Digital Commons Network^™

Performance-Based Risk Assessment For Large-Scale Transportation Networks, Anteneh Deriba, David Y. Yang

Student Research Symposium

Efficiently assessing the risk of asset failure due to deterioration or extreme events is crucial for transportation asset management. Traditional methods often lack effectiveness in directly evaluating system performance-based risks, facing challenges like the exponential increase in system states and the emergence of low-probability high-consequence events ("grey swan" events). To address these, this paper introduces a novel performance-based risk assessment approach for large-scale transportation networks, inspired by the Transitional Markov Chain Monte Carlo (TMCMC) method. This method transforms the risk assessment problem into a high-dimensional posterior distribution, with system risk acting as the normalization factor (evidence). It also provides risk-based …

Comparative Life Cycle Assessment Of Hydrogen Production Via Various Pv-Assisted Electrochemical Water Splitting Techniques, Achyuth Ravilla

Student Research Symposium

Photoelectrochemical (PEC) and photovoltaic-electrochemical (PV-EC) water-splitting technologies have emerged as cost-effective options for large-scale green hydrogen production in industrial applications. Solar to hydrogen (STH) efficiencies of these technologies have reached up to 20% and several pathways have been explored to drive down the cost of hydrogen using these technologies to less than $2/kg. However, the environmental impact assessment of these technologies for industry-scale deployment has not been explored in previous studies. This study assesses the environmental impacts of PEC and PV-EC technologies by conducting a cradle-to-gate life cycle assessment. The functional unit considered for this assessment is 1 kg of …

Flexible Strain Gauge Sensors As Real-Time Stretch Receptors For Use In Biomimetic Bpa Muscle Applications, Rochelle Jubert

Student Research Symposium

This work presents a novel approach to real-time length sensing for biomimetic Braided Pneumatic Actuators (BPAs) as artificial muscles in soft robotics applications. The use of artificial muscles enables the development of more interesting robotic designs that no longer depend on single rotation joints controlled by motors. Developing robots with these capabilities, however, produces more complexities in control and sensing. Joint encoders, the mainstay of robotic feedback, can no longer be used, so new methods of sensing are needed to get feedback on muscle behavior to implement intelligent controls. To address this need, flexible strain gauge sensors from Portland company, …

Characterization Of Chopped Carbon Fiber Reinforced Composites Produced Using Fused Deposition Modeling, Jonathon Tran, Rachel Shubella

Student Research Symposium

Fused deposition modeling (FDM) is an additive manufacturing (AM) process which can create parts with complex geometries in their final shape without need for additional specialized tools or devices. The FDM process builds parts by adding material layer by layer only where it is needed, saving energy, costs, production time for complex parts, and minimizing waste. Fiber reinforcement can significantly enhance the mechanical properties of a polymer material and depends significantly on the fiber length distribution and fiber orientation distribution of the final part. In this research, we investigated the various infill patterns of FDM printed Markforged onyx which is …

Pulse Modulation In Braided Pneumatic Actuators Mimics Contractile Behavior Of Biological Muscles, Mohamad Elzein

Student Research Symposium

Advancements in robotics and bioengineering aim to emulate biological muscle systems through robotic actuators, blending mechanical strength with biological adaptability. A lesser-explored aspect is mimicking the pulse-like control characteristic of biological muscles, which contract in response to action potentials from motoneurons, with muscle contractile force relying heavily on the timing between these potentials. This study explores the effect of pulse lengths and the gaps between pulses on braided pneumatic actuators (BPAs), which mimic the nonlinearity and dynamic response of biological muscles. It hypothesizes that artificial muscles utilizing pulse-based control will exhibit a similar force dependency on the intervals between pulses …

Self-Balancing Robot Leg, Ben Bolen

Student Research Symposium

Research in the Agile and Adaptive Robotics Lab involves the creation of biomimetic robots. To this end, we developed a self-balancing robot leg actuated with braided pneumatic actuators (BPAs)—a type of pneumatic artificial muscle. These BPAs, akin to human muscles, exhibit properties such as high strength-to-weight ratio and tunable passive stiffness. An Inertial Measurement Unit (IMU) was placed on top of the tibia for feedback and the tibia and foot were connected with a hinge joint. The orientation of the ankle joint was controlled with an Arduino microcontroller sending commands to the proportional pressure valves supplying the BPAs. Leg balance …

Reducing Switching Noise And Losses In Two-Stage Electric Power Converters, Abhijeet Prem

Student Research Symposium

Advancements in semiconductor devices are enabling the design of better electrical power converter systems. Wide Bandgap (WBG) switching devices from Silicon Carbide and Gallium Nitride can operate at high temperatures, voltages, and frequencies with faster turn-on/off periods, improving converter performance over silicon devices. However, WBG technology is still new, and the rapid switching transitions of these devices lead to issues such as voltage overshoots, ringing, and electromagnetic interference, which need to be addressed for widespread adoption. This work introduces a new control method for reshaping the switching voltages, which overcomes the disadvantages of fast transition time without increasing the system's …

Plasma Ion Source, Nathan K. Davis

Student Research Symposium

It is well known that a plasma can be created with both high input power and ultra low pressure. The challenge is in creating these same plasma characteristics with both lower power while maintaining a higher pressure. We have developed an ion beam by careful manipulation of magnetic and electric fields. Magnetic fields are used to accelerate ambient electrons to ionize the low pressure gas into a plasma. Electric fields are used to extract the ions into a focused beam. To achieve these initial ionizations, an artificial vacuum is created to reach low enough pressures to ionize the gas. A …

Comparative Life Cycle Assessment Of Recycling Processes For Perovskite Solar Cells, Juan P. Herrera, Jules Freeman, Achyuth Ravilla, Ilke Celik

Student Research Symposium

Perovskite solar cells (PSCs) have emerged as a promising option for solar energy generation. However, it is essential to consider the environmental impact of these innovative photovoltaic (PV) technologies as the industry moves towards commercialization. Researchers are currently exploring ways to recycle PSCs to recover valuable materials and reduce their environmental impact at the end of their life. To ensure the sustainability of PSCs, this study evaluates and compares the environmental impacts of five recently developed recycling approaches. The Tool for Reduction and Assessment of Chemicals (TRACI) method was utilized to measure environmental impacts in categories such as acidification (kg …

Deriving Analytical Design Constraints For Absolute & Relative Encoding Schemes In Functional Subnetworks, Cody W. Scharzenberger-Braet, Alexander Hunt

Student Research Symposium

As neural networks have become prolific solutions to modern problems, there has been a congruent rise in the popularity of the numerical machine learning techniques used to design them. While they are highly generalizable, numerical methods tend to produce networks that act as inscrutable “black boxes,” making it difficult to interpret their behavior. One solution to the problem of network transparency is to use analytical techniques, but these methods are underdeveloped compared to their numerical alternatives. In order to enhance the viability of analytical techniques, this work extends previous efforts to quantify the impact that non-spiking neural encoding schemes have …

Improving Intersection Safety With Geographically-Targeted Crash Prediction Models In Utah, Atul Subedi

Student Research Symposium

This project aims to improve intersection safety in Utah by developing geographically-targeted crash prediction models. The lack of research investigating active mode crashes at signalized intersections in different geographical regions calls for this study. The objective of this research is to understand the factors associated with the frequency of active mode crashes at signalized intersections. Exposure variables such as AADT, pedestrian and bicycle volumes, and intersection-level variables such as crossing distance, speed limit, and presence of street lights were analyzed using a negative binomial regression model.

Understanding The Role Of A Putative Type I Polyketide Synthase In Chlorflavonin Biosynthesis, Ammar Mussaji

Student Research Symposium

Flavonoids are an important class of plant secondary metabolites with a variety of biological functions in the development processes of hosts. These molecules have also shown health-benefiting properties such as antioxidant and anti-inflammatory activities. As such, they are commonly used as pharmaceuticals and nutraceuticals. In plants, flavonoids are assembled through a type III polyketide synthase (PKS) and associated tailoring enzymes such as hydroxylase and glycosyltransferase. Some filamentous fungi also produce flavonoids, such as chlorflavonin from Aspergillus candidus. Chlorflavonin is a novel halogenated flavonoid found in nature reported to possess antifungal and anti-tuberculosis activity. Unlike plants, the biosynthetic process of flavonoids …

Glycosylation Of Anti-Tb Agent Chlorflavonin For Combating Mycobacterium Tuberculosis, Jie Ren

Student Research Symposium

More than two billion people were infected by the bacterial pathogen Mycobacterium tuberculosis (Mtb) in 2020. However, during the past 50 years, the first-line (isoniazid, delamanid, and rifampicin) and second-line (capreomycin, streptomycin, and cycloserine) therapies have remained unchanged with disadvantages such as long treatment periods and severe side effects. The slow development of anti-TB drugs cannot combat the fast development of drug resistant M. tuberculosis strains from multidrug-resistant (MDR) into extensively drug resistant (XDR), which further hinders the World Health Organization’s goal to end the global TB pandemic by the year 2035. Flavonoids are a type of natural product with …

Does Diet Effect The Brain?, Janna Hart

Student Research Symposium

Short-chain fatty acids are biomolecules produced from bacterial fermentation of dietary fiber in the gut. Short-chain fatty acids are used in the gut to supply energy and reduce inflammation but are also believed to have effects on the brain. While we do not know how short-chain fatty acids affect the brain and behavior, recent research has led to the idea of using dietary changes as a treatment for mental health disorders. In my research, we aimed to visualize where short-chain fatty acids act in the brain with a particular focus on neural immune cells called microglia and the neurons that …

Memristors, Memcapacitors And Their Application In Neuromorphic Computing, Nithyakalyani Sampath

Student Research Symposium

Data-intensive computing operations, such as training neural networks, are essential but energy-intensive. Memcapacitance and memristance,which can be described as capacitance and resistance, with “memory”, are properties of semiconductor devices that are observed on the nano-scale. These properties allow for data storage without a constant source of power, leading to hardware which is more energy efficient.

We intend to demonstrate that we can build specialized hardware onto which a neural network can be directly mapped using memristors and memcapacitors, improving the energy efficiency of the network. We will use Simulation Program with Integrated Circuit Emphasis (SPICE) to model our memcapacitor and …

Growing Reservoir Networks Using The Genetic Algorithm Deep Hyperneat, Nancy L. Mackenzie

Student Research Symposium

Typical Artificial Neural Networks (ANNs) have static architectures. The number of nodes and their organization must be chosen and tuned for each task. Choosing these values, or hyperparameters, is a bit of a guessing game, and optimizing must be repeated for each task. If the model is larger than necessary, this leads to more training time and computational cost. The goal of this project is to evolve networks that grow according to the task at hand. By gradually increasing the size and complexity of the network to the extent that the task requires, we will build networks that are more …

Electric Vehicles: Lowering Greenhouse Gas Emissions, Tyler Hansen

Student Research Symposium

The amount of greenhouse gasses in the earth’s atmosphere has led to rapid climate change. In order to remedy this, the amount of annual greenhouse gas emissions needs to be decreased. As of 2019, transportation accounted for 29 percent of the Nation’s total greenhouse gas emissions. Therefore, one important way to decrease greenhouse gas emissions in the U.S will be a switch from traditional vehicles powered by gasoline and diesel, to electric vehicles. Despite challenges of infrastructure, resources, and consumer access, a national switch to electric vehicles is possible and necessary.

A Novel Composite Hybrid Energy Storage System For Hybrid And Electric Vehicles, Marium Rasheed

Student Research Symposium

This work introduces a composite hybrid energy storage system (CHESS) architecture that combines energy-dense and capacitively-coupled power-dense battery packs in a unique configuration that requires minimal energy balancing using low-power DC-DC converters. A power-dense battery is coupled to an energy-dense battery using a relatively small supercapacitor module that naturally distributes the system current between the two packs, requiring no additional contactors or full-power processing DC-DC converters. A design procedure is developed to size the system for plug-in hybrid and battery electric vehicles (PHEVs and BEVs). The procedure results in designs that achieve weight reduction for a PHEV/BEV battery-energy-storage system (ESS) …

Nuclear Fusion: Powering The Future, Maxwel Head

Student Research Symposium

There has always been a concern for power generation for the world. With limited fossil fuels and the inefficiency of our current, renewable, power generation, a solution to our issue has been in the works for many years. Engineers, scientists, and civil workers are hard at work attempting to apply nuclear fusion to create massive amounts of power for the foreseeable future. Research was conducted using internet and library resources to find primary and secondary sources. For this study, interviews and news reports and case studies were reviewed to provide diverse information. To summarize what was found, engineers are hard …

Effect Of Cannabidiol On Crystallization Behavior And Physical Properties Of Cocoa Butter And Palm Oil, Isaac Hilton

Student Research Symposium

Demand for lipid-based products containing cannabidiol (CBD) is increasing following the legalization of industrial hemp production. This study investigates the impact of CBD on the crystallization behavior and physical properties of cocoa butter (CB) and palm oil (PO) for possible food applications. CB and PO samples with 0%, 1%, and 2.5% CBD were crystallized at 22°C and 26°C, respectively and the crystallization as a function of time was measured using a pulsed NMR for 165 min and 90 min, respectively. Melting behavior, crystal morphology, and viscoelasticity were measured at this time. Viscoelasticity and hardness were also measured after storing the …

Financial Literacy In America, John Cappelli

Student Research Symposium

After graduation most people do not have enough financial knowledge to be successful. This research project looks at how financial literacy courses impact students of different backgrounds. Research was conducted using online databases to evaluate primary and secondary sources including surveys and Add something specific about the sources you used. From this research I found that US high school graduates are lacking in financial education. In conclusion I think that all US highschools need to include mandatory financial education courses in order to ensure students have at least a basic understanding before having to make major decisions.

Investigating Factors That Predict Progress High Achieving Engineering Students Make Towards Desired Outcomes Of College, Ibukun Osunbunmi

Student Research Symposium

In an effort to increase the retention and progress undergraduate engineering students are making towards the desired outcome of college, researchers have been investigating what factors influence the academic achievement of students. The desired outcomes of college in this study include intellectual and scholarly development, workforce preparedness, advance in general knowledge, personal development, and scientific and technological skill development. While some studies have shown evidence that students’ engagement and learning skills are important predictors, others have suggested that educational policies, background, and demography of students are significantly associated with students’ academic achievement. In this study, predictive modeling of parents’ educational …

Paying The Pied Passer: Discussing The Appropriate Contract To Award Nfl Quarterbacks, Alex Gohr

Student Research Symposium

No NFL team has ever won the Super Bowl while simultaneously paying their starting quarterback more than 13% of the maximum budget allowed for player salaries. This paper explores the effects of quarterbacks on an NFL roster and the consequences of the size of their contracts have on the performance of the team as a whole entity. This research was derived from databases of NFL statics and expert opinions on the matter of player contracts. From the research conducted, it is concluded that quarterbacks must voluntarily take less money for the opportunity to continue to compete for championships or, alternatively, …

Name-Matching Techniques For Disambiguating Interaction Data, Adam Weaver

Student Research Symposium

Fuzzy name matching methods are helpful because names are often misspelled, sound similar, or reside in similar circumstances. A fuzzy name matching process assigns two names a similarity score between 0 and 1 using name-matching techniques (with 1 meaning identical and 0 meaning entirely unique). Fuzzy name matching is used for optimizing customer databases, creating more accurate medical records, or in Social Network Analysis (SNA). To observe the links between students’ social practices and academic performance, our research group is performing a large-scale (1000+ student) SNA through open-response name-generator surveys. Accordingly, the survey responses contain ambiguous names—many of which are …

Development Of A Design Guideline For Pile Foundations Subjected To Liquefaction-Induced Lateral Spreading, Milad Souri, Arash Khosravifar

Student Research Symposium

Past earthquakes confirmed that seismically induced kinematic loads from soil lateral spreading and inertial loads from structure can cause severe damages to pile foundations. The research questions are:

• How to combine inertial and kinematic loads in design of pile foundations in liquefied soil?
• How the combination of inertia and kinematics changes with depth?
• How this combination is affected by long-duration earthquakes?
• How this combination affects inelastic demands in piles?

Reliable Explanations Via Adversarial Examples On Robust Networks, Walt Woods, Jack H. Chen, Christof Teuscher

Student Research Symposium

Neural Networks (NNs) are increasingly used as the basis of advanced machine learning techniques in sensitive fields such as autonomous vehicles and medical imaging. However, NNs have been found vulnerable to a class of imperceptible attacks, called adversarial examples, which arbitrarily alter the output of the network. To close the schism between needing reliability in real-world applications and the fragility of NNs, we propose a new method for stabilizing networks, and show that as an added bonus, our technique results in reliable, high-fidelity explanations for the NN's decision. Compared to the state-of-the-art, this technique increased the area under the curve …

Diagnostic Imaging Of Structural Concrete Using Ground Penetrating Radar And Ultrasonic Array, Sina Mehdinia, Thomas Schumacher, Eric Wan, Xubo Song

Student Research Symposium

Structural concrete is the most widely used construction material in the world. Many structures critical to a society such as bridges, hospitals, and airports are built with concrete. While this material is well understood from a mechanical design point of view, still no accurate quantitative tools exist to assess it for damage and deterioration. This is of particular concern for an urban area like Portland with a mega-thrust earthquake waiting to occur. Non-destructive evaluation tools that can quickly and accurately give a full picture of the integrity of structural concrete elements will be key to help plan effective and safe …

Explanation Methods For Neural Networks, Jack H. Chen, Christof Teuscher

Student Research Symposium

Neural Networks (NNs) have become a basis of almost all state-of-the-art machine learning algorithms and classifiers. While NNs have been shown to generalize well to real-world examples, researchers have struggled to show why they work on an intuitive level. We designed several methods to explain the decisions of two state-of-the-art NN classifiers, ResNet and an All-CNN, in the context of the Japanese Society of Radiological Technology (JSRT) lung nodule dataset and the CIFAR-10 image dataset. Leading explanation methods LIME and Grad-CAM generate variations of heat maps which represent the regions of the input determined salient by the NN. We analyze …

Exploring And Expanding The One-Pixel Attack, Umairullah Khan, Walt Woods, Christof Teuscher

Student Research Symposium

In machine learning research, adversarial examples are normal inputs to a classifier that have been specifically perturbed to cause the model to misclassify the input. These perturbations rarely affect the human readability of an input, even though the model’s output is drastically different. Recent work has demonstrated that image-classifying deep neural networks (DNNs) can be reliably fooled with the modification of a single pixel in the input image, without knowledge of a DNN’s internal parameters. This “one-pixel attack” utilizes an iterative evolutionary optimizer known as differential evolution (DE) to find the most effective pixel to perturb, via the evaluation of …

An Assessment Of The Decision Making Units’ Efficiency In Service Systems (The Case Of Cellular Telecom), Maoloud Dabab, Timothy R. Anderson

Student Research Symposium

Most tools and models on performance and quality of service management are generic and do not solve the complex technical systems, which the most critical component on the network and where these tools should be applied. The objective of this research is to assess the cellular performance and Base Transceiver Station (BTS) efficiency by proposing a robust model that is derived from multiple Key Performance Indicators (KPIs) based on technical and financial aspects. The novelty of this research provides a comprehensive multidimensional model for tuning the BTS parameters, which can lead to developing a standard global mobile network KPI. The …