Mechanical Engineering Commons^™

Data-Driven Discovery Of Extreme Thermal Materials By High-Throughput Computation And Machine Learning, Joshua Ojih

Theses and Dissertations

The quest for materials with extraordinary properties has been a longstanding endeavor in material science and engineering, driving future technological advancement. However, the discovery of such materials is non-trivial. Recent advancements in computational methods, particularly the integration of machine learning (ML) techniques with density functional theory (DFT), have opened new avenues for accelerating the discovery of materials with exceptional and extreme properties. This dissertation focuses on developing a synergistic approach and workflow combining ML and DFT to identify materials with properties that are pushed beyond current limits, using lattice thermal conductivity (LTC) as a case study of the workflow.

We …

Integrating Digital Twin Technology For Real Time Blockage Detection In Water Cooled Electronics, Richard Scott Hainey Jr.

Theses and Dissertations

This paper presents a culmination of research into integrating Digital Twin (DT) technology in water-cooled electronic systems to improve system reliability by detecting faults in the cooling system that maintains the proper operation of heat-producing electronic components and systems. A DT is a virtual representation of a physical twin (PT). This PT can represent real-world systems, individual components, or processes. Using the DT, operators can gain insight into the behavior and characteristics of the PT, thereby facilitating informed decisions to improve its health and optimize processes. The DT system is designed to detect obstructions forming in the waste heat-producing components …

Interpretation Of Surface Roughness Of Stainless Steel 316l In Laser Powder Bed Fusion Additive Manufacturing, Tianyu Zhang

Theses and Dissertations

Laser Powder Bed Fusion (L-PBF), a widely used metal additive manufacturing (AM) method, is emerging as a key technology in the modern manufacturing industry. Its applications span across aerospace, transportation, energy, and biomedical industries, aiming to maximize product functionality, quality, and manufacturing efficiency.

Surface roughness, an important measure of product quality, impacts geometrical tolerances and plays a critical role in mechanical and functional properties. Although post-process techniques such as machining, shot peening, and chemical processing can be used to refine surfaces, internal surfaces in complex geometries remain difficult to treat, limiting part performance due to undesired surface features. The …

Investigation And Comparative Analysis Of Onset Of Nucleate Boiling (Onb) In A Narrow Rectangular Channel In Microgravity And Earth Gravity Environments, Fahim Foysal

Theses and Dissertations

Understanding the onset of nucleate boiling (ONB) in different gravitational environments is crucial for a wide variety of industrial and space applications of flow boiling systems for thermal management. This thesis provides a comparative analysis of ONB in both microgravity (µg) and Earth gravity (1g) environments, with the aim of identifying the key differences. NASA’s experimental facility called Flow Boiling and Condensation Experiment (FBCE) equipped with Flow Boiling Module (FBM) was used for both the experiment onboard the International Space Station (ISS) and on Earth. The experiment was conducted in a rectangular channel of 5mm (depth) ×2.5 mm (width) ×114.6 …

Leveraging The Usage Of Blockchain Towards Trust-Dominated Manufacturing Systems, Philip Joseph Samaha

Theses and Dissertations

Smart Manufacturing has elevated manufacturing processes, transitioning from automated systems to autonomous ones. This evolution has heightened the significance of data within manufacturing facilities. The role of data has evolved from solely monitoring processes to both monitoring and extracting insights from these processes, facilitating precise control. In this context, the data infrastructure plays a critical role, encompassing both internal data circulating within the facility—such as information exchanged between controllers and actuators—and external data transmitted to and from outside entities. When the factory's cyber infrastructure is connected to the internet, security concerns escalate significantly, amplifying associated risks. Therefore, the integration of …

Mechanics Based Characterization Of Elastic Metamaterials, Mamdudur Rahman

Theses and Dissertations

In bandgap engineering there is a shortage of systematic design approach which enables one to select design variables to achieve bandgap in desired frequency range. Tools that can address this can open new areas of interest, especially since phononic crystals with low frequency bandgaps have multitude of applications in attenuation of structural vibration. Furthermore, mechanics-based characterization of phononic crystals had not seen much progress in the recent years while a lot of applied research had been conducted on phononic materials with material phase periodicity and other factors taken into consideration. This work aims to propose a systematic characterization approach of …

Redefining Gas Turbine Engine Development: A Digital Twin Framework Informed By Operational Dynamics And Numerical Analysis, Sowmya Raghu

Theses and Dissertations

Gas Turbine Engines (GTEs) serve as primary propulsion systems in aviation and are key for power generation units in various industrial applications. The conventional Gas Turbine Engine Development and Monitoring Lifecycle (EDML) typically encompasses six stages: preliminary design, numerical analysis, prototyping and testing, manufacturing, systems integration, and subsequent systematic monitoring processes. This dissertation redefines the gas turbine engine design and development process by synergistically integrating design capabilities, real-time operational data, and predictive maintenance through the implementation of digital twins. The primary objective is to establish a comprehensive framework for gas turbine engine design by utilizing thermodynamic and aerodynamic modeling, supported …

Temporal Forecasting Of High-Rate Dynamic Using Physics-Informed Machine Learning And Hardware-Software Co-Design, Puja Chowdhury

Theses and Dissertations

Due to aging, fatigue, corrosion, and even natural disasters; the health of the structure is prone to degradation throughout its service life. The explosively-fast growing efforts on Structural health monitoring (SHM) always try to exploit different aspects of the automation of damage detection, localization, and prognosis tasks. One of the main challenges is the hardware and software co-design to implement the model in real-life situations. On the other hand, the fast-advancing artificial intelligence draws the researchers' attention to adopt different data-driven approaches in this field. This brings other challenges like domain-specific model adaptation, data bias, data scarcity, model validation by …

Boosting Steam Tolerance And Electrochemical Performance Of An La0.6Sr0.4Co0.2,Fe0.8O3− Δ-Based Air Electrode For Protonic Ceramic Electrochemical Cells, Lei Wu, Jiqiang Sun, Huiyang Qi, Baofeng Tu, Chunyan Xiong, Fanglin Chen, Peng Qiu

Faculty Publications

La_0.6Sr_0.4Co_0.2Fe_0.8O_3−δ (LSCF) is the state-of-the-art air electrode material for solid oxide electrochemical cells using oxide-ion electrolytes, yet its application in proton ceramic electrochemical cells (PCCs) remains limited, mainly attributed to its instability under operating conditions of high temperature and high humidity. To address this issue, coating a PrCoO_3−δ (PCO) catalyst onto the LSCF scaffold has been evaluated in this study. The introduction of the PCO coating not only enhances the LSCF electrode's electrochemical performance but also significantly improves its steam tolerance by preventing direct contact between steam and …

First-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations: Mathematical Framework And Illustrative Application To The Nordheim–Fuchs Reactor Safety Model, Dan Gabriel Cacuci

Faculty Publications

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (1st-CASAM-NODE) which yields exact expressions for the first-order sensitivities of NODE decoder responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim–Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, …

Thermodynamic Modeling Of Uranium Nitride With Select Actinides And Fission Products, Eric Reece Mcmanus

Theses and Dissertations

Uranium mononitride fuel is being investigated as a potential nuclear fuel for a Westinghouse lead-cooled fast reactor due to factors such as its high uranium density, high melting point, and favorable thermal conductivity. To obtain an understanding of the thermochemical behavior of UN fission products and minor actinides, thermodynamic data was obtained from various resources to create a database to represent the behavior of the fuel. This database was used to generate an Ellingham diagram to represent the relative thermodynamic stability of the phases over the reactor temperature range. A simulation was run computing the equilibrium state of the fuel, …

Microchannel Slip Flow Characteristics By Time Travel After Photobleaching Velocimetry, Brandon James Sellers

Theses and Dissertations

Interfacial science follows the study of observing behavior between two or more phases of matter when in contact. For example, a liquid solution passes through a microchannel, and the walls interact with the fluid shearing along the surface. The fluid particles develop momentum changes from interfacial phenomena and slip along the wall begins to affect the fluid body. Slip flow is a name for the phenomenon, and with it, modeling velocity for the interfacial behavior demands both resolution and minimal interference. Laser-induced fluorescence photobleaching anemometry (LIFPA) works as a sound method for acquiring data on microchannel flow, but it needed …

The Effect Of Chromium Coatings On Hydrogen Uptake In Zirconium Alloy Nuclear Fuel Cladding, Jorie Lyn Walters

Theses and Dissertations

The amount of hydrogen in a nuclear reactor can have a profound impact on its performance and safety when it is absorbed into or released from fuel rods. Hydrogen pickup in modern fuel cladding materials has been minimized by alloying additions and microstructural texture engineering, but these materials are still susceptible to hydrogen release during high temperature oxidation. The nuclear accident at the Fukushima Daiichi power plant in 2011 resulted in hydrogen gas production and subsequent explosions which led the United States Department of Energy to initiate a program to develop enhanced nuclear fuel cladding materials. New cladding materials include …

A Holistic Quality Management Model For Optimization Of Quality Assurance In Manufacturing, Devon Blakeney Clark

Theses and Dissertations

Quality Management (QM) is essential in manufacturing to ensure products are consistent and functional every time. Consumers expect high quality products that last, and industries unable to accomplish this are destined to fail. Therefore, product quality has always been at the forefront of manufacturer decision making, though it is normally viewed as a given more than as a goal. This means that businesses want quality because it is needed for their survival, but there has not been consideration for how to incorporate innovation into this essential field. Quality needs to be viewed holistically with regards to all manufacturing factors that …

A Plug-And-Produce Connectivity Framework For Manufacturing Systems, Theodros Abraham Tarekegne

Theses and Dissertations

The Industrial Internet of Things (IIoT) movement has birthed technologies that enable the fusing of physical and digital environments. However, the extensive number of available options for industrial communication and data formatting has remained a barrier to achieving digital knowledge synonymy in industry. There have been previous attempts to establish standards for industrial connectivity and communication, but legacy machines, as well as custom and non-proprietary devices, still face issues communicating data with other manufacturing equipment. To address these challenges, the Industrial Internet of Things initiative has led to the creation of the Plug and Produce (PnP) concept to facilitate the …

Experimental And Computational Understanding Of Solid Oxide Iron Air Battery Performance, Chaitali Morey

Theses and Dissertations

Long-duration energy storage (LDES) (10+ hours) is considered a key technical solution for a widespread penetration of renewable energy into the utility market. However, the currently available storage technologies are limited to less than 10 hours for cost reasons. The benchmark Li-ion battery technology would be economically prohibitive if the storage time goes beyond 4 hours. Therefore, developing new low-cost LDES-compatible battery technologies is highly desirable. A solid oxide iron air battery (SOIAB) has been developed which consists of a reversible solid oxide cell (RSOC) and energy storage unit (ESU) of an iron bed. This battery is considered a promising …

Crystal Plasticity Modeling Of Heterogeneous Microstructure Of Additively Manufactured Metals, Md Mahabubur Rohoman

Theses and Dissertations

Additive manufacturing (AM) has emerged as a promising technique in the manufacturing industry for producing complex metal components as it provides shape freedom and simplistic processing chain.

Powder bed fusion is the widely used AM technique that uses laser or electron beam as the energy source to melt the metal powder and deposit it in a layer-by-layer fashion. While doing so, the previously molten layers are constantly are in re-heating and re-cooling processes which end up creating an intricate solidification for the deposited layers. Due to the complexity involved in the thermal cycles for the solidification process, columnar grains develop. …

Application Of Machine Learning Techniques And The Unscented Kalman Filter To Real-Time Gas Turbine Clearance Prediction, Donald Earl Floyd

Theses and Dissertations

The growth in renewable energy sources and retirement of large baseload coal-fired power stations has led to an accompanying decrease in reliability and security of the electrical grid. Since renewable energy sources are typically non-dispatchable, this can lead to blackouts and/or brownouts for customers. Heavy duty gas turbine power plants (HDGT) offer a solution to this problem. HDGTs are dispatchable, clean, and offer flexibility in the fuel they consume, but operational limitations must be well understood to fully exploit their benefits.

One of the main operational limitations is the tip clearances in the gas turbine. In many cases, the gas …

Enhanced Two-Phase Heat Spreading Enabled By Dropwise Condensation, Kai Luo

Theses and Dissertations

The rapidly increasing power density of electronic systems has raised challenges for thermal management. Efficient heat spreading plays an important role in distributing high-density heat to the large-area heat sink and maintaining the junction temperature below the temperature limit during operation. Vapor chambers, a type of flat heat pipe utilizing two-phase heat transfer and fast travel of vapor flow, can achieve far more efficient two-dimensional heat spreading than most conduction-based thermal ground plane materials. By promoting dropwise condensation in vapor chambers, the thermal performance and scalability can be further improved due to the enhanced condensation heat transfer and unique droplet …

Simultaneous Crack & Wave Propagation And Acoustic Emission Signal Modelling Using Peri-Elastodynamic, Md Mushfiqur Rahman Fahim

Theses and Dissertations

This work presents the use of Peri-Elastodynamic, a guided wave simulation method based on meshfree non-local Peridynamics theory. To model simultaneous crack and wave propagation simulation and its application on Acoustic Emission (AE) signal modelling, a new formulation is presented. The field of nondestructive evaluation (NDE) and structural health monitoring (SHM) is slowly embracing the advancement in Machine Learning (ML) / Artificial Intelligence (AI) for better and cost-effective assessment of structures and damage prediction. AI/ML can revolutionize the NDE/SHM field by automating the data collection and analyzing processes. However, the big challenge is that the model needs a sheer amount …

Review Of Fourth-Order Predictive Modeling And Illustrative Application To A Nuclear Reactor Benchmark. I. Typical High-Order Sensitivity And Uncertainty Analysis, Dan Gabriel Cacuci, Ruixian Fang

Faculty Publications

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to nuclear energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, while yielding best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally …

Surface Acoustic Waves-Based Point-Of-Care Biosensor, Debdyuti Mandal

Theses and Dissertations

A biosensor is an analytical tool consisting of biologically active material used in close conjunction with a device that converts a biochemical signal into a quantifiable electrical signal. The early detection of the disease biomarkers can enhance the increased curability of the disease, reduce healthcare costs, and finally, improve the quality of life for patients. Thus, for the following purpose, there is always a need for an effective biosensor as a diagnostic device. The biosensor typically consists of an actuator, a bio-recognition component, and a transducer that converts captured signals into a meaningful display. The bio-recognition component uses biomolecules to …

Multidimensional Simulation Of Cool Diffusion Flame, Ejaz Ahmed

Theses and Dissertations

Understanding the behavior of spherical cool diffusion flames in microgravity conditions is crucial for advancing combustion research. This knowledge has significant implications for both fundamental science and practical applications, such as spacecraft fire safety and the development of advanced, high-efficiency engines that benefit from low-temperature chemistry. Spherical cool diffusion flames are typically characterized by peak temperatures between 500 and 1000K and are often followed by the radiative extinction of a hot flame. Some low-temperature ignitions can sustain indefinitely at around 700K, leading to chain-branching pathways that produce intermediate species such as C2H4, H2O2, HO2, CH2O, CH3O, and HCO. In some …

Accelerating Numerical Modeling And Optimization Of Structural Mechanical Systems, Fatemeh Hashemian

Theses and Dissertations

This research proposal presents Bayesian optimization and reduced order modeling methods to accelerate numerical analysis and design of structure mechanical system. First, a holistic framework of Bayesian optimization (BO) based on parameterized numerical models and genetic algorithm-guided adaptive sampling is developed to automate and accelerate the design of a front-loading washing machine. The research aims to address challenges associated with the model parameterization and global optimization and design. A multibody dynamics model of the washing machine incorporating a set of 9 key design variables is developed. The design variables are implemented to enable automated modifications of the dynamics model for …

Development Of A Large Format Additive Manufacturing System Based On An Off-The-Self Pellet Extruder, Aywan Das

Theses and Dissertations

Large Format Additive Manufacturing (LFAM), or Big Area Additive Manufacturing (BAAM), was introduced to resolve the limitations of the low deposition rate, low scalability, and therefore long print times, of traditional 3D printing methods when applied to the manufacturing of large structures and tooling. LFAM can be used to overcome the high conventional tooling costs of large structures. However, even with robotic setups, LFAM still mainly relies on quasi-planar, 2.5D printing strategies. This fails to reap the advantages of multi-axis printing, such as improved adhesion, reduced support material use, and the ability to create complex curved surfaces. In this research, …

Correction: Graph Theory And Graph Neural Network Assisted High-Throughput Crystal Structure Prediction And Screening For Energy Conversion And Storage, Joshua Ojih, Mohammed Al-Fahdi, Yagang Yao, Jianjun Hu, Ming Hu

Faculty Publications

Correction for ‘Graph theory and graph neural network assisted high-throughput crystal structure prediction and screening for energy conversion and storage’ by Joshua Ojih et al., J. Mater. Chem. A, 2024, 12, 8502–8515, https://doi.org/10.1039/D3TA06190F.

On page 8511 in section 3.2 of the published article, the text “The single values of bonding and antibonding for each structure are obtained by performing integration over COHP curves for each atomic pair as evaluated by the LOBSTER package” should have included citations to six references. The missing references are listed below as ref. 1–6.

The Royal Society of Chemistry apologises for …

Cognitive Manufacturing: Definition And Current Trends, Fadi El Kalach, Ibrahim Yousif, Thorsten Wuest, Amit Sheth, Ramy Harik

Publications

Manufacturing systems have recently witnessed a shift from the widely adopted automated systems seen throughout industry. The evolution of Industry 4.0 or Smart Manufacturing has led to the introduction of more autonomous systems focused on fault tolerant and customized production. These systems are required to utilize multimodal data such as machine status, sensory data, and domain knowledge for complex decision making processes. This level of intelligence can allow manufacturing systems to keep up with the ever-changing markets and intricate supply chain. Current manufacturing lines lack these capabilities and fall short of utilizing all generated data. This paper delves into the …

A Redox-Reversible A/B-Site Co-Doped Bafeo3 Electrode For Direct Hydrocarbon Solid Oxide Fuel Cells, Haixia Li, Wanhua Wang, Kai Zhao, Ka-Young Park, Taehee Lee, Ramin Babazadeh Dizaj, Andreas Heyden, Dong Ding, Fanglin Chen

Faculty Publications

Solid oxide fuel cells (SOFCs) can directly convert the chemical energy in fuel to electrical energy with fuel flexibility; however, the conventional nickel-based anodes face great challenges due to coking upon direct oxidation of hydrocarbon fuels and redox instability. Thus, developing new anode materials which can provide high coking resistance as well as redox stability is crucial. In this work, Ba_0.6La_0.4Fe_0.8Mo_0.1Ni_0.1O_3−δ (BLFMN) has been synthesized in air using a sol–gel combustion method, resulting in a dual phase consisting of a cubic BLFMN main phase and scheelite BaMoO_{4 …}

The Second-Order Features Adjoint Sensitivity Analysis Methodology For Response-Coupled Forward/Adjoint Linear Systems (2nd-Fasam-L): Mathematical Framework And Illustrative Application To An Energy System, Dan Gabriel Cacuci

Faculty Publications

The Second-Order Features Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “2nd-FASAM-L”), presented in this work, enables the most efficient computation of exactly obtained mathematical expressions of first- and second-order sensitivities of a generic system response with respect to the functions (“features”) of model parameters. Subsequently, the first- and second-order sensitivities with respect to the model’s uncertain parameters, boundaries, and internal interfaces are obtained analytically and exactly, without needing large-scale computations. Within the 2nd-FASAM-L methodology, the number of large-scale computations is proportional to the number of model features (defined as functions of model parameters), as opposed to …

Design Of A Launchable Remote-Controlled Rover And Protective Aeroshell, Matthew Loewer, Colby Weeks, Lake Williams, Jackson Zazzaro

Senior Theses

Planetary rovers, vehicles that can traverse challenging terrain, have excelled in their exploration missions to other celestial bodies. They have been especially suitable for exploring Mars, as rovers such as Opportunity and Perseverance have collected valuable geological, atmospheric, seismic, and magnetic information from the Martian surface. Rovers will remain vital in future space exploration missions, and it is necessary to understand their design and functionality. This paper focuses on the design and prototyping of a miniature rover that can survive the rough Martian terrain while collecting and submitting environmental data for scientific analysis. The design is based off proven Martian …