Engineering Commons^™

Digital Twin-Centered Hybrid Data-Driven Multi-Stage Deep Learning Framework For Enhanced Nuclear Reactor Power Prediction, James Daniell, Kazuma Kobayashi, Ayodeji Alajo, Syed Bahauddin Alam

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

The accurate and efficient modeling of nuclear reactor transients is crucial for ensuring safe and optimal reactor operation. Traditional physics-based models, while valuable, can be computationally intensive and may not fully capture the complexities of real-world reactor behavior. This paper introduces a novel hybrid digital twin-focused multi-stage deep learning framework that addresses these limitations, offering a faster and more robust solution for predicting the final steady-state power of reactor transients. By leveraging a combination of feed-forward neural networks with both classification and regression stages, and training on a unique dataset that integrates real-world measurements of reactor power and controls state …

Soy-Grid Prototype Development For Erosion Control Situated In The Scholarly And Public Spheres, Kyle Butler

Honors Senior Capstones and Theses

Erosion control is crucial for preserving coastlines and stream banks, protecting shoreline properties, and maintaining the ecological balance of vulnerable environments. Coastal areas are particularly susceptible to erosion caused by wave action, storms, and human activities. Erosion can lead to land loss, habitat destruction, and increased vulnerability to flooding. Effective erosion control measures help stabilize shorelines, prevent property damage, and safeguard coastal and inland infrastructure, while also preserving the natural beauty and recreational value of these areas.

Taking The Leap: A Qualitative Study Exploring The Entanglement Of The Vertical Transfer Process And Engineering Identity Development Among Community College Students, Janice Edwards

Dissertations of Practice

Taking the Leap: A Qualitative Study Exploring the Entanglement of the Vertical Transfer Process and Engineering Identity Development among Community College Students

Community colleges provide an open access, cost effective pathway to earning a baccalaureate degree in engineering. However, the transfer and degree completion rates remain low. Improved persistence has been linked to a variety of factors including a strong engineering identity. The purpose of this qualitative case study was to expand the understanding of engineering identity development during the vertical transfer process. Each milestone in the process, framed within transfer student capital, was considered to determine what, if any, …

In Vitro Hydrogel Blood Clots Phantoms, Ethan Evans

Bioengineering Master's Theses

This thesis presents a mechanical and microstructural characterization of agarose-based hydrogels as synthetic thrombus analogs for balloon catheter testing. Agarose gels ranging from 0.25% to 1.0% (w/v) were fabricated and analyzed using dynamic shear rheometry, capillary flow porometry, and gas pycnometry. Rheological data showed a nonlinear increase in storage modulus (G′), from 110 ± 66 Pa at 0.25% agarose to 4,900 ± 1,600 Pa at 1.0%, effectively mimicking the viscoelastic spectrum of acute to chronic thrombi. Gas pycnometry measurements indicated that true density (P_true) increased modestly from 1.03 g/mL to 1.13 g/mL over the same concentration range. This …

Numerical And Experimental Investigation Of The Dynamic Behavior Of Vibrating Niti Guidewire, Graham Gavin

Conference Papers

Minimally invasive interventions often utilise slender wires to access and navigate to target sites. These guidewires act as rails, facilitating access for other therapies. In endovascular procedures, the guidewires facilitate angioplasty balloons, stenting and other dilation procedures. Due to their small profile and flexibility, endovascular guidewires have limited ability to transfer forces to their tip and as a result cannot penetrate hard calcified blockages, commonly referred to as chronic total occlusions (CTOs) [1-2]. One method proposed to overcome this limitation is the application of vibrations to the wire. The vibrations are transmitted along the length of the wire to the …

Evaluation Of The Crossing Forces Of A Vibrating Guidewire In Contact With Model Calcified Materials, A. Rezaei, Graham Gavin, S. Raut

Conference Papers

Peripheral arterial disease (PAD) affects millions globally, with over 21 million cases reported in the U.S. in 2020. It occurs when leg arteries become narrowed or blocked, leading to complications like critical limb ischemia, where blood flow is severely restricted. Standard treatments, such as bypass surgery and endovascular procedures, aim to restore blood flow. However, advanced chronic total occlusions with calcified plaques, often prevent flexible guidewires crossing into the true lumen of the distal vessel, accounting for approximately 80% of procedural failure. The use of high-frequency (20- 50 kHz) mechanical vibrations (0-50 μm) delivered to the distal tip of specialist …

Material Vulnerabilities In Aviation: A Comparative Study Of Hiduminium Rr58 In The Concorde, Siddhant Singh, Kuldeep Agarwal

Automotive and Manufacturing Engineering Technology Department Publications

The catastrophic crash of Air France Flight 4590 in the year 2000 disclosed huge flaws in the material used to manufacture the Concorde fuel tanks, Hiduminium RR58 (Aluminum 2618A). Although this alloy was selected due to its resistance to high-temperature, this research examines its thermal and mechanical vulnerabilities, especially in relation to Aluminum 7075-T3, a large-scale application of which in the Boeing 747 was widespread. By comparing tensile strength, thermal conductivity, fatigue life, and creep life, this research determines how Hiduminium RR58's over-aging susceptibility, thermal cycling degradation, and rupture due to impact were contributory causes to the disaster. The study …

Performance-Based Approach To Characterize External Sulfate Attack For Reactive Powder Concrete, Umut Bakhbergen, Chang Seon Shon, Dichuan Zhang, Jong Ryeol Kim, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Reactive powder concrete (RPC) is a relatively new type of high-performance concrete, offering enhanced load-bearing capacity, mechanical strength, and durability. The enhanced microstructural density of RPC with the incorporation of reinforcing fibers significantly increases its resistance to durability challenges, particularly against external sulfate attack (ESA). However, conventional laboratory testing methods for evaluating the resistance of RPC to ESA are limited. Hence, a new performance-based approach was developed to evaluate the durability of RPC exposed to ESA. Expansion of nine RPC mixtures designed by Taguchi L9 orthogonal array method with four factors (steel fiber content, water-to-binder ratio (w/b), silica fume content, …

Performance And Economic Evaluation Of Asphalt-Based High Friction Surface Treatment (Hfst) Applications, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are recognized for enhancing friction between tires and road surfaces, with reduced road accidents being a key benefit. Epoxy-based HFSTs, though widely used, come with challenges like compatibility issues with existing pavements, higher installation and removal costs, and reduced durability tied to substrate quality. Recently, state agencies have increasingly focused on developing asphalt-based alternative binders for HFST applications as highlighted in the National Cooperative Highway Research Program (NCHRP) RFP #NCHRP 10-145. This study introduces asphalt-based HFSTs as an alternative to traditional epoxy-based treatments. Various aggregate types were examined for friction performance and the effect of …

Representing Structural Isomer Effects In A Coarse-Grain Model Of Poly(Ether Ketone Ketone), Chris D. Jones, Jenny W. Fothergill, Rainier Barrett, Lina N. Ghanbari, Nicholas R. Enos, Olivia Mcnair, Jeffrey Wiggins, Eric Jankowski

Boise State University Publications and Presentations

Carbon-fiber composites with thermoplastic matrices offer many processing and performance benefits in aerospace applications, but the long relaxation times of polymers make it difficult to predict how the structure of the matrix depends on its chemistry and how it was processed. Coarse-grained models of polymers can enable access to these long-time dynamics, but can have limited applicability outside the systems and state points that they are validated against. Here we develop and validate a minimal coarse-grained model of the aerospace thermoplastic poly(etherketoneketone) (PEKK). We use multistate iterative Boltzmann inversion to learn potentials with transferability across thermodynamic states relevant to PEKK …

Lesson 1: Seldm Introduction, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Lesson 2: Analyzing Seldm Results, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Pre And Post Student Self-Assessment Questions, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Lesson 2: Seldm Results Template, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Analyzing Micrometeoroid And Orbital Debris Shield Performance For Sample Return Spacecraft, William P. Schonberg, Michael Squire

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Sample-return missions typically seek to collect and return samples from extraterrestrial locations to Earth for analysis. The return of samples from certain locations in the solar system represents a potential hazard to Earth's biosphere from foreign microorganisms. One way this could occur would be a break-up of the returning capsule during entry (which would disperse the samples through the air) due to undetected damage to the capsule thermal protection system (TPS). As a result, missions that plan to return payloads from some destinations are likely to have certain design requirements for the TPS surrounding their returning capsules, which may include …

Lesson 1: Steps To Run Seldm Example - Student Version, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Lesson 2: Analyzing Seldm Results, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Class-Wise Histogram Matching-Based Domain Adaptation In Deep Learning-Based Bridge Element Segmentation, Tarutal Ghosh Mondal, Zhenhua Shi, Haibin Zhang, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study focused on the problem of domain shift in deep learning-based bridge element segmentation. The impracticability of accounting for all possible variabilities vis-à-vis structural shape, size, color, texture, illumination, and other operational conditions in the training process leads to the deterioration in the model performance when applied to test data from novel unseen domains. In such situations, rebuilding the model with labeled training data from the target domain becomes prohibitively expensive and time-consuming in many practical cases. Recent advancements in unsupervised domain adaptation techniques are known to provide viable solutions to this problem. However, it was observed in this …

Seldm Case Study Exercise: Download Instructions, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Lesson 1: Steps To Run Seldm Example - Instructor Version, Lillian C. Jeznach

University Workshop Materials for the Stochastic Empirical Loading and Dilution Model (SELDM)

No abstract provided.

Feasibility Study Of A Smart Insole With Triboelectric Energy Harvesters For Early Flatfoot Detection, Mohammad Alghamaz

Mechanical Engineering Theses

This study introduces a self-powered smart insole system designed for real-time monitoring of foot health, with a specific focus on detecting flatfoot conditions. The insole integrates multiple triboelectric energy harvesters strategically positioned to capture electrical signals generated from ground reaction forces during daily activities such as walking, jogging, and running. Proof-of-concept testing was conducted on a single participant under two conditions: a healthy foot and a simulated flatfoot created by reducing the medial arch height by approximately 70\. In the healthy foot trials, the system demonstrated consistent and reliable performance, with negligible electrical output from the medial arch sensor, as …

A Computational Fluid Dynamics Approach To Analyze The Virtual Impactor In Pneumatic Aerosol Jet Printing, Akashita Sareen

Theses, Dissertations and Capstones

Aerosol jet printing (AJP) is a 3D printing, advanced manufacturing process that generates an aerosol mist appropriate for fine printing small, low-volume electronic parts. The pneumatic aerosol jet printing technology’s virtual impactor is the focus of this study. In this technology, high velocity nitrogen gas aerosolizes various inks in the atomizer. The aerosolized stream of ink is then transported to a virtual impactor (VI) to become dense and concentrated as it begins to enter the deposition head for high precision electronics printing. AJP faces challenges in large-scale adoption due to challenges related to overspray, instability, ink clogging etc. There is …

Challenges In Numerical Simulation Of Frost Heave, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave of soil extensively exists in northern regions and poses a significant threat to infrastructure in cold regions. Despite over a century of research, challenges persist in numerically simulating frost heave. This study addresses two key issues: (1) What is the primary driving force for liquid water transfer during the freezing process? (2) How can we correctly represent unfrozen water content? Critical insights are derived from the theoretical analysis of coupled hydrothermal migration during soil freezing processes, followed by a case simulation using COMSOL Multiphysics. It concludes that of the water content gradient, suction gradient, and hydraulic gradient, only …

Using Preformed Particle Gels To Control Transport In Geothermal Reservoirs: Mathematical Modeling, Philip Winterfeld, Baojun Bai, Yu Shu Wu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

We are developing swellable Preformed Particle Gels (PPG), which can control preferential fluid and heat flow through fracture networks to increase the performance of EGS reservoirs. Part of this development is a mathematical model and numerical simulator to simulate PPG treatments by considering coupled thermal-hydraulic-mechanical effects, and gel swelling kinetics and plugging efficiency, from which an optimized gel treatment design and operation can be achieved. The starting point for our mathematical model is the TOUGH2-CSM formulation and code. The TOUGH2-CSM fluid and heat flow formulation is based on the TOUGH2 one for multiphase, multicomponent, and multi-porosity systems, with the latter …

Ai In Higher Ed, Where Are We Now?: Insights From The 2025 Educause Ai Landscape Study, Angela Neria, Jeff Burns

Posters

Curious about how higher education is really using AI? Wondering what’s next for AI policies, workforce impacts, and leadership strategies? The 2025 EDUCAUSE AI Landscape Study has the answers! Based on fresh data from institutions across higher ed, this study highlights key trends, challenges, and opportunities in AI adoption. Stop by our poster session to get a quick snapshot of where AI stands today—and where it’s headed. Let’s talk about what these findings mean for PSU and the future of AI in higher education!

“Science Belongs Everywhere”: Outlooks On Post-Secondary Stem Education For Correctional Centers In Virginia, Shelita R. Augustus

Division of Strategic Enrollment Management and Student Success Publications

Virginia has an incarceration rate of 679 per 100,000 residents, the highest among independent democratic nations. This scoping review examines perspectives on post-secondary STEM education to promote STEM education within Virginia's correctional facilities, assesses programs to improve rehabilitation, reduce recidivism, and address systemic inequalities by developing the scientific potential of incarcerated individuals. The review finds that while STEM education in correctional facilities faces limitations, its potential benefits are being realized nationwide. Virginia has made strides through initiatives like House Bill 2158, which aims to expand higher education access for incarcerated individuals. Examples such as the programs at J. Sargeant Reynolds …

A Systems-Based Framework For Product Circularity Assessment, Gisele Bortolaz Guedes, Junwon Ko, Fazleena Badurdeen, I. S. Jawahir, K. C. Morris, Vincenzo Ferrero

Mechanical Engineering Faculty Publications

One of the key aspects of Circular Economy (CE), particularly when focusing on the product level, lies in its emphasis on designing products to facilitate the circulation of resources and maximize value throughout their entire lifecycle. To effectively develop such products an understanding of the characteristics of circular products (CP) is needed. Adopting a systems perspective that considers the total lifecycle and stakeholders involved and recognizing interdependencies among them is essential for identifying factors that characterize CPs. Existing methods for assessing product circularity do not identify all factors that charac- terize CPs and have limitations in the measurement methods proposed, …

Explaining Deep Learning-Based Anomaly Detection In Energy Consumption Data By Focusing On Contextually Relevant Data, Mohammad Noorchenarboo, Katarina Grolinger

Electrical and Computer Engineering Publications

Detecting anomalies in energy consumption data is crucial for identifying energy waste, equipment malfunction, and overall, for ensuring efficient energy management. Machine learning, and specifically deep learning approaches, have been greatly successful in anomaly detection; however, they are black-box approaches that do not provide transparency or explanations. SHAP and its variants have been proposed to explain these models, but they suffer from high computational complexity (SHAP) or instability and inconsistency (e.g., Kernel SHAP). To address these challenges, this paper proposes an explainability approach for anomalies in energy consumption data that focuses on context-relevant information. The proposed approach leverages existing explainability …

Kolmogorov–Arnold Recurrent Network For Short Term Load Forecasting Across Diverse Consumers, Muhammad Umair Danish, Katarina Grolinger

Electrical and Computer Engineering Publications

Load forecasting plays a crucial role in energy management, directly impacting grid stability, operational efficiency, cost reduction, and environmental sustainability. Traditional Vanilla Recurrent Neural Networks (RNNs) face issues such as vanishing and exploding gradients, whereas sophisticated RNNs such as Long Short- Term Memory Networks (LSTMs) have shown considerable success in this domain. However, these models often struggle to accurately capture complex and sudden variations in energy consumption, and their applicability is typically limited to specific consumer types, such as offices or schools. To address these challenges, this paper proposes the Kolmogorov–Arnold Recurrent Network (KARN), a novel load forecasting approach that …

Leveraging Hypernetworks And Learnable Kernels For Consumer Energy Forecasting Across Diverse Consumer Types, Muhammad Umair Danish, Katarina Grolinger

Electrical and Computer Engineering Publications

Consumer energy forecasting is essential for managing energy consumption and planning, directly influencing operational efficiency, cost reduction, personalized energy management, and sustainability efforts. In recent years, deep learning techniques, especially LSTMs and transformers, have been greatly successful in the field of energy consumption forecasting. Nevertheless, these techniques have difficulties in capturing complex and sudden variations, and, moreover, they are commonly examined only on a specific type of consumer (e.g., only offices, only schools). Consequently, this paper proposes HyperEnergy, a consumer energy forecasting strategy that leverages hypernetworks for improved modeling of complex patterns applicable across a diversity of consumers. Hypernetwork is …