Computational Engineering Commons^™

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, …

Turbulent Plenum Jet-Crossflow Validation Via Subgrid Scale Model Variation And Upstream Forcing Under Dynamic Hybrid Rans-Les, Cole W. Mccallum

Mechanical Engineering Undergraduate Honors Theses

In modern gas turbine design, film cooling has become ubiquitous as a method for limiting heat transfer between high temperature gases post-combustion and the surface of downstream blades. This paper validates the use of various computational fluid dynamics techniques in recreating an experiment measuring adiabatic effectiveness over a surface downstream of a compound-angle N2 plenum jet incident on a turbulent-air boundary layer [1]. To do this, both RANS and Dynamic Hybrid RANS-LES (DHRL) methods are implemented and compared to previous research [2]. The latter method is then modified through implementation of a different subgrid scale (SGS) model and through addition …

Hdra-Fusion: Hybrid Detection With Routed Architecture For Manipulation-Aware Ai Face Forgery Detection, Omar Ebeid

Theses and Dissertations

With the rapid advancements in artificial intelligence-based image generation and manipulation tools, it is extremely difficult to detect if an image is genuine or artificially crafted. Despite extensive research in this area, existing image detection systems suffer from three major problems: suboptimal cross-dataset generalization due to shortcut learning of dataset-specific patterns, unreliable probability estimates due to domain shift, particularly in cross-manipulation evaluation settings, and an inability to detect images manipulated by multiple types of manipulations within a single detection framework. To address these limitations, we propose HDRA-Fusion (Hybrid Detection with Routed Architecture), a framework built on the conclusion that different …

The Digital Neuron: Neural Cellular Automata For Neural–Symbolic Translation, Nicole Assenza

SMU Data Science Review

A neural cellular automata (NCA) architecture, referred to as Pluto’s NCA, was developed to characterize bilateral communication and semantic reciprocity between symbolic representations and a spatially distributed update field. The architecture employs an encoder–automata–decoder pipeline that maps symbolic inputs into a multichannel state field and reconstructs them through agreement-driven attractor convergence within a stable semantic attractor landscape. System behavior was evaluated under controlled perturbations, including rhythmic desynchronization, graded ablations, correlated and independent noise, and percolation-based structural degradation. Quantities such as Agreement(t), internal coherence Aᵢ(t), the recovery time constant τ, and the critical percolation threshold pc were measured to assess stability, …

Techno-Enviro-Economic Analysis Of Precipitated Calcium Carbonate Production From Carbon Dioxide In Cement Industry Flue Gas And Calcium Hydroxide, Natalia Debora Panggabean, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

CCUS is a technological solution to reduce emissions from the cement industry, which is the second largest CO2-intensive industry. This study aims to analyze technical, economic, and environmental performance of Precipitated Calcium Carbonate (PCC) synthesis in cement industry flue gas. The process simulation includes the CO2 capture system from cement plant, CO2 captured used as feedstock for PCC synthesis process through its reaction with calcium hydroxide. The simulation was carried out using ASPEN Plus software. Technical analysis was performed to determine the CO2 capture efficiency and PCC synthesis efficiency. Economic analysis was conducted to calculate CO2 capture cost and production …

Feasibility Analysis Of Thermal Oxidizer To Determine Remaining Life Using Fitness- For-Service Level 3 Method, Yudhi Yudistirawan, Donanta Dhaneswara, Wahyuaji Narottama Putra, Gama Widyaputra, Dewi Kurnia Suci, Agung Putra Mahardhika

Journal of Materials Exploration and Findings

An aged thermal oxidizer (TOX) in the oil and gas industry necessitates a comprehensive evaluation to ensure its continued safe operation. This study presents a Remaining Life Assessment (RLA) and a Fitness for Service (FFS) evaluation for the four main components of the TOX, in accordance with API 510, API 579/ASME FFS-1, and ASME BPVC Section VIII Div-1 standards. The investigation includes the determination of maximum stress and maximum temperature required to assess the operational viability of the reactor. The four components are radiant, convection, transition, and stack sections—were modeled using the finite element method (FEM). Following the geometric modeling, …

Assessing Passenger Electric Vehicle Growth Strategies And Their Impacts On Electricity Demand Load And Co2 Emissions In Aceh Province To Achieve Net Zero Emission Target By 2060, Taufik Hidayat, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

The electrification of the transport sector is a crucial pathway for achieving Indonesia’s Net Zero Emissions (NZE) target by 2060. This study assesses the potential impact of passenger electric vehicle (EV) penetration on electricity demand and CO2 emissions in Aceh Province through a scenario-based modelling approach. Two policy-aligned scenarios are assessed: a low-penetration (LP) scenario and a high-penetration (HP) scenario. Using the Gompertz model and the ASIF framework, total CO2 emissions were projected from 2020 to 2060. Results show that although higher EV penetration reduces direct emissions from internal combustion engine (ICE) vehicles, total CO2 emissions increase more significantly under …

Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass

Northeast Journal of Complex Systems (NEJCS)

By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and …

Numerical Study Of Nutrient Mixing In Trabecular Bone In Microgravity, Disuse And Normogravity, Sagar Gharti

Doctoral Dissertations and Master's Theses

Mechanical loading is known to regulate bone remodeling by driving interstitial fluid flow which stimulates cells and drives nutrient transport within the trabecular network. In microgravity, the absence of mechanical stimulation or loading suppresses convective flow processes, causing diffusion-driven nutrient mixing and renewal, and accelerated bone loss. This thesis investigates how oscillation frequency and trabecular bone density jointly control nutrient mixing and wall shear stress within trabecular cavities.

A computational fluid dynamics (CFD) framework is developed in STAR-CCM+ using a soft-cap oscillation model that mimics cyclic compression. Three idealized trabecular morphologies are simulated across different frequencies to represent microgravity or …

Reconstruction Of Information System Acceptance Model In The Era Of Integrated Artificial Intelligence: A Systematic Literature Review, Ilham, Merlin Apriliyanti

Library Philosophy and Practice (e-journal)

This study aims to explain the rapid development of Artificial Intelligence (AI) which has driven significant transformations in the development and use of information systems. However, most classical information system acceptance models, such as the Technology Acceptance Model (TAM) and  (UTAUT), have not been able to fully explain the unique characteristics of AI-based systems that are autonomous, adaptive, and complex. This study aims to reconstruct the information system acceptance model in the era of integrated AI through a Systematic Literature Review (SLR) approach. This study was conducted using the PRISMA protocol on 130 leading scientific articles indexed by Scopus and …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …