Engineering Commons^™

A Non-Linear Optimization Model For Controlling The Real Area Of Contact In Surface Texture Design, Sandra Eksioglu, Min Zou

Industrial Engineering Faculty Publications and Presentations

Motivated by the potential of surface texturing to enhance the tribological performance of micro- and nano-electromechanical systems (MEMS/NEMS), this study proposes a novel non-linear optimization approach for designing textured surfaces. This model minimizes the contact area between interacting surfaces and deformation during sliding under dry conditions by controlling key design parameters, such as the size and shape of the designed surface. We test the performance of the proposed model using the lotus leaf surface with dimensions of 248 x 136 micrometers. Due to the large size of the model, we propose a solution approach which consists of a data aggregation …

Small Laser-Textured Dimples For Improved Tribological Performance Of Cocrmo In Artificial Hip Joints, William B. Bennett, Min Zou

Mechanical Engineering Faculty Publications and Presentations

This study investigates the impact of small dimples on the tribological properties of CoCrMo (CCM) surfaces. Laser-ablated textures with 5 mu m diameter dimples were fabricated at varying aspect ratios (0.1, 0.2, 0.3) and surface densities (5%, 15%, 25%) to evaluate their effects on friction and wear when paired with ultra-high molecular weight polyethylene (UHMWPE) counterfaces. The results showed that small dimples significantly reduced and stabilized the coefficient of friction (CoF) and wear compared to untextured CCM and larger dimples as reported in the literature. The texture configuration with a 5% surface density and 0.1 aspect ratio achieved the best …

Reweighting Configurations Generated By Transferable, Machine Learned Models For Protein Sidechain Backmapping, Jacob Monroe

Chemical Engineering Faculty Publications and Presentations

Multiscale modeling requires the linking of models at different levels of detail, with the goal of gaining accelerations from lower fidelity models while recovering fine details from higher resolution models. Communication across resolutions is particularly important in modeling soft matter, where tight couplings exist between molecular-level details and mesoscale structures. While multiscale modeling of biomolecules has become a critical component in exploring their structure and self-assembly, backmapping from coarse-grained to fine-grained, or atomistic, representations presents a challenge, despite recent advances through machine learning. A major hurdle, especially for strategies utilizing machine learning, is that backmappings can only approximately recover the …

Workforce Forecasting For State Transportation Agencies: A Machine Learning Approach, Adedolapo Ogungbire, Suman Kumar Mitra

Civil Engineering Faculty Publications and Presentations

A decline in the number of construction engineers and inspectors at state transportation agencies (STAs) to manage the ever-increasing lane miles has emphasized the importance of workforce planning in these agencies. Forecasting workforce requirements is crucial for effective planning in any industry or agency. This study developed machine learning (ML) models to estimate the person-hour requirements of STAs at the project level. The Arkansas Department of Transportation (ARDOT) was used as a case study, using its employee and project details data between 2012 and 2021. ML regression models ranging from linear, tree ensembles, kernel-based, and neural network-based models were …

Examining The Impact Of The Covid-19 Pandemic On Older Adults' Activity Participation And Mode Usage In A Rural State: A Case Study Of Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Alishia Juanelle Ferguson, Michelle Gray, Jennifer D. Webb

Civil Engineering Faculty Publications and Presentations

The objective of the study was to investigate the impact of the COVID-19 pandemic on the activity participation and mode usage of older adults residing in Arkansas, a predominantly rural state. Leveraging primary data collected from 832 older adult participants, the study employed Latent Class Analysis (LCA) to capture older adults' heterogeneity in travel behavior and found three distinct classes: Pandemic-affected minimal travelers, Unaffected non-commuter car users, and Unaffected commuter car users, showing different levels of their activity participation, mode usage during the pandemic and varying the pandemic's impact on their trips. To understand these variations in light of the …

Overexpression And Biophysical And Functional Characterization Of A Recombinant Fgf21, Phuc Phan, Jason Hoang, Thallapuranam Krishnaswamy Suresh Kumar

Chemistry & Biochemistry Faculty Publications and Presentations

Fibroblast growth factor 21 (FGF21) is an endocrine FGF that plays a vital role in regulating essential metabolic pathways. FGF21 increases glucose uptake by cells, promotes fatty acid oxidation, reduces blood glucose levels, and alleviates metabolic diseases. However, detailed studies on its stability and biophysical characteristics have not been reported. Herein, we present the overexpression, biophysical characterization, and metabolic activity of a soluble recombinant FGF21 (rFGF21). The far-UV circular dichroism spectra of rFGF21 show a negative trough at 215 nm, indicating that the protein’s backbone predominantly adopts a β sheet conformation. rFGF21 shows intrinsic tyrosine fluorescence at 305 nm. Thermal …

Insights From Consumers' Exposure To Environmental Nutrition Information On A Dashboard For Improving Sustainable Healthy Food Choices, Prince Agyemang, Ebenezer M. Kwofie, Jamie L. Baum, Dongyi Wang

Biological and Agricultural Engineering Faculty Publications and Presentations

Over the last decade, there has been a growing demand for tools to support sustainable healthy lifestyles, including food choices. Through a survey, this study examined the influence of environmental nutrition information conveyed with aids such as nudges and traffic light labels through a Dashboard for Improving Sustainable Healthy (DISH v1.0) food choices on consumer purchase intentions. DISH is an application that enables end-users to envisage and compare the potential impacts of their choices before purchasing. In the early stage of the technological development of DISH, the environmental nutrition information of two fast-food menus, plant-based and animal-based burgers, was tested …

Membrane Filtration Of Nanoscale Biomaterials: Model System And Membrane Performance Evaluation For Aav2 Viral Vector Clarification And Recovery, Mara Leach, Kearstin Edmonds, Emily Ingram, Rebecca Dutch, Sumith R. Wickramasinghe, Malgorzata Chwatko, Dibakar Bhattacharyya

Chemical Engineering Faculty Publications and Presentations

The growing demand for viral vectors as nanoscale therapeutic agents in gene therapy necessitates efficient and scalable purification methods. This study examined the role of nanoscale biomaterials in optimizing viral vector clarification through a model system mimicking real AAV2 crude harvest material. Using lysed HEK293 cells and silica nanoparticles (20 nm) as surrogates for AAV2 crude harvest, we evaluated primary (depth filters) and secondary (membrane-based) filtration processes under different process parameters and solution conditions. These filtration systems were then assessed for their ability to recover nanoscale viral vectors while reducing DNA (without the need for endonuclease treatment), protein, and turbidity. …

Economic Impact Of Energy Accounting Schemes For Commercial Systems On A Broiler Farm With Power Demand And Generation, Yi Liang, Michael Popp

Biological and Agricultural Engineering Faculty Publications and Presentations

The aim of this study was to assess the impact of the on-farm solar photovoltaic (PV) generation to offset grid electricity consumption on a commercial poultry farm in the US. Hourly electricity production by PV systems was estimated using the System Advisor Model (SAM) of the National Renewable Energy Lab (NREL) and compared with the estimated electric load demand of a broiler house. We analyzed the economic benefits of installing solar systems of three capacities under net energy metering and net energy billing pricing scenarios. Results suggested that a smaller PV installation of 35 kWp, while substantially short of meeting …

Environmental-Health Convergence: A Deep Learning-Oriented Decision Support System For Catalyzing Sustainable Healthy Food Systems, Prince Agyemang, Ebenezer M. Kwofie, Jamie I. Baum, Dongyi Wang, Emmanuel A. Kwofie

Biological and Agricultural Engineering Faculty Publications and Presentations

To generate evidence to address food system challenges, we developed an adaptable framework for multimodel assessment of the convergence effect of health and environmental drivers in food systems. We achieved this goal by developing a modeling framework that facilitates testing and applying four deep-learning algorithms using a case study of the United States's food system. Among the models tested, the bidirectional and single-layer long short-term memory models outperformed the others with α_E(2.75) and α_H(3.51) when predicting environmental drivers and health drivers, respectively. All the models tested performed better at predicting environmental than health drivers. The best-performing …

Unlocking The Phosphorus Circularity Potential Of Corn Belt Watersheds With Biorefinery Phosphorus Recovery Incentives, Kenneth Ruffatto, Arghajeet Saha, Rebecca L. Muenich, Andrew J. Margenot, Roland D. Cusick

Biological and Agricultural Engineering Faculty Publications and Presentations

As global phosphorus (P) stores rapidly decline, P fed algal blooms continue to threaten critical freshwater resources across the globe. In the Midwestern United States (US), particularly the Corn Belt, biorefineries could play a key role in addressing this issue. By recovering P from the byproducts of ethanol production these facilities could reduce the P content of distillers grain feed, thereby reducing P excreted in manures. This process could potentially divert P away from concentrated animal feeding operations (CAFOs) and toward renewable P (rP) fertilizer production utilizing the recovered P. To foster the inclusion of P recovery incentives in state …

Cold-Plasma-Driven Ammonia Synthesis Over Porous Silica: The Role Of The Morphology, Fnu Gorky, Vashantu Storr, Jacek B. Jasinski, Maria L. Carreon

Chemical Engineering Faculty Publications and Presentations

Nonthermal plasma (NTP) has opened unexplored routes for small-scale, decentralized ammonia production. However, understanding the ammonia formation pathways when employing NTP-driven processes is challenging due to the complex nature of the process. In this work, we report the effects of the morphology and textural properties on ammonia production. Herein, we explore mesoporous and macroporous regimes in silica. Performance of mesoporous silica with a gyroid morphology displays the highest ammonia production rate of 160.7 mu mol/ming-cat at a plasma power of 15 W. The findings from this work provide insights into tailoring porous structures and morphology for ammonia production powered by …

An Ultra-Low-Power 0.8 V, 60 Nw Temperature Sensor For Battery-Less Wireless Sensor Networks, Fnu Naveed, Jeff Dix

Electrical Engineering and Computer Science Faculty Publications and Presentations

This work presents a nano-watt digital output temperature sensor featuring a supply-insensitive, self-biased current source. Second-order temperature dependencies of the MOS diode are canceled to produce a stable reference and a linear temperature-sensitive voltage. The sensor integrates a sensing unit, voltage-controlled differential ring oscillators, and a low-power frequency-to-digital converter, utilizing a resistor-less design to minimize power and area. The delay element in the ring oscillator reduces stage count, improving noise performance and compactness. Fabricated in 65 nm CMOS, the sensor occupies 0.02 mm2 and consumes 60 nW at 25 °C and 0.8 V. Measurements show an inaccuracy of +1.5/−1.6 °C …

A Multi-Method Geophysical Approach For Complex Shallow Landslide Characterization, Mohammadyar Rahimi, Clinton Wood, Meersad Fathizadeh, Salman Rahimi

Civil Engineering Faculty Publications and Presentations

This case study demonstrates the value of combining multiple non-invasive geophysical methods to characterize a landslide along Highway 7 near Jasper, Arkansas, USA. Geophysical testing was conducted using Multichannel Analysis of Surface Waves (MASW), Horizontal to Vertical Spectral Ratio (HVSR), and Electrical Resistivity Tomography (ERT), supplemented by select soil borings. The geophysical investigation aimed to provide a high-resolution, near-continuous view of subsurface conditions, including bedrock depth and the location of the groundwater table or highly saturated zones within the slide area. These factors are important contributors to slope instability. The MASW results revealed a highly variable depth to weathered bedrock …

Powersynth 2: Automated Power Electronics Physical Design Synthesis With Custom And Heterogeneous Components, Mehran Sanjabiasasi, Alan H. Mantooth, Yarui Peng

Electrical Engineering and Computer Science Faculty Publications and Presentations

Electronics Design Automation (EDA) has shown significant importance in the power electronics industry. As power electronic circuits become more complex, the traditional trial-and-error approach in physical design becomes less effective and time-consuming. Novel packaging technologies and intelligent physical design automation solutions are crucial to overcome these challenges and produce reliable solutions. PowerSynth 2 is an EDA tool for generating and optimizing power module layouts. To extend the layout synthesis capability beyond power modules, the layout engine needs to consider various custom components such as capacitors, inductors, and gate drivers. This research presents a novel framework for the layout synthesis process …

Rfid Occupied Advanced Framework For Specialized Vehicle Access, Operating System, And Wireless Data Transmission Without Human Intervention, Abdullah Al Mamun Anik, Mosammet Sadia Akter Moon, Fahim Faysal Arnob, Mehedi Hasan, S. A. Naimal Hoque, Mohammad Mashhunar Rahman, Tahzin Bin Ahmed, Tonmoy Barua

Mechanical Engineering Faculty Publications and Presentations

Radio frequency identification system (RFID) tags are tiny electronic devices that include a distinctive code that can be detected by a reader that supports RFID. The string of characters is used for recognizing and monitoring the object to which the tag is connected. RFID tags interact with RFID readers using radio frequency. While the tag comes into close proximity to the scanner, that device sends a radio signal that triggers the tag. The tag then responds by sending its unique identity. RFID pinpointing ability is verified experimentally in two different techniques, one utilizing radar and the other a photosensitive transition. …

Accurately Constituting Robust Interfaces For High-Performance High-Energy Lithium Metal Batteries, Kevin V. Carballo, Meetesh Singh, Xiangbo Meng

Mechanical Engineering Faculty Publications and Presentations

High-energy lithium metal batteries (LMBs) have received ever-increasing interest. Among them, coupling lithium metal (Li) with nickel-rich material, LiNi_xMn_yCo_zO₂ (NMCs, x ≥ 0.6, x + y + z = 1), is promising because Li anodes enable an extremely high capacity (∼3860 mA h g⁻¹) and the lowest redox potential (−3.04 V vs. standard hydrogen electrode), while NMCs can achieve a much higher capacity of ∼200 mA h g⁻¹ and lower cost than those of LiCoO₂. However, the resultant Li‖NMC cells have been hindered from commercialization due to a …

Cross-Facility Reliable Deep Learning Based Beef Marbling Assessment Via Unsupervised Domain Adaptation Regression, Samuel Vinson, Dongyi Wang

2025 Research Poster Competition

Beef is one of the most important sources of animal protein and plays a crucial role in daily diets to support muscle growth, energy production and overall health. Historically, each beef carcass was evaluated by 3-5 skilled United States Department of Agriculture (USDA) meat graders, which are still considered as the gold standard for grading. Since 2009, electronic imaging grading systems have been approved by the USDA and have been gradually adopted in the grading facilities. Accurate and consistent beef grading plays a critical role in maintaining the quality, market value, and consumer trust in U.S. beef products. The USDA …

Twitter-Based Osint For Cyber Event Analytics, Dakota S. Dale, Kylie Mcclanahan, W. Sky Elder, Qinghua Li

Electrical Engineering and Computer Science Faculty Publications and Presentations

Open-Source Intelligence (OSINT) is often regarded as a critical component for cybersecurity intelligence gathering to secure cyber infrastructures. As Artificial Intelligence (AI) and social media progress and become more commonplace, we have the unique opportunity to collect and analyze information from social media in real time. In this paper, we propose an AI-based framework for automatically filtering the Twitter stream for cybersecurity information, analyzing the natural language to aggregate the tweets around specific cybersecurity events, and certifying the information. The system's applications range from discovering events security operators may not have been aware of to helping operators investigate on-going events …

Sogar: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition, Naga Venkata Sai Raviteja Chappa, Pha Nguyen, Alexander H. Nelson, Han-Seok Seo, Xin Li, Page Daniels Dobbs, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Social group activity recognition is crucial for various applications including surveillance, human-robot interaction, and behavioral analysis. Current approaches often require extensive manual annotations and rely heavily on pre-trained detectors, limiting their practical applications. Additionally, existing methods struggle to effectively model long-term spatiotemporal relationships in group activities. This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we create local and global views with varying frame rates. Our self-supervised objective ensures that features extracted from contrasting views of the same video are consistent across …

Intercellular Stress Generation During 1d Collective Migration Of Cancer Cells, Logan Waddle, Jian Zhang

2025 Research Poster Competition

Physical forces drive many cellular processes such as migration and proliferation. A metastatic tumor will have invasive strands/chains that extend from the main tumor. These chains of cells collectively migrate away from the main tumor to establish new colonies elsewhere in the body. However, how physical forces drive this collective invasion and the required energy for this process is not well understood. Invasion of a metastatic tumor to surrounding tissues leads to a majority of cancer-associated death and is often a collective effort among cells, it is therefore important to fully understand the process behind collective cancer invasion.

The goal …

Stakeholder Perspective-Taking In Engineering Design; A Neurocognitive Approach, Megan Taylor, Yakhoub Ndiaye, Jenn Campbell

2025 Research Poster Competition

During the engineering design process, the ‘black box’ of a designer's mind determines who the stakeholders are, which stakeholder needs they are addressing and how they will address them. This process can build bias into engineering designs, leading to less equitable, accessible, and inclusive engineered artifacts. Design neurocognition, a new field that aims to determine the unknowns of a working designer’s mind, has arisen because of this uncertainty. The fNIRS (Functional Near-Infrared Spectroscopy) allows insight into the prefrontal cortex during decision making processes by analyzing the change in oxygenated blood in the surface of the prefrontal cortex, about 3 cm …

Exploring User Sentiment On Social Issues Via Neural Network Transfer Learning In Digital Communities, Ananya R. Vangoor

2025 Research Poster Competition

Understanding public sentiment on social issues is crucial for gauging the stance of the general population. Traditionally, surveys have been a common approach for this. However, to capture more candid opinions, social media provides a rich source of unadulterated opinions. By analyzing social media statements, we can gain insights into the perspectives of specific groups. More specifically, we will investigate the attitudes of the public into the relationship between hard work and success in the workplace.

To begin, I will be training a neural network on X, formerly known as Twitter, tweets to categorize each tweet as either pro-luck or …

Analyzing Unmanned Aircraft System (Uas) Incidents From Nasa Asrs Data Using Unsupervised Machine Learning, Kacey Haws, Neelakshi Majumdar

2025 Research Poster Competition

The NASA Aviation Safety Reporting System (ASRS) assembles voluntarily submitted aviation safety incident reports in their database to act on the information provided. This database allows the government, companies, and citizens to submit incident or situational reports to its database to discern recurring issues in the National Aviation System (NAS) so that the proper officials can act [1]. The narratives provided in these reports are text-based, resulting in large amounts of data to process. Previous work in the University of Arkansas Aerospace Systems Engineering and Transportation Laboratory (ASYST) lab involved parsing unmanned aircraft system (UAS) incident reports manually. While these …

New Insights Into Fertilisation With Animal Manure For Annual Double-Cropping Systems In Nitrate-Vulnerable Zones Of Northeastern Spain, Dolores Quilez, Monica Guillen, Marta Valles, Arturo Dauden, Beatriz Moreno-Garcia

Biological and Agricultural Engineering Faculty Publications and Presentations

Maize double-cropping production systems in Mediterranean areas have a great nitrogen extraction capacity and high nitrogen (N) requirements. This study aims to assess whether in these farming systems, animal manure can be applied, using adequate management practices, at levels exceeding the maximum annual amount of livestock manure established in the European Nitrate Directive for vulnerable zones (170 kg N ha-1) without increasing the risk of water nitrate contamination. We compare the risk of nitrate leaching under two fertilisation strategies, one with synthetic fertilisers and the second with a maximised application of pig slurry, exceeding the limits of the EU Nitrate …

A Review Of Unmanned Aircraft Systems Safety Reporting And Analysis Of Incidents, Ryker Davis, Neelakshi Majumdar

2025 Research Poster Competition

Unmanned Aerial Systems (UAS), or drones are rapidly integrating into various industries. However, safety concerns regarding their design, training, and operation are rising. To ensure safer integration into the National Airspace System (NAS), it is crucial to understand the potential risks associated with UAS operations. To address these safety concerns, a systematic analysis of UAS incidents is essential to identify common factors and potential risks. There are various sources that record UAS safety events such as accidents and incidents. Analyzing these safety events to identify their causes and contributing factors may help in developing improved design and operations and thereby …

A Statistical Analysis For Evaluating The Parameters Influencing The Rutting And Cracking Performance Of Asphalt Mixtures, Alexis Light, Mohammad Tahir Ansari, Andrew F. Braham

2025 Research Poster Competition

Durable pavement is essential for modern transportation infrastructure, especially in the United States of America which boasts over 8.5 million lane miles of roads and highways. Despite advanced construction techniques, asphalt pavements are susceptible to rutting and cracking, significantly affecting their performance and maintenance costs. Current methods for analyzing rutting and cracking in asphalt mixtures rely on various parameters, leading to measurement variability. This highlights the need for more rigorous analysis to explore the relationship between mix design variables and pavement performance. This research explores the IDEAL-CT and Asphalt Pavement Analyzer (APA) data from mix designs collected by the Arkansas …

Solo Versus Dual: A Comparative Analysis Of Instructional General Aviation Accidents, Jesse Pham, Neelakshi Majumdar

2025 Research Poster Competition

The Federal Aviation Administration (FAA) oversees and regulates all aviation operations in the United States including General Aviation (GA) (FAA, 2016). General aviation is defined as all civil aviation operations other than scheduled air services and non-scheduled air transport operations for remuneration or hire (ICAO, 2009). The FAA sets the standards for pilot certification and training. Student pilots are required to fly at least a minimum of 40 hours to earn their private pilot license (CFR, 2024). During this time, students are to fly for at least 30 hours with a flight instructor and 10 hours solo, which includes cross-country …

Simulation-Enhanced Bayesian Optimization Of System Designs Using Hybrid Physical And Computer Experiments, Luke Kim, Kelly Sullivan, Haitao Liao, Ed Pohl

2025 Research Poster Competition

We consider the problem of learning and optimizing the performance of a system by conducting a limited number of physical and digital experiments within a design space. Physical experiments are assumed to be unbiased but costly, while digital experiments (e.g., simulations) are less expensive but may introduce bias due to the limitations of the simulation model. This problem is relevant in many fields, such as optimizing engineered systems where performance (e.g., mechanical properties and reliability) depends on various design variables and external/internal factors. Without digital experiments, optimizing the system’s performance amounts to evaluating a noisy and expensive-to-assess black-box function, a …

Facial Chick Sexing: An Automated Chick Sexing System From Chick Facial Image, Marta Veganzones Rodriguez, Thinh Phan, Arthur F.A. Fernandes, Vivian Breen, Jesus Arango, Michael T. Kidd, Ngan Le

Computer Science and Computer Engineering Faculty Publications and Presentations

Chick sexing, the process of determining the gender of day-old chicks, is a critical task in the poultry industry due to the distinct roles that each gender plays in production. While effective traditional methods achieve high accuracy, color, and wing feather sexing is exclusive to specific breeds, and vent sexing is invasive and requires trained experts. To address these challenges, we propose a novel approach inspired by facial gender classification techniques in humans: facial chick sexing. This new method does not require expert knowledge and aims to reduce training time while enhancing animal welfare by minimizing chick manipulation. We develop …