Computational Engineering Commons^™

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 …

Generalized Planning Using Language Models And Its Applications, Vishal Pallagani

Theses and Dissertations

Planning is a fundamental capability for intelligent systems, yet classical planners remain difcult to scale and generalize across domains due to their reliance on hand- engineered models, brittle search procedures, and limited adaptability. These limita- tions constrain real-world applications that require fexible reasoning, robust decision- making, and the ability to operate across diverse environments.

Large language models have emerged as powerful learners supported by their ar- chitectures and large-scale training data, demonstrating strong capabilities in tasks such as question answering, code generation, summarization, and reasoning. Moti- vated by their broad generalization abilities, I investigate whether language models can be systematically …

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 …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Trusted Forms—The Case Of Barack Obama’S Birth Certificate, Karl-Heinrich Schmidt, Frederik Schlupkothen

Proceedings from the Document Academy

Documents can be understood as containers for information that enable remote communication between people across space and time. They are therefore fundamentally subject to issues of trust. The theoretical treatment of documents as a means of remote communication has a long history and has arrived in the age of electronic document exchange, as shown by the work of R. T. Pédauque, which is taken as a starting point here.

To take theory further, form-based documents are discussed here as an example. Form-based documents control the information provided by fillers by specifying form fields. The core of this paper is to …

Mechanical Characterization And Modeling Of Rat Myocardia Under The Influence Of Epirubicin, Abdallah Mahmoud Alkhaiyat

Theses and Dissertations

Cancer remains a predominant health challenge that is responsible for a significant portion of global morbidity and mortality. Epirubicin (EPI), a chemotherapeutic anti-cancer drug, has shown remarkable efficacy in combating various malignancies. However, it is known to have undesirable side effects on the heart, collectively referred to as cardiotoxicity. This research investigates the adverse effects of chemotherapy on cardiac contractility through an in vitro examination of the mechanics of healthy and infarcted animal heart tissues. Electrically stimulated slices of rat ventricular tissue were tested using an isometric force measurement tissue bath. The tissue slices were subjected to uniaxial stretching, allowing …

A Virtual-Reality-Based Dental Simulator For Endodontics With Automated Formative Feedback, Yousef Salah Abo El Ela

Theses and Dissertations

Advancements in virtual reality (VR) and haptic technology are transforming the landscape of medical and dental education, offering new avenues for safe, immersive, and repeatable training experiences. Within dentistry, endodontics presents unique challenges for preclinical education due to anatomical complexity, limited access to extracted teeth, ethical concerns, and the shortcomings of conventional plastic models. Despite endodontics specific plastic teeth being available, they fall short of replicating the hardness of real extracted teeth, are relatively costly compared to generic plastic teeth, and are ultimately a disposable item which makes them inadequate as a sustainable long-term solution. Extracted teeth do a much …

Mechanistic Auditing Of Privacy Retention In Llm Summarization, Samreen Begum

Computer Science and Engineering Theses - Archive

Anonymized summarization aims to produce useful summaries while replacing person names with placeholders such as [PERSON]. In practice, privacy is often evaluated by checking that no real names appear in the generated text. However, suppressing a name in the output does not guarantee that the model has removed identity information from its internal computation. This gap is critical in collaborative inference frameworks, where intermediate internal states (ISs) are exposed for safety auditing. We study this question in a controlled setting where a language model reads a document containing a real name and is required to generate a summary that replaces …

Mapping Leo Satellite Internet Performance Using Mobile Starlink Deployment, Annika Govil, Jacob Gray

UROP Posters

High-speed, low-latency internet connectivity on the move is a critical challenge for applications in connected vehicles, disaster response, and remote education. While terrestrial networks such as 4G or 5G are widespread, they lack coverage in remote or rural geographic areas.

Low Earth Orbit (LEO) satellite constellations, such as SpaceX's Starlink, promise global high-bandwidth, low-latency internet. However, their performance is well-documented in stationary scenarios, while data for *mobile* applications is scarce. This project explores the feasibility and real-world performance of LEO satellite internet while in motion.

Current research documents the performance of LEO satellite constellations in stationary settings. However, data concerning …

Deterministic Black-Box Context-Free Grammar Inference: Scaling From Small To Big Languages, Mohammad Rifat Arefin

Computer Science and Engineering Dissertations

Context-free grammars are essential for a number of software engineering tasks like program understanding, debugging, and grammar-based testing. However, formal language descriptions (i.e. grammars) are often unavailable, outdated, or inaccessible because parsers are closed-source or cannot be instrumented. Black-box grammar inference addresses this gap using only valid sample programs and parser acceptance decisions. The problem is challenging because finite samples rarely exercise all language features or their combinations, while the inference process cannot inspect the parser’s internal representation of syntax. This dissertation develops deterministic techniques for black-box context-free grammar inference. The first tool, TreeVada introduces the structural assumption that balanced …

Apache Hadoop Installation And Configuration Steps, Safet Jahaj

Open Educational Resources

This tutorial covers the installation and configuration steps of Apache Hadoop on a Windows operating system.

Generative Imaging For Computational Pathology, Md Jillur Rahman Saurav

Computer Science and Engineering Dissertations

Hematoxylin and eosin (H&E) staining remains central to cancer diagnosis, providing morphological information essential for pathological assessment. Immunohistochemistry (IHC) and newer multiplexed imaging technologies complement H&E by revealing molecular information critical for accurate tumor subtyping and treatment decisions. In practice, however, H&E and IHC are obtained from different consecutive sections that are not spatially aligned, comprehensive multiplexed panels are expensive and tissue-consumptive, and not all stains are available at every clinical site, limiting comprehensive molecular profiling and the full diagnostic potential of these technologies in clinical practice. This dissertation addresses these gaps through three complementary generative deep learning studies in …

Clear Skies, Avery C. Munn

Williams Honors College, Honors Research Projects

Air quality impacts public health, environmental sustainability, and quality of life. However, accurate and easily accessible short-term air quality forecasting is challenging to find. This project, Clear Skies, presents a machine learning–based system for forecasting next-day Air Quality Index (AQI) levels across regions in Ohio. By using historical pollutant data with variables such as temperature, humidity, wind speed, and atmospheric pressure, the system finds relationships that traditional statistical models often don’t show.

Machine learning models are evaluated alongside AI techniques to find the environmental factors that influence AQI predictions. This helps reduce the “black box” nature of many AI systems …

Quantifying Hemodynamics In Implantable Cardiac And Renal Support Devices Using Computational Modeling, Alexander D. De Oliveira

Summer Research Program Abstracts

No abstract provided.

Hyperglycemia Detection From Single-Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes need to measure their glucose levels in order to determine how much insulin or medicine …