Mechanical Engineering Commons^™

Metaversekg: Knowledge Graph For Engineering And Design Application In Industrial Metaverse, Utkarshani Jaimini, Tongtao Zhang, Georgia Olympia Brikis

Publications

While the term Metaverse was first coined by the author Neal Stephenson in 1992 in his science fiction novel “Snow Crash”, today the vision of an integrated virtual world is becoming a reality across different sectors. Applications in gaming and consumer products are gaining traction, industrial metaverse applications are, still in their early stages of development with one of the challenges being interoperability across various metaverse development platforms and existing software tools. In this work we propose the use of a knowledge graph based semantic data exchange layer, the Metaverse Knowledge Graph, to enable seamless transfer of information across platforms. …

Impacts Of Preferential Vaporization Of Multi-Component Liquid Fuels On Near-Limit Combustion Behaviors, Seungjae Lim

Theses and Dissertations

Combustion technologies used in energy conversion devices involve multi-phase and multi-component combustion behaviors associated with chemical kinetic characteristics coupled with spray dynamics. For reliable engine operation, the engine operation envelope is necessarily required to be determined by near-limit combustion behaviors such as flame flashback, lean blowout, ignition, and extinction, which are influenced by both fuel chemical and physical properties. Liquid fuels are composed of a wide range of molecular structures and weights, therefore exhibiting relatively large distillation temperature range. When fuel chemical properties change during fuel vaporization, preferential vaporization effects could play a considerable role in near-limit combustion behaviors. In …

Towards Modeling Of Induction Welding Of Thermoplastic Laminates With A Mixed Finite Element Boundary Element Approach, Florentius Johannes Van Zanten

Theses and Dissertations

There is an increased interest in induction welding of carbon fiber reinforced thermoplastic composite laminates within the aerospace industry. Currently, optimal manufacturing process parameters (e.g., current, power, and frequency settings, coil movement speed, etc.) are determined through an experimental trial-and-error approach. To reduce the need for an experimental approach that can determine the manufacturing process parameters, which would be expensive in both time and money, accurate and computationally efficient numerical tools are desired. This research is focused on improving the existing numerical tool, WelDone, in regard to its speed and accuracy.

WelDone utilizes a hybrid element formulation that combines traditional …

Molten Salt Thermal Properties Database – Thermochemical Development And Thermodynamic Assessment Of Various Molten Salt Systems, Johnathon Chandler Ard

Theses and Dissertations

The Molten Salt Thermal Properties Database – Thermochemical (MSTDB-TC) is a validated open-source database for thermochemical modeling of molten salt reactor (MSR) relevant fluoride and chloride salt systems. The database has been created and populated by leveraging available models from literature as well as completing novel system assessments. The development and contents of the MSTDB-TC v1.2 initial release are detailed along with various system assessments performed in the course of the work. The database utilizes a major strength of the CALPHAD thermodynamic modeling method. This is the ability to estimate higher-order system behavior by combining modeled lower-order systems, …

Self-Sensing Smart Products In Smart Manufacturing Systems, Juergen Lenz, Eric Macdonald, Ramy Harik, Thorsten Wuest

Faculty Publications

We are surrounded by a growing number of products with embedded intelligence relying on sensors and internet access. These smart products, that already transform our lives, are also physical entities that need to be manufactured. Manufacturing today similarly relies on data and data-driven insights to improve quality, efficiency, and safety on the shopfloor. This paper discusses the vision to utilize the ability of smart products to sense and communicate already during their own manufacturing to enrich the smart manufacturing system’s data for better insights development and optimization. We furthermore, discuss the barriers and opportunities embedded in such a paradigm shift.

Experimental Investigations Of Yarn Pull-Out Behavior In Kevlar®: Influence Of Applied Metallic Coatings And Effect Of Dynamic Loading, Julie Ann Roark

Theses and Dissertations

Flexible woven Kevlar® textile fabrics are widely used in protective armor applications. Yarn pull-out, comprised of yarn uncrimping (i.e., straightening) and yarn translation, is a major energy absorption mechanism during ballistic impact onto these fabrics, especially for impact velocities below the ballistic limit. Yarn pull-out is influenced by various parameters including inter-yarn friction, pull-out distance, pull-out velocity, transverse pre-tension, fiber diameter, fabric architecture, fabric waviness, fabric count and yarn modulus.

The first part of this thesis investigates yarn pull-out behavior of commercially available Kevlar® KM2+ individual yarns coated with metallic layers (copper, aluminum, aluminum nitride, silver) via a directed vapor …

High-Throughput Computation Of Interfacial Thermal Management Of Wide-Bandgap Semiconductors, Hao-Wen Chen

Theses and Dissertations

As semiconductor electronics, in particular high electron mobility transistors, get hot in operation, people are trying to incorporate different semiconductor materials to solve the problem of heat dissipation to maintain the device efficiency and performance. In this master thesis, two different packages, LAMMPS and almaBTE, that are focusing on micro-scale and atomic scale respectively, are used to simulate the heat transfer process across interfaces in two different scales. In the LAMMPS simulation, the research is exploring how the location of atoms and the thickness of interfacial layers will influence the interfacial thermal conductance. On the other hand, using the almaBTE …

Uncrewed Aircraft Systems For Autonomous Infrastructure Inspection, Michail Kalaitzakis

Theses and Dissertations

Uncrewed Aircraft Systems (UAS) are becoming increasingly popular for infrastructure inspections since they offer increased safety, decreased costs and consistent results, compared to traditional methods. However, there are still many open challenges before fully autonomous, reliable, and repeatable UAS inspections. While a UAS platform has increased mobility and can easily approach hard to reach areas, it has limited range and payload capacity and is susceptible to environmental disturbances. Therefore, current operations are limited to Visual Line of Sight (VLOS) manual inspections that usually result in just a qualitative (visual) assessment of the structure.

The objective of this work is to …

Fabrication Of Asymmetrical Hollow Fiber-Supported Thin Film Membranes, Stack Assembly, And Accelerated Long-Term Stability Test For Oxygen Production From Air, Myongjin Lee

Theses and Dissertations

Air separation is a widely used process for oxygen production. Several separation technologies have been developed for air separation, including cryogenic distillation, swing adsorption, redox process of metal oxides, and electrochemical process. Among these technologies, electrochemical permeation process stands out as a cost-effective and simple process for pure oxygen production from air. The electrochemical permeation process employs a gas-tight membrane to permeate and separate oxygen from air directly, where the membrane conducts both ions and electrons simultaneously. Different membrane designs have been studied to obtain the improved performance for oxygen permeation, typically planar and tubular designs. Among these membrane configurations, …

Shear Localization In The Metallic Nanolayered Composites, Shujing Dong

Theses and Dissertations

In this dissertation, the influences of layer thickness (h), interface orientation relationship (OR) and dislocation slip activities on shear band (SB) formation mechanisms was investigated by means of molecular dynamics (MD) simulations.

The effect of h and dislocation slip systems on the shear localization in Cu-FCC/Nb-BCC MNCs was studied. The strain softening observed in those samples was triggered by the SB formation. The microstructure evolutions and dislocation slips revealed that the unsymmetrical dislocation transmission across the interface induces the shear localization and promotes the SB formation. The quantitative analysis of the change in the separation distance of initially …

Use Of Dic Measurements With Finite Element Models For Direct Heterogeneous Material Property Determination And Wrinkle Formation During Automated Fiber Placement, Sreehari Rajan Kattil

Theses and Dissertations

In this work, application of DIC in combination with finite element modeling is demonstrated for efficient material characterization for complex heterogeneous materials and tow wrinkle formation during automated fiber placement.

The first part of the work describes the integration of DIC measurements with finite element models for direct property identification in heterogeneous material systems. The material property identification is based on solving partial differential equations (PDE) of equilibrium for unknown elastic material properties with known boundary conditions and full field strain data (Eg. DIC). The PDEs are solved numerically using Petrov-Galerkin finite element procedure. The classical Bubnov-Galerkin method is shown …

A Novel Self-Assembled Cobalt-Free Perovskite Composite Cathode With Triple-Conduction For Intermediate Proton-Conducting Solid Oxide Fuel Cells, Hua Tong, Min Fu, Yang Yang, Fanglin Chen, Zetian Tao

Faculty Publications

A traditional composite cathode for proton-conducting solid oxide fuel cells (H-SOFCs) is typically obtained by mixing cathode materials and proton conducting electrolyte of BaCe_0.7Y_0.2Z_r0.1O_3–δ (BZCY), providing chemical and thermal compatibility with the electrolyte. Here, a series of triple-conducing and cobalt-free iron-based perovskites as cathodes for H-SOFCs is reported. Specifically, BaCe_xFe_1–xO_3–δ (x = 0.36, 0.43, and 0.50) shows various contents of two single phase perovskites with an in situ heterojunction structure as well as triple conductivity by tailoring the Ce/Fe ratios. The cell performance with the optimized BaCe_{0.36 …}

Overview Of Arbitrarily High-Order Adjoint Sensitivity And Uncertainty Quantification Methodology For Large-Scale Systems, Dan Gabriel Cacuci

Faculty Publications

This work reviews from a unified viewpoint the concepts underlying the “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems” (nth-CASAM-L) and the “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (nth-CASAM-N) methodologies. The practical application of the nth-CASAM-L methodology is illustrated for an OECD/NEA reactor physics benchmark, while the practical application of the nth-CASAM-N methodology is illustrated for a nonlinear model of reactor dynamics that exhibits periodic and chaotic oscillations. As illustrated both by the general theory and by the examples reviewed in this work, both the nth-CASAM-L and nth-CASAM-N methodologies overcome the curse of dimensionality …

Advances In High-Order Sensitivity Analysis For Uncertainty Quantification And Reduction In Nuclear Energy Systems, Dan Gabriel Cacuci

Faculty Publications

No abstract provided.

Sensitivity Analysis, Uncertainty Quantification And Predictive Modeling Of Nuclear Energy Systems, Dan Gabriel Cacuci

Faculty Publications

No abstract provided.

Strain And Strain Rate In Friction Extrusion, Xiao Li, Md Reza-E- Rabby, Anthony Guzman, Glenn Grant, Suveen Mathaudhu, Michah Hinton, Anthony P. Reynolds

Faculty Publications

Friction extrusion is a metal forming process that generates large plastic strains and deformation-induced heating through friction between a rotating die and the material to be extruded. The final deformation state in friction extruded wire has been visualized in previous studies but the distribution and evolution of strain and strain rate inside the solid material have yet to be elucidated. This paper develops an approach that reveals the deformation during the process by visualizing the shape change of the pre-embedded markers in the remnant billet. For the first time, the distribution of steady-state strain and strain rate in friction extrusion …

A Primer On The Factories Of The Future, Noble Anumbe, Clint Saidy, Ramy Harik

Faculty Publications

In a dynamic and rapidly changing world, customers’ often conflicting demands have continued to evolve, outstripping the ability of the traditional factory to address modern-day production challenges. To fix these challenges, several manufacturing paradigms have been proposed. Some of these have monikers such as the smart factory, intelligent factory, digital factory, and cloud-based factory. Due to a lack of consensus on general nomenclature, the term Factory of the Future (or Future Factory) has been used in this paper as a collective euphemism for these paradigms. The Factory of the Future constitutes a creative convergence of multiple technologies, techniques, and capabilities …

Piezoelectric Point-Of-Care Biosensor For The Detection Of Sars-Cov-2 (Covid-19) Antibodies, Debdyuti Mandal, Mustahseen M. Indaleeb, Alexandra Younan, Sourav Banerjee

Faculty Publications

It is always challenging to diagnose a disease using a biosensor reliably, and quickly with high sensitivity and selectivity, simultaneosuly. Recently the world experienced a global pandemic caused by a novel coronavirus (COVID-19). Although the vaccines are available, COVID-19 resulted a huge threat to the entire world with high mortality rates. Irrespective of a specific disease, there is a constant need for a cheaper and faster in-vitro, lab-on-a-chip sensor with high sensitivity and selectivity. Such sensors will not only facilitate the disease detection but will expedite and vaccine development process through detection of its corresponding antibodies when developed. In this …

Predicting Lattice Vibrational Frequencies Using Deep Graph Neural Networks, Nghia Nguyen, Steph-Yves V. Louis, Lai Wei, Kamal Choudhary, Ming Hu, Jianjun Hu

Faculty Publications

Lattice vibrational frequencies are related to many important materials properties such as thermal and electrical conductivity as well as superconductivity. However, computational calculation of vibrational frequencies using density functional theory methods is computationally too demanding for large number of samples in materials screening. Here we propose a deep graph neural network based algorithm for predicting crystal vibrational frequencies from crystal structures. Our algorithm addresses the variable dimension of vibrational frequency spectrum using the zero padding scheme. Benchmark studies on two data sets with 15,000 mixed-structure and 35,552 rhombohedra samples show that the aggregated R2 scores of the prediction reach …

High-Throughput Computational Evaluation Of Lattice Thermal Conductivity Using An Optimized Slack Model, Guangzhao Qin, An Huang, Yinqiao Liu, Huimin Wang, Zhenzhen Qin, Xue Jiang, Jijun Zhao, Jianjun Hu, Ming Hu

Faculty Publications

High-throughput computational screening of materials with targeted thermal conductivity (κ) plays an important role in promoting the advancement of material design and enormous applications. The Slack model has been widely applied for the fast evaluation of κ with minimal time and resources, showing the potential capability of high-throughput screening of κ. However, after examining the Slack model on a large set of 353 materials, a huge discrepancy is found between the predicted κ and the correspondingly measured κ in experiments for some materials in addition to the generally overestimated κ by the Slack model. Thus, it is …

Optimised Adjoint Sensitivity Analysis Using Adjoint Guided Mesh Adaptivity Applied To Neutron Detector Response Calculations, Andrew G. Buchan, Dan Gabriel Cacuci, Steven Dargaville, Christopher C. Pain

Faculty Publications

This article presents a new approach for the efficient calculation of sensitivities in radiation dose estimates, subject to imprecisely known nuclear material cross-section data. The method is a combined application of adjoint-based models to perform, simultaneously, both the sensitivity calculation together with optimal adaptive mesh refinement. Adjoint-based sensitivity methods are known for their efficiency since they enable sensitivities of all parameters to be formed through only two solutions to the problem. However, the efficient solutions can also be obtained by their computation on optimal meshes, here guided by goal-based adjoint approaches. It is shown that both mesh adaptivity and sensitivity …

Structural Health Monitoring Of Fatigue Cracks For Steel Bridges With Wireless Large-Area Strain Sensors, Sdiq Anwar Taher, Jian Li, Jong-Hyun Jeong, Simon Laflamme, Hongki Jo, Caroline Bennett, William N. Collins, Austin Downey

Faculty Publications

This paper presents a field implementation of the structural health monitoring (SHM) of fatigue cracks for steel bridge structures. Steel bridges experience fatigue cracks under repetitive traffic loading, which pose great threats to their structural integrity and can lead to catastrophic failures. Currently, accurate and reliable fatigue crack monitoring for the safety assessment of bridges is still a difficult task. On the other hand, wireless smart sensors have achieved great success in global SHM by enabling long-term modal identifications of civil structures. However, long-term field monitoring of localized damage such as fatigue cracks has been limited due to the lack …

Efficiently Searching Extreme Mechanical Properties Via Boundless Objective-Free Exploration And Minimal First-Principles Calculations, Joshua Ojih, Mohammed Al-Fahdi, Alejandro David Rodriguez, Kamal Choudhary, Ming Hu

Faculty Publications

Despite the machine learning (ML) methods have been largely used recently, the predicted materials properties usually cannot exceed the range of original training data. We deployed a boundless objective-free exploration approach to combine traditional ML and density functional theory (DFT) in searching extreme material properties. This combination not only improves the efficiency for screening large-scale materials with minimal DFT inquiry, but also yields properties beyond original training range. We use Stein novelty to recommend outliers and then verify using DFT. Validated data are then added into the training dataset for next round iteration. We test the loop of training-recommendation-validation in …

Hybrid Theory-Machine Learning Methods For The Prediction Of Afp Layup Quality, Christopher M. Sacco

Theses and Dissertations

The advanced manufacturing capabilities provided through the automated fiber placement (AFP) system has allowed for faster layup time and more consistent production across a number of different geometries. This contributes to the modern production of large composite structures and the widespread adaptation of composites in industry in general and aerospace in particular. However, the automation introduced in this process increases the difficulty of quality assurance efforts. Industry available tools for predicting layup quality are either limited in scope, or have extremely high computational overhead. With the advent of automated inspection systems, direct capture of semantic inspection data, and therefore complete …

Nondestructive Material Characterization Using A Fully Noncontact Ultrasonic Lamb Wave System For Thin Metals, Nuclear Cladding, And Composite Materials, Elsa Z. Compton

Theses and Dissertations

Effective non-destructive evaluation (NDE) inspection system and methods are highly desired in a broad range of engineering applications including thin metal structure thickness evaluation. Ultrasonic guided waves in thin-walled structures, namely Lamb waves, have gained popularity as a NDE method. By using the ultrasonic waves in conjunction with high spatial resolution multidimensional wavefield measurements, thickness evaluations for thin metals can be achieved. This thesis explores the configuration and application of a fully noncontact ultrasonic Lamb wave NDE system for thickness characterization and evaluation of very thin metal plates. We have tested the actuation and sensing of Lamb waves for thickness …

The NTh-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems (Nth-Casam-N): Mathematical Framework, Dan Gabriel Cacuci

Faculty Publications

This work presents the n^th-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (n^th-CASAM-N), which enables the most efficient computation of exactly determined expressions of arbitrarily high-order sensitivities of generic nonlinear system responses with respect to model parameters, uncertain boundaries, and internal interfaces in the model’s phase space. The mathematical framework underlying the n^th-CASAM-N is proven to be correct by using mathematical induction. The n^th-CASAM-N is formulated in linearly increasing higher-dimensional Hilbert spaces—as opposed to exponentially increasing parameter-dimensional spaces—thus overcoming the curse of dimensionality in sensitivity analysis of nonlinear systems.

Illustrative Application Of The Nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Nonlinear Systems To The Nordheim–Fuchs Reactor Dynamics/Safety Model, Dan Gabriel Cacuci

Faculty Publications

The application of the recently developed “nth-order comprehensive sensitivity analysis methodology for nonlinear systems” (abbreviated as “nth-CASAM-N”) has been previously illustrated on paradigm nonlinear space-dependent problems. To complement these illustrative applications, this work illustrates the application of the nth-CASAM-N to a paradigm nonlinear time-dependent model chosen from the field of reactor dynamics/safety, namely the well-known Nordheim–Fuchs model. This phenomenological model 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, either intentionally or by accident. This model is sufficiently complex to demonstrate all the …

Performance Projection Of A High-Temperature Co2 Transport Membrane Reactor For Combined Co2 Capture And Methane-To-Ethylene Conversion, Xin Li, Kevin Huang, Noah Van Dam, Xinfang Jin

Faculty Publications

Direct conversion of methane into ethylene through the oxidative coupling of methane (OCM) is a technically important reaction. However, conventional co-fed fixed-bed OCM reactors still face serious challenges in conversion and selectivity. In this paper, we apply a finite element model to simulate OCM reaction in a plug-flow CO₂ /O₂ transport membrane (CTM) reactor with a directly captured CO₂ and O₂ mixture as a soft oxidizer. The CTM is made of three phases: molten carbonate, 20% Sm-doped CeO₂ , and LiNiO₂ . The membrane parameters are first validated by CO₂ /O₂ flux …

Audio-Based Wildfire Detection On Embedded Systems, Hung-Tien Huang, Austin Downey, Jason D. Bakos

Faculty Publications

The occurrence of wildfires often results in significant fatalities. As wildfires are notorious for their high speed of spread, the ability to identify wildfire at its early stage is essential in quickly obtaining control of the fire and in reducing property loss and preventing loss of life. This work presents a machine learning wildfire detecting data pipeline that can be deployed on embedded systems in remote locations. The proposed data pipeline consists of three main steps: audio preprocessing, feature engineering, and classification. Experiments show that the proposed data pipeline is capable of detecting wildfire effectively with high precision and is …

Zintl Phase Compounds Mg3Sb2-XBiX (X=0, 1, And 2) Monolayers: Electronic, Phonon And Thermoelectric Properties From Ab Initio Calculations, Zheng Chang, Jing Ma, Kunpeng Yuan, Jiongzhi Zheng, Bin Wei, Mohammed Al-Fahdi, Yufei Gao, Xiaoliang Zhang, Hezhu Shao, Ming Hu, Dawei Tang

Faculty Publications

The Mg₃Sb_2−xBi_x family has emerged as the potential candidates for thermoelectric applications due to their ultra-low lattice thermal conductivity (K_L) at room temperature (RT) and structural complexity. Here, using ab initio calculations of the electron-phonon averaged (EPA) approximation coupled with Boltzmann transport equation (BTE), we have studied electronic, phonon and thermoelectric properties of Mg₃Sb_2−xBi_x (x = 0, 1, and 2) monolayers. In violation of common mass-trend expectations, increasing Bi element content with heavier Zintl phase compounds yields an abnormal change in K_L in two-dimensional Mg₃Sb …