Engineering Commons^™

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, …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Ronald E. Mcnair Scholars Program Profiles And Abstracts 2021, Mcnair Scholars Program

McNair Symposium

This is the complete event program and provides presentation abstracts and biographies of McNair scholars and their mentors.

Ronald E. Mcnair Scholars Program Profiles And Abstracts 2020, Mcnair Scholars Program

McNair Symposium

This is the complete event program and provides presentation abstracts and biographies of McNair scholars and their mentors.

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 …

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 …

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 …

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?

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 …

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 …

Bond-Type Cfrp Anchorage System For Prestressed Concrete Applications, Yasir Saeed, Franz Rad, Salam Al-Obaidi

Student Research Symposium

High tensile strength, adjustable and high modulus of elasticity, high strength-to-weight ratio, and non-corrosiveness are great features which have made Fiber Reinforced Polymer (FRP) very attractive to engineers. Prestressed concrete applications require high strength prestressing material that could apply and maintain effective compressive force to concrete members. Although FRPs, especially Carbon FRP (CFRP), have the desired strength, no efficient system for its anchorage to concrete has been devised yet. This paper presents an experimental evaluation on new bond-type CFRP anchors. A total of eleven samples were prepared and tested. The CFRP rods were 0.375 in. and 0.50 in. diameter. The …

Concrete Beams With Fully Corroded Steel Repaired With Cfrp Laminates, Needa M. Lingga, Yasir Saeed, Franz Rad, Anas Yosefani

Student Research Symposium

This research focused on concrete beams with voids simulating beams with fully corroded steel that were repaired with CFRP laminates. The experimental program included testing five, approximately one- third-scaled simply supported rectangular concrete beams. The aim was to investigate the extent of improvement by CFRP to flexural and shear capacity of beams that contain fully corroded steel bars, simulated by voids. Load carrying capacity, deflection, and ductility were measured and compared. Test results showed that one layer of CFRP increased the load capacity to slightly higher than the typical code-designed RC beam, and two layers of CFRP increased it by …

Coastal Bridges Subjected To Waves: Analysis And Quantification Of Forces, Alaa Waleed Hameed, Thomas Schumacher

Student Research Symposium

Coastal bridges can be exposed to significant wave forces during hurricane events. This research is studying the parameters that govern the structural response through data analysis of a large experimental data set. This data set was generated by testing a heavily-instrumented 1:5-scale bridge superstructure model, which was modeled after the I-10 Bridge over the Escambia Bay, under various wave conditions and water levels in a large wave flume. A unique aspect of the model is that the flexibility of the substructure can be adjusted to represent different types of bridge support systems. This poster discusses the first part of the …

Radiation Source Localization By Using Backpropagation Neural Network, Jian Meng, Christof Teuscher, Walt Woods

Student Research Symposium

The most difficult part of the radiation localization is that we cannot use the traditional acoustic localization method to determine where the radiation source is. It’s mainly because the electromagnetic waves are totally different with the sound wave. From the expression of the radioactive intensity, we can tell that the intensity of radiation not only depend on the distance from the radiation but also related to the type of the nuclide. In general, the relationship between the intensity and the distance satisfy the inverse-square law, which is a non-linear relationship. In other words, if we can use the measurement and …

Apprehensive Drought Characteristics Over Iraq: Results Of A Multidecadal Spatiotemporal Assessment, Maysoun Ayad Hameed, Ali Ahmadalipour, Hamid Moradkhani

Student Research Symposium

Drought is an extreme climate phenomenon that happens slowly and periodically threatens the environmental and socio-economic sectors. Iraq is one of the countries in the Middle East that has been dealing with serious drought-related issues in the 21st century. Here, we investigate meteorological drought across Iraq from 1948 to 2009 at 0.25◦ spatial resolution. The Standardized Precipitation Evapotranspiration Index (SPEI) has been utilized as a multi-scalar drought index accounting for the effects of temperature variability on drought. Four of the main characteristics of drought including extent, intensity, frequency and duration are studied and the associated spatiotemporal patterns are investigated for …

Using Reservoir Computing To Build A Robust Interface With Dna Circuits In Determining Genetic Similarities Between Pathogens, Christopher Neighbor, Christof Teuscher

Student Research Symposium

As computational power increases, the field of neural networks has advanced exponentially. In particular recurrent neural networks (RNNs) are being utilized to simulate dynamic systems and to learn to predict time series data. Reservoir computing is an architecture which has the potential to increase training speed while reducing computational costs. Reservoir computing consists of a RNN with a fixed connections “reservoir” while only the output layer is trained. The purpose of this research is to explore the effective use of reservoir computing networks with the eventual application towards use in a DNA based molecular computing reservoir for use in pathogen …

Wideband Absorber Characterization Using Coaxial Airline And Electromagnetic Simulation, Ha Tran, Thanh Le, Branimir Pejcinovic

Student Research Symposium

With the increase in popularity of electronic devices especially the wireless devices, microwave absorber becomes more essential to reduce electromagnetic interference. A deep understanding of electromagnetic properties namely electric permittivity and magnetic permeability is required in order to fabricate, test and use microwave absorber. In this study, we focused on developing a procedure to parameterize material electromagnetic properties. We first extract material properties by placing samples inside an airline and taking measurements of scattering parameters matrix with a vector network analyzer. Air-line is the preferred transmission line medium since the traveling wave inside the airline is both TEM and confined. …

Biochemical Reservoir Computing, Hoang Nguyen, Christof Teuscher

Student Research Symposium

Reservoir computing is an emerging machine learning paradigm. Compared to traditional feedforward neural networks, the reservoir can be unstructured and recurrent and only the output layer is trained. Reservoirs can be built with various types of physical components, yet, biochemical building blocks have not been widely used. This project focuses on designing and testing a reservoir computer (RC) based on chemical reaction network (CRN). We simulated high-level CRNs in MATLAB and their complex chemical dynamics were observed over time. A CRN constructed by a network of coupled deoxyribozyme oscillators was chosen for the final RC model. The inputs of the …

Business Model Innovation: Review Of The Concept, Importance, Classifications, And Elements, Ahmed Alibage, Mark Ahn

Student Research Symposium

The research trend on business models continues to surge, foreseeing them as the future blueprint to create and sustain competitive advantages, as well as the major driver that guides the strategic renovation efforts of businesses all over the world. In this research, we intensively review the literature on the business model regarding the concept emergence, theoretical background, definitions, importance, classifications, and the structure of the elements. Our interest is in gaining a better understanding of how to innovate a business model that can lead to create and sustaincompetitive advantages. Based on our findings, the literature to date lacks the systematic …

Toward Understanding Pu And Peou Of Technology Acceptance Model, Nayem Rahman

Student Research Symposium

Technology Acceptance Model (TAM) is considered one of the most popular models used in Information System (IS) research. Fred Davis developed this model as part of his doctoral research at MIT in 1986. Since then this model has been widely used in IS research and other disciplines. Two main components of TAM are Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). This model allowed researchers to plug-in external factors to these two components. Researchers have used a variety of external factors to draw relationships between these two internal factors of TAM model. However, most of the research used these …