Engineering Commons^™

Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Renjith Prasad, Ruwan Wickramarachchi, Amit Sheth

Publications

Rare event prediction is critical in industrial applications, including real-world Industry 4.0 applications. These events, defined by their low occurrence frequency, are often difficult to predict due to the skewed data distribution, which complicates modeling and evaluation. In our research, we provide a comprehensive review of current approaches to rare event prediction across four key dimensions: rare event data, data processing techniques, algorithmic approaches, and evaluation methodologies [1]. By analyzing diverse datasets with multiple modalities, including numerical, image, text, and audio, we categorize the primary challenges and present the gaps in current research. Specifically, we present three novel research contributions …

Predicting Chaotic Systems With Quantum Echo-State Networks, Erik Connerty, Ethan N. Evans, Gerasimos Angelatos, Vignesh Narayanan

Publications

Recent advancements in artificial neural networks have enabled impressive tasks on classical computers, but they demand significant computational resources. While quantum computing offers potential beyond classical systems, the advantages of quantum neural networks (QNNs) remain largely unexplored. In this work, we present and examine a quantum circuit (QC) that implements and aims to improve upon the classical echo-state network (ESN), a type of reservoir-based recurrent neural networks (RNNs), using quantum computers. Typically, ESNs consist of an extremely large reservoir that learns high-dimensional embeddings, enabling prediction of complex system trajectories. Quantum echo-state networks (QESNs) aim to reduce this need for prohibitively …

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 …

A Benchmark Knowledge Graph Of Driving Scenes For Knowledge Completion Tasks, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

Knowledge graph completion (KGC) is a problem of significant importance due to the inherent incompleteness in knowledge graphs (KGs). The current approaches for KGC using link prediction (LP) mostly rely on a common set of benchmark datasets that are quite different from real-world industrial KGs. Therefore, the adaptability of current LP methods for real-world KGs and domain-specific ap- plications is questionable. To support the evaluation of current and future LP and KGC methods for industrial KGs, we introduce DSceneKG, a suite of real-world driving scene knowledge graphs that are currently being used across various industrial applications. The DSceneKG is publicly …

Single-Molecule Profiling Of Per- And Polyfluoroalkyl Substances By Cyclodextrin Mediated Host-Guest Interactions Within A Biological Nanopore, Xiaojun Wei, Aditya Choudhary, Leon Y. Wang, Lixing Yang, Mark J. Uline, Mario Tagliazucchi, Qian Wang, Dmitry Bedrov, Chang Liu

Faculty Publications

Biological nanopores are increasingly used in molecular sensing due to their single-molecule sensitivity. The detection of per- and polyfluoroalkyl substances (PFAS) like perfluorooctanoic acid and perfluorooctane sulfonic acid is critical due to their environmental prevalence and toxicity. Here, we investigate selective interactions between PFAS and four cyclodextrin (CD) variants (α-, β-, γ-, and 2-hydroxypropyl-γ-CD) within an α-hemolysin nanopore. We demonstrate that PFAS molecules can be electrochemically sensed by interacting with a γ-CD in a nanopore. Using HP-γ-CDs with increased steric resistance, we can identify homologs of the perfluoroalkyl carboxylic acid and the perfluoroalkyl sulfonic acid families and detect common PFAS …

Ontology Design Metapattern For Relationtype Role Composition, Utkarshani Jaimini, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

RelationType is a metapattern that specifies a property in a knowledge graph that directly links the head of a triple with the type of the tail. This metapattern is useful for knowledge graph link prediction tasks, specifically when one wants to predict the type of a linked entity rather than the entity instance itself. The RelationType metapattern serves as a template for future extensions of an ontology with more fine-grained domain information.

Visual Causal Question And Answering With Knowledge Graph Link Prediction, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

The ability to answer causal questions is important for any system that requires robust scene under- standing. In this demonstration, we develop a prototype system that leverages our causal link prediction framework, CausalLP. CausalLP framework uses a visual causal knowledge graph and associated knowledge graph embedding for two visual causal question and answering tasks- (i) causal explanation and (ii) causal prediction. In the live demonstration sessions, the participants will be invited to test the efficiency and effectiveness of the system for visual causal question and answering.

Causal Neuro-Symbolic Ai For Root Cause Analysis In Smart Manufacturing, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

Root cause analysis is the process of investigating the cause of a failure and providing measures to prevent future failures. It is an active area of research due to the complexities in manufacturing production lines and the vast amount of data that requires manual inspection. We present a combined approach of causal neuro-symbolic AI for root cause analysis to identify failures in smart manufacturing production lines. We have used data from an industry-grade rocket assembly line and a simulation package to demonstrate the effectiveness and relevance of our approach.

Causal Knowledge Graph For Scene Understanding In Autonomous Driving, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

The current approaches to autonomous driving focus on learning from observation or simulated data. These approaches are based on correlations rather than causation. For safety-critical applications, like autonomous driving, it’s important to represent causal dependencies among variables in addition to the domain knowledge expressed in a knowledge graph. This will allow for a better understanding of causation during scenarios that have not been observed, such as malfunctions or accidents. The causal knowledge graph, coupled with domain knowledge, demonstrates how autonomous driving scenes can be represented, learned, and explained using counterfactual and intervention reasoning to infer and understand the behavior of …

Modeling Reversible Volume Change In Automotive Battery Cells With Porous Silicon Oxide-Graphite Composite Anodes, Taylor R. Garrick, Brian J. Koch, Miguel A. Fernandez, Erin Efimoff, Hunter Teel, Matthew D. Jones, Mingjie Tu, Sirivatch Shimpalee

Faculty Publications

Automotive battery manufacturers are working to improve the individual cell and overall pack design by increasing durability, performance, and range, while reducing cost, and active material volume change is a key aspect that needs to be considered during this design process. Recently, silicon oxide-graphite composite anodes are being explored to increase total anode capacity while maintaining a tolerable amount of cell level reversible volume expansion due to the relatively lower reversible volume change of the silicon oxide compared to pure battery grade or metallurgical grade silicon. To predict the blended anode response and contribution to the overall cell volume change, …

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 …

Feasibility Study Of Perovskite Solid Electrolyte For Electrochemical Lithium-Ion Cells, Danyi Sun

Theses and Dissertations

To achieve a high energy density in lithium-ion batteries (LIB), replacing the graphite anode with lithium metal is essential, as it offers a theoretical capacity of 3840 mAh/g.(Q. Wang et al. 2021) However, the use of lithium metal anodes is restricted by the formation of lithium dendrites, which can cause short circuits.(Wood et al. 2016) Solid-state electrolytes present a viable alternative to conventional liquid electrolytes by potentially mitigating dendrite growth. Among these, the perovskite-type Li3/8Sr7/16Ta3/4Zr1/4O3 (LSTH) stands out due to its excellent ambient stability, although its synthesis, properties, and applications remain underexplored.(Y. Li et al. 2018) In this study, I …

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 …

Vascular Calcification In A Mouse Model Of Chronic Kidney Disease And In Human Peripheral Arterial Disease, Breanna Pederson

Theses and Dissertations

Vascular calcification is a process in which calcium and phosphate crystallize to form hydroxyapatite in the extracellular matrix of blood vessels. There are two forms of arterial calcification: intimal and medial, which occur via different etiologies. Intimal calcification is associated with atherosclerosis and occurs in the layer of endothelial cells adjacent to the artery lumen. Medial arterial calcification (MAC) is independent of atherosclerosis and occurs in the middle, muscular layer of the artery. MAC is strongly associated with aging, diabetes mellitus, and chronic kidney disease (CKD). MAC is frequently in patients with peripheral arterial disease (PAD). Most studies to date …

Effect Of Storage Time And Temperature On Aggregation Of Alzheimer's Disease Amyloid-Β Protein, Amy Veihdeffer

Theses and Dissertations

Amyloid-β protein (Aβ) is widely studied due to its key role in Alzheimer’s disease (AD) pathology. One characteristic of patients suffering from AD is the deposition of amyloid plaques comprised of Aβ aggregates, which are associated with synapse damage. Thus, studying Aβ aggregation and aggregation inhibition may provide pathological and therapeutic insights. Aggregation of Aβ is a nucleation dependent process that may be influenced by the presence of pre-formed Aβ aggregate seeds that can facilitate formation of protein aggregates. These seeds may appear during preparation or storage of monomer, posing impact on experiments that study the aggregation process and the …

Evaluation Of Settlement In Poorly Graded Sand With Gravel Under Strain-Controlled Cyclic Triaxial And Dynamic Centrifuge Model Testing Conditions, Elise Jones

Theses and Dissertations

This research evaluates the dynamic behavior and volume change of sand with gravel subjected to cyclic loading. Historically, research on the dynamic behavior of cohesionless soils has primarily focused on the study of liquefaction due to its known implications on soil shear strength loss. Gravelly soil is generally assumed to be less susceptible to liquefaction since its large particle size facilitates drainage during cyclic loading. Gravel’s particle size also makes it difficult to test using standard cyclic shearing laboratory equipment. Thus, there is a lack of widespread research and predictive methods for the dynamic behavior of gravelly soil. Determining the …

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 …

Devices And Dining: A Cross-Cultural Analysis Of Mobile Device Use In Italian And American Restaurants, O'Malley Jenkins

Senior Theses

The field of technology ethics has seen increasing growth and interest over the years. Many have begun to consider the impacts of technology’s use and whether it is being employed in a healthy manner by users. However, there has been limited investigation into whether the ways in which technology use varies across cultures. This study begins to address this gap by researching Italian and American device usage in fast food settings. Non-participant naturalistic observations were used to record data for 89 Italian and 88 American customers of fast food restaurants. Analysis of the collected data indicates that Americans use their …

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 …

Sex Differences In Active Avoidance And Neural Circuit Mechanisms In Contextual Fear Generalization, Carly Vincent

Theses and Dissertations

The current studies were aimed to investigate two behavioral hallmarks of anxiety and stress-related disorders, avoidance responses and the over-generalization of fear. In the first set of studies, active avoidance and extinction learning, that parallels exposure therapy in preclinical rodent models, were used. It is known that stress can influence aversive learning and extinction training, which can result in poor extinction retention. However, it is not well understood how the stress response is facilitating extinction resistance in active avoidance learning across sexes. Therefore, the first set of studies aimed to investigate the role of biological sex and glucocorticoid receptor (GR) …

Design And Application Of Redox-Mediated Flow Electrode Electrodialysis For Ion Removal And Recovery, Rongxuan Xie

Theses and Dissertations

To meet the growing demand for freshwater driven by population growth and rising living standards, the first desalination plants were established in the late 1950s. As energy costs have risen over time, research has increasingly focused on reducing the overall cost of water treatment. Electrodialysis (ED), which facilitates the migration of anions and cations across ion exchange membranes under the influence of an electric field, has gained significant attention as a treatment method for saline water and brine due to its simplicity, low cost, and scalability. However, its traditional batch operation mode and the potential for generating flammable gases have …

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 …