Mechanical Engineering Commons^™

A Digital Twin Based Forecasting Framework For Power Flow Management In Dc Microgrids, Kerry Sado, Jarrett Peskar, Austin Downey, Jamil A. Khan, Kristen Booth

Faculty Publications

The ability to forecast system conditions is integral to the definition and functionality of digital twins. While forecasting methods have been explored for use in digital twin systems, the integration of feedback mechanisms for real-time forecasting and in-situ decision-making in DC microgrids has not been extensively investigated. This research develops a modular forecasting framework tailored for digital twins in DC microgrids to enable real-time monitoring, online forecasting, and decision-making. DC microgrids, characterized by dynamic load variations, benefit from advanced predictive capabilities to maintain stability and operational efficiency. The proposed digital twin-based forecasting framework addresses these challenges by providing real-time predictive …

Si-Doped Ain Using Pulsed Metalorganic Chemical Vapor Deposition And Doping, Tariq Jamil, Abdullah Al Mamun Mazumder, Mohammod Ali, Jingyu Lin, Hongxing Jiang, Grigory Simin, M. Asif Khan

Faculty Publications

In this paper we describe a pulsed metalorganic chemical vapor deposition (MOCVD) Si-doping approach for AlN epilayers over bulk AlN. The Al-rich growth/doping conditions in the pulsed MOCVD process resulted in n-AlN layers with transmission line model currents that were an order higher than for structures on layers that were grown/doped at identical temperatures using the conventional MOCVD process. Our work demonstrated that like the other reported approaches such as UV exposure during growth, the pulsed MOCVD process is also very effective in reducing point defects by the defect quasi-Fermi level-chemical potential control.

Co2 Electrolysis Using Metal-Supported Solid Oxide Cells With Infiltrated Pr0.5Sr0.4Mn0.2Fe0.8O3−Δ Catalyst, Boxun Hu, Ka-Young Park, Asia Sarycheva, Robert Kostecki, Fanglin Chen, Michael C. Tucker

Faculty Publications

Electrochemical conversion of CO₂ to CO is demonstrated with symmetric-structured metal supported solid oxide cells (MS-SOC). Perovskite Pr_0.5Sr_0.4Mn_0.2Fe0.8O_3−δ (PSMF) and Pr₆O₁₁ catalysts were infiltrated into the MS-SOC cathode and anode, using 3 cycles with firing at 850 °C and 8 cycles with firing at 800 °C, respectively. Upon reduction during operation, the perovskite PSMF was transformed to Ruddlesden–Popper structure with a highly efficient electrocatalytic activity. The impact of operating temperature (600–800 °C) and overpotential (0–1.8 V) on the CO₂ conversion was investigated. The highest CO₂ conversion …

Sno2 Modified Csh2Po4 (Cdp) Protonic Electrolyte For An Electrochemical Hydrogen Pump, Minal Gupta, Kangkang Zhang, Kevin Huang

Faculty Publications

CsH₂PO₄ (CDP) is a well-known super-protonic conductor. However, it must operate under high humidity conditions to prevent dehydration and fast conductivity decay. Herein, we report that adding hydrophilic SnO₂ into CDP can suppress the rate of dehydration of CDP, thus stabilizing protonic conductivity over a broader range of water partial pressures (pH₂O). A total of seven compositions of (1 − x)CDP/(x)SnO₂ were prepared, where 5 ≤ x ≤ 40 (wt%), and examined for their phasal, microstructural, and vibrational properties using X-ray diffraction, field emission scanning electron microscopy, and …

Sno2 Modified Csh2Po4 (Cdp) Protonic Electrolyte For An Electrochemical Hydrogen Pump, Minal Gupta, Kangkang Zhang, Kevin Huang

Faculty Publications

CsH₂PO₄ (CDP) is a well-known super-protonic conductor. However, it must operate under high humidity conditions to prevent dehydration and fast conductivity decay. Herein, we report that adding hydrophilic SnO2 into CDP can suppress the rate of dehydration of CDP, thus stabilizing protonic conductivity over a broader range of water partial pressures (pH2O). A total of seven compositions of (1 - x)CDP/(x)SnO₂ were prepared, where 5 ≤ x ≤ 40 (wt%), and examined for their phasal, microstructural, and vibrational properties using X-ray diffraction, field emission scanning electron microscopy, and Raman spectroscopy. The signature of H₂O …

Digital Twins For Flexible Manufacturing, Drew Brandon Sander

Theses and Dissertations

With the establishment of Digital Twins as an enabling technology for Industry 4.0, it is time to transition from the previous foundations to works that implement and highlight the capabilities Digital Twins present. The Industry 4.0 paradigm has recentered the focus on customizability, leading to reemerging goals of flexibility within manufacturing. Empowered through new cyber-physical systems, new enabling technologies are driving the revolution. To identify how Digital Twins as an enabling technology contribute to flexibility within manufacturing, a comprehensive investigation is conducted along with a detailed case study. A systematic literature review is conducted to analyze quality Digital Twin implementations …

Novel Redox Oxygen Active Materials For Solid Oxide Cells And Thermochemical Hydrogen Production, Jiaxin Lu

Theses and Dissertations

This dissertation investigates novel materials designed to significantly enhance the performance and durability of oxygen electrodes for solid oxide cells and redox active materials for thermochemical hydrogen production. The first part of this work evaluates Ta-doped BaCoO₃₋δ (BCT) and its structural analog SrCoO₃₋δ (SCT), focusing on their catalytic performance in oxygen reduction and evolution reactions. Among BCT compositions (x = 0.1, 0.3, 0.5), the BCT10 (x = 0.1) composition exhibited the highest oxygen vacancy concentration, electronic conductivity, and lowest polarization resistance. However, SCT10 surpassed BCT10 in these critical performance parameters and also demonstrated greater stability over extended operational periods. Notably, …

Evaluation Of Impact Energy In Composites Using Acoustic Emission Sensing Technique, Li Ai, Tanner Mesaric, Sydney Flowers, Sydney Houck, Joshua Widawsky, Paul Ziehl

Faculty Publications

A major challenge faced by composite materials is impact, which can result in unexpected damage and degradation. Impact events can cause significant structural damage that may not be immediately visible, leading to a reduction in the material’s mechanical properties and overall performance. This paper presents an impact assessment method using acoustic emission (AE) sensing technology. The primary goal of this approach is to determine the extent of impact damage on composite components by analyzing AE signals produced under operating stress conditions. An advanced algorithm is proposed to predict the probability that the damage falls into various damage categories, providing a …

Introducing The Second-Order Features Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations—Ii: Illustrative Application To Heat And Energy Transfer In The Nordheim–Fuchs Phenomenological Model For Reactor Safety, Dan Gabriel Cacuci

Faculty Publications

This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently the exact expressions of the first- and second-order sensitivities of NODE decoder responses to the neural net’s underlying parameters (weights and initial conditions). The application of the 2nd-FASAM-NODE methodology will be illustrated using the Nordheim–Fuchs phenomenological model for reactor safety, which describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted. The representative model responses that will …

Introducing The Second-Order Features Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations—I: Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work introduces the mathematical framework of the novel “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (1st-FASAM-NODE). The 1st-FASAM-NODE methodology produces and computes most efficiently the exact expressions of all of the first-order sensitivities of NODE-decoder responses with respect to the parameters underlying the NODE’s decoder, hidden layers, and encoder, after having optimized the NODE-net to represent the physical system under consideration. Building on the 1st-FASAM-NODE, this work subsequently introduces the mathematical framework of the novel “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)”. The 2nd-FASAM-NODE methodology efficiently computes the exact expressions …

Impact Of Vaporization On Drop Aerobreakup, B. Boyd, S. Becker, Yue Stanley Ling

Faculty Publications

Aerodynamic breakup of vaporizing drops is commonly seen in many spray applications. While it is well known that vaporization can modulate interfacial instabilities, the impact of vaporization on drop aerobreakup is poorly understood. Detailed interface-resolved simulations were performed to systematically study the effect of vaporization, characterized by the Stefan number, on the drop breakup and acceleration for different Weber numbers and density ratios. It is observed that the resulting asymmetric vaporization rates and strengths of Stefan flow on the windward and leeward sides of the drop hinder bag development and prevent drop breakup. The critical Weber number thus generally increases …

Influence Of Redox Engineering On The Trade-Off Relationship Between Thermopower And Electrical Conductivity In Lanthanum Titanium Based Transition Metal Oxides, Mohammad El Loubani, Gene Yang, Seyed Morteza Taghavi Kouzehkanan, Tae-Sik Oh, Santosh Kiran Balijepalli, Dongkyu Lee

Faculty Publications

Discovery of new materials plays a critical role in developing advanced high-temperature thermoelectric (TE) applications. Transition metal oxides (TMOs) are one of the attractive candidates for high-temperature TE applications due to their thermal and chemical stability. However, the trade-off relationship between thermopower (S) and electrical conductivity (σ) limits the maximum attainable power factor (PF), thereby hindering improvements in TE conversion efficiency. To overcome this trade-off relationship, the emerging approach of the redox-driven metal exsolution in TMOs shows promise in improving both S and σ. However, the effect of metal exsolution with different particle sizes and …

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 …

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 …

Investigating Electrochemical Performance And Interfacial Stability Of Solid-State Lithium Metal Batteries: A Study Of Hybrid Polymer-Ceramic Electrolyte Systems, Ziba Rahmati

Theses and Dissertations

Solid-state batteries (SSBs) are emerging as a promising energy storage technology, surpassing traditional liquid electrolyte (LE) counterparts in performance and safety. A critical component in SSBs is the solid-state electrolyte (SSE), which plays a pivotal role in safety, efficiency and stability. SSEs, including sulfides, halides, oxides, and polymers, present distinct advantages and challenges compared to LEs. Among these, oxide-based SSEs are particularly attractive for their balance in ionic conductivity and chemical stability.

This study addresses key challenges related to interfacial stability and electrochemical performance in SSBs by focusing on hybrid polymer-ceramic electrolyte systems. A major challenge to such a SSB …

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 …

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 …

In Situ Assembly Enabling Adhesive-Free Bonding Of Large Area Electronic Sensors To Concrete For Structural Health Monitoring, Emmanuel Ogunniyi, Han Liu, Austin Downey, Simon Laflamme, Caroline Bennett, William Collins, Hongki Jo, Paul Ziehl

Faculty Publications

Cracks developed in concrete infrastructure are one of the primary mechanisms that degrade their structural integrity, which may result in structural failures. Previous research on soft elastomeric capacitors (SEC) has shown their viability for structural health monitoring of structural materials, including concrete, steel, and fiberglass composites. The SEC, or its derivative version with a corrugated geometry termed corrugated SEC or cSEC, is a parallel plate capacitor. Prior work demonstrated that it was possible to directly paint the electrode interfacing with the structural material onto the structure and adhere the rest of the pre-fabricated sensor onto the wet interface, thereby eliminating …

Analysis Of Shock Absorption By Spring-Assisted Crutch Tips, Noah Hirschegger, Daegan Caime, Mohamed Atta

Senior Theses

Angel Consulting was originally created to address the problem of excessive wear and tear on the joints of individuals who use crutches for long periods of time. This company has sought to alleviate these issues with a proprietary spring-assisted crutch tip, which reduces the impact of crutch use and will hopefully be able to assist people in alleviating joint damage and discomfort. The team's main purpose is to determine an optimal metric for both marketability and effectiveness and to test the prototype design to ensure the validity of assistance for people who require chronic crutch use. To do this, we …

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 …

Autonomous Real-Time Model Updating Within Digital Twin Frameworks For Thermal Systems, Braden Robert Priddy

Theses and Dissertations

As engineering systems increase in scale and complexity in the era of the Fourth Industrial Revolution, data-driven solutions will become essential in enabling the next generation of these systems. One of the trending tools that can aid in this transition is digital twins. As physical systems degrade throughout their life cycles, their behavior also changes. Digital twins use data assimilation to continuously update virtual models to represent the current state of their physical counterparts. A reliable digital twin can be leveraged by a system operator to perform diagnostics, optimize, and tests without ever needing the physical system. However, implementing effective …

Advancement Of The Zinc Ion Battery: Polymer Electrolyte And Electrode Development For Aqueous Zinc-Ion Batteries, Roya Rajabi

Theses and Dissertations

Rechargeable aqueous zinc-ion batteries (ZIBs) have garnered significant attention in recent years as a promising candidate for stationary large-scale energy storage due to their distinct safety features and cost-effectiveness compared to conventional lithium-ion batteries. Despite their great potential, ZIBs are currently facing critical challenges for commercialization, including poor cycle stability at low discharge rates, lower energy density (Wh/kg) and higher self-discharge rate. These issues must be addressed for them to become a viable energy storage solution. The above challenges are fundamentally rooted in the bulk properties of electrolytes and interactions with electrodes, such as; 1) formation of insulating layered double …

Augmented Reality (Ar) And Virtual Reality (Vr)-Based Data Visualization Frameworks For The Manufacturing Industry, Nitol Saha

Theses and Dissertations

Industry 4.0 is transforming the manufacturing industry by integrating digital technologies throughout the production lifecycle, leading to the development of smart factories. The integration of Augmented Reality (AR) and Virtual Reality (VR) alongside smart manufacturing is transforming traditional industry practices by establishing a robust cyber-physical infrastructure, enhanced data visualization, and improved task execution. This thesis aims to develop AR and VR-based data visualization frameworks for the manufacturing industry, focusing on detailed implementation strategies, initial results, and key findings of these frameworks. One major focus of these frameworks is the generalization of the technological assets so that these frameworks can be …

Augmented Reality Based Maintenance Operations And Training, Victor Scott Gadow

Theses and Dissertations

Augmented Reality (AR) is the process of superimposing virtual information on top of objects or other structures in the real-world environment. It is considered one of many paradigms included in the idea of smart manufacturing and can enable a mixture of the other technologies involved. A large increase in research on AR has been seen in the past decade as technologies have begun to evolve to become more robust and reliable. It has been implemented into several key areas of manufacturing such as maintenance, assembly, training, and quality control. The rise of industry 4.0 is changing how data is used …

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 …

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 …

A Process Planning Software For Modeling Parameter Behavior In Automated Fiber Placement, Benjamin Jeffrey Francis

Theses and Dissertations

The manufacturing of large-scale, geometrically complex composite structures is often accomplished today using the Automated Fiber Placement (AFP) process. AFP utilizes a fiber placement end effector and a gantry or robotic kinematic system to lay up groups of composite tows, iteratively building the complete structure. The reduced width of each tow allows the deployment of AFP for builds with significant curvature, unlike other automated methods such as automated tape laying. Despite its proven track record and widespread use, the current AFP process contains inefficiencies and suffers from workflow bottlenecks that significantly increase cycle time, material wastage, and overall cost. A …

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, …