Digital Commons Network^™

A Framework For Optimizing Creep Model Parameters From Conventional And Accelerated Creep Tests, William D. Day

Graduate Studies Theses and Dissertations 2026

The demand for efficiency in power generation and propulsion requires higher firing temperatures and reduced cooling air consumption which raises metal temperatures. This makes simplistic creep evaluations, such as Larson-Miller and Orr-Sherby-Dorn parameters, inadequate. Finite element analysis (FEA) must simulate primary and secondary creep, predict failure, and provide design guidance. Gas turbine components, expected to last over 100,000 hours, often require extrapolation of limited test data for new materials. It is essential that robust creep simulations be developed efficiently, accurately, and effectively use limited test data.

This dissertation describes an optimized framework for efficient creep testing and rapid construction of …

Thermomechanical Modeling Of Transpiration Surfaces For Hypersonic Propulsion, Spencer D. Smith

Graduate Studies Theses and Dissertations 2026

Hypersonic flight vehicles are a promising form of high speed passenger transport and efficient space access architectures. However, they are fundamentally a thermally limited technology. High heat fluxes exceeding 10 MW/m2 and gas temperatures between 3000-4000K can be found both within the engine, and on the outer surface. Current conventional engineering materials are non-viable at these conditions. In order to make these materials viable, active cooling strategies could be utilized. One particularly promising type is transpiration cooling, where a coolant is diffused through a porous surface. Although researched heavily in the 1960s, adoption is still minimal. Part of the reason …

Towards Supporting Real-Time Estimation Of Vehicle Fuel Consumption And Co2 Emissions In Smart City Applications, Abrar Alali, Stephan Olariu

Computer Science Faculty Publications

This paper evaluates a simplified physics-based energy demand model designed to estimate vehicle fuel consumption and CO₂ emissions—a critical tool for sustainable transportation planning and smart city applications. Unlike data-driven regression models that lack generalizability for user-defined conditions or complex physics-based approaches that rely on extensive, often proprietary data, the simplified model is distinguished by its minimal parameter requirements, depending primarily on a single, overarching powertrain efficiency value. A key contribution is the comprehensive empirical evaluation of the simplified model against official Environmental Protection Agency (EPA) test data across multiple driving cycles and vehicle types, providing a rigorous validation previously …

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

Fused Filament Fabrication Additive Manufacturing Of 17-4 Ph Stainless Steel: Process–Structure–Property Relationships In Magnetic Materials, Maanav Patel

Theses and Dissertations

Additive manufacturing (AM) enables the fabrication of complex metallic components through layer-by-layer processing directly from digital models. Among AM techniques, material extrusion–based processes such as fused filament fabrication (FFF) provide an accessible method for producing metal parts using filament feedstocks composed of metal powders and polymer binders. When applied to precipitation-hardening stainless steels such as 17-4 PH, the processing route and heat treatments can influence the resulting microstructure and functional properties. This work investigates the magnetic behavior of 17-4 PH stainless steel fabricated using FFF and evaluates how heat treatment conditions influence measured magnetic properties. Samples were produced and analyzed …

Scalar Source Localization Using Multi-Sensor Domains Of Dependence In Turbulent Channel Fow, Zejian You, Xiaowei Zhu, Qi Wang

Mechanical and Materials Engineering Faculty Publications and Presentations

Tracking hazardous events such as wildfire smoke, coastal oil spills, or chemical releases in natural environments is complicated by turbulent dispersion and molecular diffusion. This study presents a method to localize pollutant sources rapidly and accurately using infinite time-averaged measurements from a multi-sensor network, leveraging the duality between mean forward and adjoint scalar fields. The forward-adjoint duality states that measurements at the sensor (forward feld) are equal to the adjoint field at the source, providing crucial spatial information about the source. Consequently, the adjoint scalar fields can be interpreted as the domain of dependence for the sensor observations [1, 2]. …

Reaching The Intrinsic Performance Limits Of Superconducting Nanowire Single-Photon Detectors Up To 0.1 Mm Wide, Kristen M. Parzuchowski, Eli Mueller, Bakhrom G. Oripov, Benedikt Hampel, Ravin A. Chowdhury, Sahil R. Patel, Daniel Kuznesof, Emma K. Batson, Ryan Morgenstern, Robert H. Hadfield, Varun B. Verma, Matthew D. Shaw, Jason P. Allmaras, Martina J. Stevens, Alex Gurevich, Adam N. Mccaughan

Physics Faculty Publications

Superconducting nanowire single-photon detectors combine high detection efficiency, low noise, and excellent timing resolution, making them a leading platform for photon-counting applications. However, despite decades of materials and fabrication research, detector performance has never been shown to match theoretical performance expectations. Here, we demonstrate in situ tuning of a detector from its typical, suboptimal operation, to a regime limited only by material quality, allowing the device to reach its intrinsic performance limit. Our approach is based on current-biased superconducting “rails” placed on either side of the detector that redistribute current across its width to achieve peak performance. This technique reduces …

Swarm Of One: Self-Organization In Multicellular Robots, Trevor Riley Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

Designing robots traditionally relies on centralized, top-down methods that constrain adaptability and resiliency, producing systems optimized for specific tasks. However, such systems often fail in complex environments, such as extraterrestrial, disaster, or natural settings, where designers cannot foresee every scenario a robot may encounter. Achieving autonomy in these contexts requires robots that are resilient and capable of adapting to the unknown. Multicellular organisms exhibit this adaptability through self-organization, where complex structures and behaviors emerge from local interactions among their cells. Such organisms can be viewed simultaneously as a single entity and a swarm of cooperating cells, i.e., a Swarm-of-One.

This …

Development And Validation Of A Multi-Output Neural Network-Based Virtual Temperature Sensor For Electric Vehicle Thermal Management, Dalton Michael Wiggins

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicles (BEVs) rely on accurate thermal management to ensure component performance, efficiency, safety, and long-term durability. Critical propulsion system components, including electric motors and high-voltage battery packs, are commonly monitored using physical temperature sensors. However, these sensors increase system cost, introduce additional hardware complexity, and may be impractical for directly measuring temperatures at critical internal locations. Virtual temperature sensors (VTSs) provide a software-based alternative by estimating component temperatures using readily available vehicle operating data.

This research presents the development and validation of a long short-term memory (LSTM) neural network-based virtual temperature sensor capable of simultaneously estimating the motor …

Smartbot V3: A Scalable Educational And Research Robotics Platform And Decentralized Construction Framework, Robert Tyler Cook

Graduate Theses, Dissertations, and Problem Reports (ETD)

Autonomous robotic systems are increasingly used in both engineering education and robotics research, creating a need for systems capable of supporting both within a common platform. This thesis presents SMARTbot V3, a scalable robotics platform developed to support undergraduate robotics education and multi-robot research.

SMARTbot V3 is a differential-drive mobile manipulator incorporating a 3-degree-of-freedom manipulator, LiDAR, RGB cameras, onboard computation, and Robot Operating System 2 (ROS2) software. The platform was designed to support scalable deployment through standardized hardware, modular construction, and common software. A fleet of twenty robots was manufactured and deployed for both educational and research activities. Educational validation …

Bridging Physics-Based Modeling And Machine Learning To Predict Material Behavior: Applications In Fatigue Crack Growth And Dielectric Property Characterization, Ansan Pokharel

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation integrates physics-based modeling with machine learning (ML) to predict how materials behave under complex thermal and mechanical conditions. A key innovation of this work is the use of finite element analysis (FEA) to supplement experimental data. This approach creates more diverse and representative synthetic datasets, helping to reduce the limitations and biases that arise when training ML models solely on experimental measurements. The research focuses on two applications: improving the prediction of fatigue properties in superalloys and estimating temperature-dependent, high-frequency dielectric properties relevant to microwave-based chemical processing.

In the first study, low-cycle fatigue experiments were performed on the …

A Multiobjective Framework For Joint Coverage And Motion Planning In Uav Inspection Tasks, Luis Fernando Escobar Carvajal

Graduate Theses, Dissertations, and Problem Reports (ETD)

Unmanned Aerial Vehicles (UAVs) have become essential for data acquisition in complex 3D environments. However, traditional Coverage Path Planning (CPP) methodologies often rely on a sequential pipeline that isolates viewpoint generation from flight path routing. This decoupling fails to account for the interdependence between viewpoint distribution and minimum flight paths, effectively restricting the search space and preventing the identification of a global optimum. This dissertation proposes a unified multi-objective framework for joint coverage and motion planning. The primary contribution of this work is the transition from isolated, sequential steps to a simultaneous optimization of the number and position of viewpoints …

Machine Learning-Based Prediction Of Heavy-Duty Diesel Engine Emissions And Comparative Analysis Against Statistical Models, Abdullah Ahmad Khan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increasing stringency of emissions regulations for heavy-duty (HD) diesel engines necessitates the development of accurate, efficient, and general predictive models for engine-out emissions under steady-state operating conditions. Traditional statistical approaches, while computationally efficient, often fail to capture the inherent nonlinear relationships between the engine operating parameters and emissions formation. In contrast, machine learning (ML) techniques offer a promising alternative by learning the complex patterns directly from experimental data. The present thesis summarizes a comprehensive study on the prediction of steady-state, HD diesel engine emissions using ML models, along with a comparative analysis against conventional statistical modeling approaches.

A high-quality …

Entropic Forces Near Fluctuating Surfaces, Rubayet Hassan

Dissertations

Nanoscale structures are inherently dynamic due to persistent thermal fluctuations. Even in solid materials, these random deformations, driven by ambient thermal energy, can become significant when their characteristic scale approaches that of the structure itself and strongly influence their overall mechanical behavior. Examples of such structures include crystalline membranes, appearing in diverse forms such as nanotubes, nanoribbons, and kirigami/origami structures. Similarly, biological nanostructures, including lipid membranes, microtubules, actin filaments, and DNA, exhibit extreme flexibility and responsiveness due to their low bending rigidity. Numerous physiological processes are intrinsically linked to these thermal fluctuations, including exocytosis and endocytosis, membrane fusion, pore formation, …

Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber

Al-Esraa University College Journal for Engineering Sciences

Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …

Applying Machine Learning Techniques For Early Detection Of Cyber Attacks On Iot Devices, Noor Adnan Allamy

Al-Esraa University College Journal for Engineering Sciences

This research designs, implements, and evaluates a machine learning-based framework for the early detection of cyber attacks targeting Internet of Things (IoT) devices, with a specific focus on the context and challenges present in Iraq. The study conducts a comparative analysis of three supervised learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Networks (DNN)—using a combination of benchmark datasets (NSL-KDD, CIC-IDS-2017, Bot-IoT) and a synthesized dataset adapted to simulate the Iraqi threat landscape. Key performance metrics, including accuracy, precision, recall, and F1-score, were used for evaluation. The proposed Random Forest model demonstrated superior performance, achieving an accuracy …

Ai-Enhanced Heat Transfer Optimization In Magnetic Bio-Nanofluids, Hasan Attyah Shaboot

Al-Esraa University College Journal for Engineering Sciences

This study presents a hybrid Artificial Intelligence–Computational Fluid Dynamics (AI-CFD) framework for optimizing heat transfer in magnetic bio-nanofluids subjected to external magnetic fields. Magnetic bio-nanofluids, composed of biocompatible base fluids containing superparamagnetic nanoparticles, exhibit tunable thermal and flow behavior, making them promising for biomedical and micro-cooling applications. Conventional optimization methods based on experiments or brute-force CFD are computationally expensive and limited in exploring the full design space. To overcome these challenges, an Artificial Neural Network (ANN) surrogate model was developed to predict two key performance indicators, the Nusselt number and the friction factor, with high accuracy (R² > 0.997). The surrogate …

The Role Of The Scenario In Formulating The Contemporary Architectural Text, Rounaq Arif Mohsin, Abbas Ali Hamza, Bashar Shamil Alkhafaji

Al-Esraa University College Journal for Engineering Sciences

In order to create an integrated architectural text, which is a complicated art that blends beauty and practical elements, a rigorous design procedure is necessary. In this situation, the scenario’s role becomes crucial in developing the current architectural text and directing architectural approaches. In order to better understand how the scenario influences the design process and the interactions between various architectural aspects, this project intends to explore and analyze the impact of the scenario in developing and refining architectural text formulation approaches.

The study looks at the idea of a scenario and how it has been used in architecture, as …

Aerodynamics And Heat Transfer In Polymer Blown Film Processing: Experimental And Numerical Investigation, Mohammad Luqman Zulbakri, Nur Atiqah Mat. Rautin, Raa Khimi Shuib, Ku Marsilla Ku Ishak, Auratus Zuratul Ain Abdul Hamid, Mohamad Danial Shafiq, Mohamad Yusof Idroas, Muhammad Khalil Abdullah

Makara Journal of Technology

The effects of airflow dynamics, heat transfer, and mechanical properties on the HDPE blown film extrusion process were examined using a single-lip air ring with a fixed compressed-air valve opening angle of 10°. Reynolds numbers ranging from 9175 to 25911 were analyzed to understand their impact on cooling efficiency, bubble morphology, and film properties. Numerical simulations employing the Standard k−ω turbulence model in ANSYS FLUENT v2023, with mesh refinement achieving y+ ≈ 1, captured detailed flow and heat transfer behavior. Results showed that higher Reynolds numbers significantly enhanced the heat transfer coefficient, with values increasing from 1096 W/m²·K at Reynold …

Numerical Modeling And Experimental Validation Of A High-Temperature Latent Heat Thermal Energy Storage System Using Metallic Phase Change Materials For Concentrated Solar Power Applications, Fouad Hashim Sharhan

Al-Esraa University College Journal for Engineering Sciences

To ensure reliable performance for the power-block of CSP plants, high power density and near-isothermal discharge must be achieved. A robust means of achieving this is through thermal energy storage (TES). High temperature latent heat storage (LHS) with phase change materials (PCMs) can serve these purposes, however the conventional salts used in PCMs typically suffer from low thermal conductivity that limits power density and increases energy storage charging/discharging times. This manuscript investigates ways to address these limitations using high temperature metallic phase change materials (MPCMs) while also developing a validated numerical framework to aid in their design. To this end, …

Thermal Performance Evaluation Of Solar Cooling Systems For Educational Facilities In Baghdad, Yasser Alawi Mohammed Attia Al-Jubouri

Al-Esraa University College Journal for Engineering Sciences

Schools in Baghdad also suffer from poor thermal comfort, which is a common problem in high-temperature and low-humidity arid climates such as that of the city, where using cooling devices leads to a large energy demand and overloads on the national power grid. Such study offers a thorough assessment of the thermal performance of solar-based cooling systems in an efficient manner to be suitable for educational buildings in Baghdad. The analysis is centred on a solar thermal cooling system with absorption as the heat interaction medium, and an experimental characterisation and mathematical simulation itself are performed. A pilot installation, consisting …

Multi-Criteria Decision Making Methods In The Organisations' Maturity Assessment: Prisma And Delphi Techniques Perspectives, Jailos Mrisho Mzumile, Victoria Mahabi, Ismail W. R. Taifa

Tanzania Journal of Engineering and Technology (TJET)

Researchers often find it challenging to identify the appropriate Multi-Criteria Decision Making Methods (MCDM) to employ in various research areas that involve prioritising conflicting alternatives or criteria. A systematic literature review was conducted using the PRISMA technique to determine the most frequently and commonly employed MCDM methods in assessing organisational maturity across its functional areas. A total of 120 articles were identified for review, and a bibliometric analysis was conducted to map the relationships within the identified articles using VOSviewer 1.6.20 software. Moreover, frequent content analysis was performed to determine the most frequently employed MCDM methods in assessing an organisation’s …

Development Of Technical Solutions To Prevent The Formation Of Sludge Regime At The Bottom Of A Well, Rustam Umarkhanovich Juraev, Jonibek Tursunov

Technical science and innovation

The trouble-free process of drilling wells largely depends on the effective cleaning of the borehole. The formation of a slurry regime at the bottom of the well leads to the process of repeated crushing of drilling fines, which in turn leads to a decrease in the mechanical drilling speed, to an increase in the energy consumption of the rock-crushing tool for repeated crushing, and also increases the risk of oil seals. In addition, the formation of a slurry regime at the bottom of the well increases the intensity of abrasive wear of the drilling rig. This article provides a theoretical …

Optimization Of The Operational Efficiency Of Transport And Technological Complexes Based On Simulation Modeling, Kamoliddin Juraboevich Rustamov, Gulom Gaffurdjanovich Atabaev

Technical science and innovation

The article presents a comprehensive analytical approach to improving the operational efficiency of transport and technological machines (TTM) based on simulation modeling. The proposed model integrates the economic and reliability characteristics of maintenance (TM) strategies by describing the operation of aggregates, the probability of failures, and transitions between states — operational (W), faulty (F), and restored (R) — as probabilistic processes. Model parameters are identified using statistical data from real operating conditions and adapted to various types of technical systems. Computer simulation experiments are carried out under multiple scenarios of maintenance periodicity, workload intensity, spare parts resource, and repair policy. …

A Decision Support Model For Building Material And Component Reuse In The Context Of Circular Buildings, Havva Aksel

Journal of Sustainable Construction Materials and Technologies

Construction activities cause significant environmental impacts such as waste generation, pollution, resource consumption, and land use, which are expected to increase with global construction demands. To mitigate these environmental problems, the circular building occurs as an emerging concept depending on in the circular economy, which aims to minimize waste and redefine the “end-of-life” concept by reducing, reusing, recycling, and recovering materials. The reuse of building materials and components (BMCs) from existing structures represents a crucial strategy for achieving circularity in the built environment. Within this framework, design plays a key role. However, designing with reclaimed BMCs remains complex due to …

Characterization And Control Of Rod-Like Soft Robots, Tianrui Li

Mechanical Engineering Research Theses and Dissertations

Micro-scale robotic systems have garnered significant interest for applications in micromanufacturing and biosensing, yet quantitative design rules linking geometry, stiffness distribution, and magnetic actuation to locomotion performance at low Reynolds number remain limited. This thesis investigates magnetically actuated rod-like soft robots composed of hydrogel filaments with embedded micro-magnets and tunable hard:soft length ratios. Four- and eight-magnet swimmers with hard:soft ratios ranging from 1:1 to 2.5:1 and 4:3:1 are fabricated using a simple molding-and-insertion process and tested in water and silicone oil. A triaxial Helmholtz coil system generates rotating magnetic fields from 1 to 10 Hz, and a custom image-processing pipeline …

Expansion Limits Of Meshed Split-Thickness Skin Grafts, Haomin Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Split-thickness skin grafts are widely used to treat chronic wounds. Procedure design requires surgeons to predict how much a patch of the patient's own skin expands when it is meshed with rows of slits and stretched over a larger wound area. Accurate prediction of graft expansion remains a challenge, with current models overestimating the actual expansion, leading to suboptimal outcomes. Inspired by the principles of mechanical metamaterials, we developed a model that distinguishes between the kinematic rearrangement of structural elements and their stretching, providing a more accurate prediction of skin graft expansion. Our model was validated against extensive data …

Mae Enewsbrief July-Sept 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Assessment Of The Melt Quality Of A 30% Scrap Adc12 Aluminium Alloy Using The Inclusion And Fluidity Measurement Instrument (Ifmi) With Mullite Ceramic Filters, Gusti Ruri Ruri Lestari, Sandya Ananda Riswan, Muhammad Anis, Ahmad Ashari, Paramita Vidya Ayuningtyas, Bambang Suharno Prof, Donanta Dhaneswara

Journal of Materials Exploration and Findings

The increasing demand for sustainable practices in the metal casting industry has driven the use of recycled aluminum alloys such as ADC12. However, the addition of aluminum scrap tends to increase oxide inclusions, which reduce melt fluidity and compromise casting quality. This study utilizes the Inclusion and Fluidity Measurement Instrument (IFMI), equipped with mullite ceramic filters, to assess the melt quality of ADC12 aluminum alloy containing 30% scrap. Fluidity and inclusion characteristics were evaluated at five pouring temperatures (660°C, 680°C, 700°C, 720°C, and 740°C). The results show that fluidity increased with temperature, reaching a peak of 84.6 g·s⁻¹ at 740°C, …

Equipment Criticality Analysis To Determine Asset Integrity Management System Scheme In Supporting Production Optimization Scenarios In The Aeging Field, Donny Andryanto, Donanta Dhaneswara

Journal of Materials Exploration and Findings

This research investigates the production decline and cost increase in the X&Y oil and gas fields from 2022 to 2023. Production fell by 34%, while production costs per barrel rose by 79%. To address these issues, a series of optimization processes are proposed. These aim to restructure and enhance the production facilities to reduce current production costs. The optimizations include reducing pressure at the PPP Platform in 2024. Additional steps include shutting down CPP-ORF 14” pipelines and most processes at CPP 2 Platform by 2027 to convert it into an accommodation platform. Further, the plan involves optimizing the release of …