Engineering Commons^™

Sound Innovations For Biofabrication And Tissue Engineering, Mengxi Wu, Zhiteng Ma, Zhenhua Tian, Joseph Rich, Xin He, Jianping Xia, Ye He, Kaichun Yang, Shujie Yang, Kam W. Leong, Luke P. Lee, Tony Jun Huang

Faculty Publications

Advanced biofabrication techniques can create tissue-like constructs that can be applied for reconstructive surgery or as in vitro three-dimensional (3D) models for disease modeling and drug screening. While various biofabrication techniques have recently been widely reviewed in the literature, acoustics-based technologies still need to be explored. The rapidly increasing number of publications in the past two decades exploring the application of acoustic technologies highlights the tremendous potential of these technologies. In this review, we contend that acoustics-based methods can address many limitations inherent in other biofabrication techniques due to their unique advantages: noncontact manipulation, biocompatibility, deep tissue penetrability, versatility, precision …

Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl

Faculty Publications

Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.

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 …

Ignis: A One-Dimensional Laminar Flame Code, Jansen P. Berryhill, Jacob K. Spinti, David O. Lignell

Faculty Publications

Laminar flame codes have an important role in combustion modeling. They can provide a fundamental understanding of flame dynamics and provide a basis for building subgrid scale models in turbulent flow simulations. This paper presents Ignis, an open-source laminar flame code with the capability to offload submodels, like soot formation and radiation, using external packages and libraries. Ignis is written in C++, is documented with Doxygen, and is available on GitHub. It contains three different flame formulations: diffusion flames, premixed flames, and laminar flamelets solved in the mixture fraction coordinate. An option to facilitate creation of a diffusion flame table …

Global Empirical Model Of Sporadic-E Occurrence Rates, Eli V. Parsch, Anthony L. Franz, Eugene V. Dao, Dong L. Wu, Nimalan Swarnalingam, Cornelius C. J. H. Salinas, Daniel J. Emmons

Faculty Publications

Intense ionization enhancements in the Earth’s ionosphere, known as sporadic-E (E_s), can degrade and severely disrupt the propagation of radio signals. Although many previous studies have analyzed the characteristics and morphologies of sporadic-E, few efforts have attempted to model global E_s occurrence rates (ORs) at high time resolutions. This study develops a global empirical model of blanketing sporadic-E occurrence rates using a Karhunen–Loéve Expansion (KLE) of a global OR climatology built with Global Navigation Satellite System radio occultation (GNSS-RO) and ionosonde observations. Using an fbE ≥ threshold of 3 MHz, the model outputs a blanketing sporadic-E …

The Impact Of Film Cooling On The Heat Release Within A Rotating Detonation Combustor, Shreyas Ramanagar Sridhara, Antonio Andreini, Marc D. Polanka, Myles D. Bohon

Faculty Publications

Rotating detonation combustors establish a detonation wave that continuously circulates inside a small annulus. The presence of the detonation wave and the downstream oblique shock within the small annulus coupled with high mass flow induces a high heat load to the combustor wall. Preliminary analysis shows that for higher thermal power, internal air cooling alone is not sufficient to remove the heat out of the walls to maintain them below the maximum temperature of the metal. A possible solution is to use film cooling to reduce the heat flux to the combustor walls. One issue, though, is that the introduction …

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, …

Joint Subarray Acoustic Tweezers Enable Controllable Cell Translation, Rotation, And Deformation, Liang Shen, Zhenhua Tian, Kaichun Yang, Joseph Rich, Jianping Xia, Neil Upreti, Jinxin Zhang, Chuyi Chen, Nanjing Hao, Zhichao Pei, Tony Jun Huang

Faculty Publications

Contactless microscale tweezers are highly effective tools for manipulating, patterning, and assembling bioparticles. However, current tweezers are limited in their ability to comprehensively manipulate bioparticles, providing only partial control over the six fundamental motions (three translational and three rotational motions). This study presents a joint subarray acoustic tweezers platform that leverages acoustic radiation force and viscous torque to control the six fundamental motions of single bioparticles. This breakthrough is significant as our manipulation mechanism allows for controlling the three translational and three rotational motions of single cells, as well as enabling complex manipulation that combines controlled translational and rotational motions. …

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 …

Data-Driven Sparse Sensor Placement Optimization On Wings For Flight-By-Feel: Bioinspired Approach And Application, Alex C. Hollenbeck, Atticus J. Beachy, Ramana V. Grandhi, Alexander M. Pankonien

Faculty Publications

Flight-by-feel (FBF) is an approach to flight control that uses dispersed sensors on the wings of aircraft to detect flight state. While biological FBF systems, such as the wings of insects, often contain hundreds of strain and flow sensors, artificial systems are highly constrained by size, weight, and power (SWaP) considerations, especially for small aircraft. An optimization approach is needed to determine how many sensors are required and where they should be placed on the wing. Airflow fields can be highly nonlinear, and many local minima exist for sensor placement, meaning conventional optimization techniques are unreliable for this application. The …

Hydrogen Underground Storage For Grid Electricity Storage: An Optimization Study On Techno-Economic Analysis, Yunzhi Chen, Daniel Hill, Blake Billings, John Hedengren, Kody Powell

Faculty Publications

This study performs a techno-economic analysis of hydrogen underground storage systems for grid electricity storage, evaluating their economic viability at the plant scale using dynamic optimization. It explores the feasibility of various system configurations and revenue models in the context of volatile electricity prices and the necessity for multiple revenue streams. The hypothesis tested is that large-scale hydrogen storage, despite its low round-trip efficiency, can be economically viable with the right mix of revenue streams. This study uses scenario-based analysis to assess the impacts of different system configurations, including engaging in time-shifting arbitrage, ancillary service markets and blending hydrogen with …

Production Box Cost Estimating Relationships For Dod Avionics, Carla J. Cisneros, Edward D. White, Brandon M. Lucas, Jonathan D. Ritschel, Robert D. Fass, Shawn M. Valentine

Faculty Publications

The authors use historical information obtained from the Cost Assessment Data Enterprise to estimate recurring production unit cost for DoD avionics via cost estimating relationships (CERs). The specific modeled responses include mean unit cost, median unit cost, and the 100th production unit cost (T100) utilizing learning curve theory. For T100, the authors adopt both a multiplicative and an additive error for CER comparison. Recommended CERs consist of the mean unit cost and the T100 utilizing a multiplicative error. Moreover, results reveal that weight has a significant effect on cost as well as a potential underaccounting of real price change or …

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 …

Real-Time Synthesis Of A Nonuniformly Correlated, Partially Coherent Beam Using An Optical Coordinate Tansformation, Milo W. Hyde Iv

Faculty Publications

We design, build, and validate an optical system for generating light beams with complex spatial coherence properties in real time. Beams of this type self-focus and are resistant to turbulence degradation, making them potentially useful in applications such as optical communications. We begin with a general theoretical analysis of our proposed design. Our approach starts by generating a Schell-model (uniformly correlated or shift-invariant) source by spatially filtering incoherent light. We then pass this light through an optical coordinate transformer, which converts the Schell-model source into a nonuniformly correlated field. After the general analysis, we discuss system engineering, including trade-offs among …

Flexible Operation Of Nuclear Hybrid Energy Systems For Load Following And Water Desalination, An Ho, Blake W. Billings, John Hedengren, Kody M. Powell

Faculty Publications

Nuclear hybrid energy systems (NHES) have the potential to provide dependable and emission-free electricity to the grid while also increasing the flexibility and reliability of the electrical grid. Molten salt reactor (MSR) technology can provide consistent, carbon-free electricity while also increasing efficiency, security, and sustainability and reducing nuclear waste. This study investigates the integration of Molten Salt Reactors (MSR) and conventional Pressurized Water Reactors (PWR) with desalination technologies: Direct Contact Membrane Distillation (DCMD), Multi-Stage Flash Distillation (MSFD), and Reverse Osmosis (RO). Dynamic first-principles models were developed and tested using real grid data from the New York Independent System Operator. The …

High-Fidelity Machine Learning Techniques For Driver Drowsiness Detection, Yasser Ismail, Ebenezer Essel, Abeer Abdelhamid, Mahmoud Darwich, Fahmi Khalifa, Fred Lacy

Faculty Publications

It is devastating that daily, there is an ample number of car crashes that cause damage to automobiles, onboard passengers get injured, and others tend to lose their lives. Road crashes are fast rising across the globe and have drawn many road safety commissions and concerned individuals to discuss ways to reduce this menacing situation drastically. With the introduction of artificial intelligence and technological advancement, the government and state commissions have beckoned on the various universities and research institutions to develop methods to curb the rise of automobile crashes. Some causes of these crashes include drunk driving and drowsiness, the …

Finite Element Modeling And Analysis Of Rc Shear Walls With Cutting-Out Openings, Islam M. Saad, Mohamed Emara, Ayman El-Zohairy, Sherif El-Beshlawy

Faculty Publications

In recent decades, reinforced concrete (RC) shear walls have been one of the best structural solutions to resist lateral load in high-rise buildings. Shear wall openings are essential for preparations and architectural requirements, which weaken the wall, reducing bearing capacity, energy absorption, and stiffness while also causing stress concentrations. This paper presents a comprehensive finite element (FE) investigation of the behavior and performance of RC shear walls with openings and subjected to lateral loads. The study aims to evaluate the influence of various parameters, such as opening location, size, wall aspect ratio, axial load, and concrete strength, which affect the …

The Evaluation Of Machine Learning Techniques For Isotope Identification Contextualized By Training And Testing Spectral Similarity, Aaron P. Fjelsted, Tyler J. Morrow, Clayton D. Scott, Yilun Zhu, Darren E. Holland, Azaree T. Lintereur, Douglas E. Wolfe

Faculty Publications

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset …

Electrochemical Investigation Of Moisture Byproducts In Molten Calcium Chloride, Rankin Shum, Marah Gragun, Tyler Williams, Devin Rappleye

Faculty Publications

Residual water in molten CaCl₂ reacts to form different byproducts, such as HCl, which can impact the corrosivity of the salt and efficiency of electrochemical operations, such as electrolytic oxide reduction and electrorefining. The ability to detect and quantify these byproducts electrochemically can provide feedback on the efficacy of vacuum drying and other purification methods, as well as the impact of these byproducts on process operations. An electrochemical signal’s association with the production of H₂ is verified and characterized using cyclic voltammetry (CV) and residual gas analysis. CV estimated a 2-electron exchange process associated with H2 production. CV …

Neuro-Symbolic Ai For Deep Analysis Of Social Media Big Data, Vedant Khandelwal, Manas Gaur, Ugur Kursuncu, Valerie Shalin, Amit P. Sheth

Faculty Publications

This tutorial introduces a neuro-symbolic AI framework to analyze big data from social media platforms. Integrating human-curated knowledge through symbolic AI with the pattern recognition capabilities of neural networks enhances the adaptability and efficiency of traditional neural network approaches. Knowledge-guided zero-shot learning techniques enable swift adaption to new linguistic contexts and emerging events [6]. Participants will explore how to design, develop, and utilize these models in specific domains, such as public health surveillance, that require dynamic adaptation to new terminologies. This session The tutorial aims to equip attendees with practical skills and a deep understanding of how to apply neuro-symbolic …

Model Predictive Control Of A Grid-Scale Thermal Energy Storage System In Relap5-3d, Jaron Wallace, John Hedengren, Kody Powell, Matthew Memmott

Faculty Publications

This research delves into the integration and control of a Thermal Energy Storage (TES) system with a Small Modular Reactor (SMR), specifically the NuScale VOYGR SMR module in RELAP5-3D. The research methodology centered on modeling the NuScale VOYGR SMR, a light water pressurized water reactor (LWR) with a power output capacity of 77 MWe per module. The reactor and plant details were sourced from NuScale's final safety analysis report and supplemented by information from the NuScale website. The SMR plays a crucial role in energy generation, and to manage and dispatch the produced energy effectively, a robust storage system …

A Panel Data Regression Model For Defense Merger And Acquisition Activity, Corey D. Mack, Clay Koschnick, Michael Brown, Jonathan D. Ritschel, Brandon M. Lucas

Faculty Publications

Excerpt: This paper examines the relationship between a prime contractor's financial health and its mergers and acquisitions (M&A) spending in the defense industry. It aims to provide models that give the United States Department of Defense (DoD) indications of future M&A activity, informing decision-makers and contributing to ensuring competitive markets that benefit the consumer.

The results show a significant relationship between efficiency and M&A spending, indicating that companies with lower efficiency tend to spend more on M&As. However, there was no significant relationship between M&A spending and a company's profitability or solvency. These results were consistent with previous research and …

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, …

Addressing Strain And Porosity Changes Of Battery Electrodes Due To Reversible Expansion Through Dem Simulations, Hunter Teel, Taylor R. Garrick, Srikant Srinivasan, Fengkun Wang, Yangbing Zeng, Sirivatch Shimpalee

Faculty Publications

In this work, discrete element method (DEM) simulations were used to probe changes in electrode porosity, electrode strain, and the resultant pressure changes for composite electrodes comprised of active material and binder particles. Through the results acquired by these simulations, three cases that are representative of two limiting cases for electrode operation, and one case for realistic electrode face pressure during operation were captured and the implications on design and performance are discussed. Predicting changes in the porosity is a unique insight that is difficult if not impossible to capture experimentally but is important for predicting changes in electrochemical performance …

Quantifying The Impact Of Microstructure Variation On Charging Capability In Lithium-Ion Batteries, Hunter Teel, Taylor R. Garrick, Mitchell A. Sepe, Joseph S. Lopata, Srikant Srinivasan, Fengkun Wang, Yangbing Zeng, Sirivatch Shimpalee

Faculty Publications

Through the use of electrochemical simulations, variation in the local onset of lithium plating can be predicted and used to set charging guidelines to reduce the risk of lithium plating. The pseudo-two-dimensional (P2D) model is typically used for capturing this behavior; however, it only provides a global lithium plating onset estimate and does not consider the local variation. With material properties translated to an average continuum value, the P2D model can simulate rapid charge and capture global onset of lithium plating. However, this model lacks the ability to resolve localized behaviors across individual components due to local non-uniformities. Our three-dimensional …

Performance Of Gfrp-Confined Rubberized Engineered Cementitious Composite Columns, Mahmoud T. Nawar, Mohamed Selim, Mahmoud Zaglal, Ayman El-Zohairy

Faculty Publications

In coastal regions, the deterioration of structures and bridges due to environmental conditions and corrosion is a significant concern. To combat these issues, the use of corrosion-resistant materials like fiber-reinforced polymers (FRPs) materials, engineered cementitious composites (ECCs), and rubberized ECCs (RECC) shows promise as normal concrete (NC) alternatives by providing increased ductility and energy absorption properties. The effectiveness of confining concrete columns using GFRP tubes with ECC/RECC was assessed in this research by evaluating their performance through compression and push-out tests. The study explored key parameters such as GFRP tube thickness and the presence of shear connectors along the tube …

Experimental And Fe Investigations Of Backfill Cover On Large-Diameter Grp Pipes, Abdulmuttalib I. Said, Yahya Jabbar Hussein, Mohammed Hazim Mohammed, Abbas A. Allawi

Faculty Publications

This paper presents experimental investigations on buried Glass Reinforced Plastic (GRP) pipes with a diameter of 1400 mm. The tested pipes were buried in dense, gravelly sand and subjected to traffic loads to study the effects of backfill cover on pipe deflection. The experimental program included tests on three GRP pipes with backfill covers of 100 cm, 75 cm, and 50 cm. The maximum traffic loads applied to the pipe–soil system corresponded to Iraqi Truck Type 3 (AASHTO Htype). Vertical deflections of the pipes were monitored during the application of these loads. The experimental results showed that, as the backfill …

Acousto-Dielectric Tweezers Enable Independent Manipulation Of Multiple Particles, Liang Shen, Zhenhua Tian, Kaichun Yang, Joseph Rich, Jinxin Zhang, Jianping Xia, Wesley Collyer, Brandon Lu, Nanjing Hao, Zhichao Pei, Chuyi Chen, Tony Jun Huang

Faculty Publications

Acoustic tweezers have gained substantial interest in biology, engineering, and materials science for their label-free, precise, contactless, and programmable manipulation of small objects. However, acoustic tweezers cannot independently manipulate multiple microparticles simultaneously. This study introduces acousto-dielectric tweezers capable of independently manipulating multiple microparticles and precise control over intercellular distances and cyclical cell pairing and separation for detailed cell-cell interaction analysis. Our acousto-dielectric tweezers leverage the competition between acoustic radiation forces, generated by standing surface acoustic waves (SAWs), and dielectrophoretic (DEP) forces, induced by gradient electric fields. Modulating these fields allows for the precise positioning of individual microparticles at points where …

Enhancing Crossflow Dynamics Through The Gas Injection From Multiple Cylinders, Sahrish B. Naqvi, Sadia Siddiqa, Maciej Matyka, Rama S. R. Gorla, Md. Mamum Molla

Faculty Publications

We investigate unsteady, two-dimensional laminar fluid flow around cylinders, focusing on understanding the impact of injecting methane gas through two diametrically opposite arcs on the cylinder in the crossflow of the second fluid. This study encompasses applications in mixing and dispersion, which are crucial in various technological and natural processes. Our analysis addresses velocity field’s contribution to the spatiotemporal distribution of transported quantities. We observed that mixing induces a transition from laminar to turbulent flow. Depending on the injected-to-crossflow velocity ratios, the wake vortices downstream of cylinder arrays separate from or connect to the injected gas. This phenomenon significantly impacts …