational and economic consequences.  This study presents a simulation-driven framework designed to understand and optimize this complex behaviour. The framework models hourly wind and solar generation alongside projected demand to …

Sentience, Sheetal Agrawal

Masters Theses

The increasing urgency for sustainable and adaptive systems has driven research toward embedding intelligence directly into materials rather than relying solely on external sensing and control systems. This thesis explores how smart material1 embedded systems can be designed to recognize and respond to environmental signatures, defined as measurable patterns such as temperature fluctuations and mechanical forces. Central to this investigation is the integration of shape memory alloys, particularly Nitinol, with geometry-based actuation mechanisms that amplify material behavior into functional system responses.

The central argument is that designing with smart materials is a design problem, not primarily a materials science problem …

Optimization And Energy Efficiency Analysis Of An Automatic Feed Mixer With A Rotating Drum Mechanism, Kris Witono, Talifatim Machfuroh, Nurlia Pramita Sari, Lisa Agustriyana, Aini Lostari

Journal of Mechanical Engineering Science and Technology (JMEST)

Energy-efficient feed mixer machines are important for improving the productivity and sustainability of small and medium-scale livestock farms. Previous studies primarily focused on either structural performance or mixing efficiency, with limited studies integrating both aspects. Therefore, this study evaluated an automatic rotating-drum feed mixer by combining Finite Element Method (FEM) analysis and energy modeling. The study used FEM simulations for different materials, namely A36 steel alloy, stainless steel 304, aluminium 6061, and galvanized steel, with thicknesses of 3 mm and 4 mm, as well as different drum systems. The FEM results showed that all evaluated materials met the minimum safety …

Influence Of Gas Atmosphere And Deposition Time On Si/Mno₂ Thin Films Properties Deposited By Magnetron Sputtering For Supercapacitor Application, Tansya Trisnatika Dewi, Boon Tong Goh, Reza Akbar Pahlevi, Ishmah Luthfiyah, Markus Diantoro

Journal of Mechanical Engineering Science and Technology (JMEST)

Thin films of MnO₂ were successfully deposited onto Si substrates using the magnetron sputtering technique in various gas atmospheres and deposition times to study their influence on the structural, morphological, electrical, and electrochemical properties for application as supercapacitor electrodes. Structural analysis using XRD showed that deposition under an Ar+O₂ gas atmosphere increased the crystallite size and crystallinity of the Si/MnO₂ films, while shorter deposition times reduced the crystallite size and lowered the crystallinity. Surface morphology observation using SEM showed that the film deposited in an Ar+O₂ gas atmosphere had smaller, more uniform, evenly distributed, and closely …

Influence Of Fiber Loading And Cu/Sio₂ Fillers On Mechanical And Physical Properties Of Sugarcane Bagasse Epoxy Composites, Ansor Salim Siregar, Indra Indra, Agung Fauzi Hanafi, Sunny Ineza Putri

Journal of Mechanical Engineering Science and Technology (JMEST)

The rising worldwide need for lightweight, high-strength, and eco-friendly materials has driven considerable investigation into natural fiber composites. This research offers an extensive examination of the creation and characterization of a new hybrid composite designed for high-performance sports equipment. The composite structure consists of an epoxy matrix strengthened with sugarcane bagasse fibers and synergistic blend of copper and silicon dioxide hybrid particulate fillers. Three unique composite variations were created, with systematically adjusted weight fractions of sugarcane bagasse fiber (35%, 31%, 27%) and hybrid fillers. A thorough assessment of mechanical and physical properties was carried out following ASTM standards. The results …

Improving Semantic Precision In Text-To-Image Diffusion Models Via Latent-Space Optimization And Semantically-Parsed Evaluation, Mohammad Rouie Miab

McKelvey School of Engineering Graduate Student Theses & Dissertations

Text-to-image diffusion models can produce visually impressive images from natural-language prompts, but they often fail to satisfy the detailed semantic constraints expressed in compositional prompts. Typical failure modes include omitted objects, merged entities, incorrect quantities, incorrect attribute binding, and leakage of one entity's attributes onto another. This thesis studies the problem of semantic precision in text-to-image generation: how faithfully a generated image satisfies the structured meaning of its prompt.   The thesis makes two linked contributions. First, it presents a training-free inference-time refinement method for diffusion-based image generation. The method operates directly in latent space during denoising and uses noun-phrase-aware cross-attention …

Analysis Of Dynamic Difficulty Scaling Ai In Video Games, Tyrese W. Walker

Honors Program: Senior Projects (Public)

Video games are a popular form of interactive media and, since their inception, have become one of the largest forms of media consumed. As such, they have evolved greatly from their humble beginnings into much more complex experiences, and adjusting the difficulty level to suit the needs of the player has become common practice. While there are simple ways to do so, the best games often feature a dynamic difficulty-scaling system that adapts to the player. Classics like Resident Evil and Left 4 Dead are excellent examples of innovative dynamic scaling design. By analyzing the strongest elements of these works, …