41530 research outputs found
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Developing Practical CFD Skills for Undergraduate Researchers
No full textAs the use of computational fluid dynamics (CFD) grows in the aerospace (and other engineering disciplines), the need for coursework, and in particular labs, that develop the appropriate CFD skills is growing. In the semester transition, the Aerospace Engineering Department will be offering an applied computational aerodynamics class that will have a heavy emphasis on practical CFD applications to realistic problems to be encountered by our students. This research activity will help develop labs that will be used to teach students how to use StarCCM+ (the department’s current commercial CFD tool) starting from simple geometries going up to complete airframes. The student(s) participating in this effort will not only gain insight on how to perform these types of analyses, they will also develop skills on how to systematically grow the complexity of an instructional activity so that the end product is a curriculum that provides a practical skill-set in applied CFD
How students’ geographical area influences their level of interest in engineering after participating in the EPIC program
No full textThe purpose of this study was to look at how a student’s location can shape their interest in engineering after taking part in the EPIC program. My research question asked: How do students’ geographical area influences their level of interest in engineering after participating in EPIC? To answer this, I compared students from different income groups: higher, middle, and lower, which was determined by using ZIP code data tied to average income and education levels. I also did a closer look at students from the Santa Maria region. Many of these students were connected to the Migrant Education Program, which serves first-generation and low-income students who may not have the same access to resources as their peers in EPIC. The EPIC program reserves seats for these students so they can gain hands-on STEM experiences and see engineering as a possible path for their future. By comparing pre- and post-survey responses, the study aimed to show not just overall changes in interest, but also how each students’ regions can shape the way they engage with their interest in engineering opportunities. My goal was to highlight how a student’s environment can influence their exposure to engineering and whether programs like EPIC can help close that gap
Integrating Mobility Dynamics into Facility Location Modeling and Optimization
No full textFacility location optimization is a foundational area in operations research and data analytics that is concerned with determining the optimal placement of facilities to serve a spatially distributed demand. However, traditional facility location decision is often approached from a centralized perspective, where the facility planner dictates the allocation of customers to facilities. In this setting, it is typically assumed that customers patronize the nearest facility, and their preferences are not explicitly modeled. This traditional decision-making framework may not accurately reflect real-world dynamics where customers may choose facilities based on a variety of factors beyond proximity. Thus, this project aims to develop a novel decentralized decision-making framework for facility location modeling that explicitly considers people\u27s actual mobility patterns and behavioral preferences. By accounting for people\u27s nuanced mobility patterns in facility location optimization, the decentralized facility location model can provide more realistic and precise decision support for stakeholders, such as city planners and policy makers, with the goal of improving access to essential services. Ultimately, this project offers unique opportunities to leverage real human mobility data in the development of a data-driven, optimization-based framework for facility location problems
Computational Investigation of the Role of 3D Genome Architecture in the Lifecycle of the Malaria Parasite
No full textMalaria, a mosquito-borne infectious disease caused by the Plasmodium parasite, is responsible for more than a half a million deaths per year, the vast majority of which occur in central Africa. The parasite undergoes an incredibly complex cell molecular transformation as it transitions from living in mosquitoes to living in humans with different sets of genes being activated or silenced in order to evade the immune system of the host. Understanding how its genome guides this transition is critical for developing adequate treatments. In this project, we aim to develop a computational framework for investigating the role of the three dimensional (3D) DNA architecture in enabling the expression of virulence genes. We use recently and newly acquired data of DNA-DNA and long non-coding RNA-DNA interactions to create a genome interaction map. We plan to employ a diffusion kernel algorithm to highlight clusters of interacting virulence genes and computationally build a background model to statistically assess the importance of lncRNAs. Our work lays the foundations for further systematic analyses of changes in 3D parasite genome conformation during its complex lifecycle
DeepSeek, ChatGPT, or Gemini? A Multi-Method Investigation of Neural and Behavioral User Experience (UX)
No full textAs artificial intelligence tools become integral to everyday tasks, understanding how users interact with these systems is essential for improving user experience and system design. This research aims to investigate and compare the interface usability and emotional responses elicited by three prominent AI tools—ChatGPT, DeepSeek, and Google Gemini—using the Emotiv Insight EEG headset. By combining usability testing with emotional biometrics, this study offers a novel approach to evaluating conversational AI systems. The study will capture both subjective usability metrics and objective emotional markers such as arousal, valence, and engagement. Participants will complete standardized tasks using each AI tool, while their EEG data is recorded. A follow-up usability questionnaire (e.g., SUS or UEQ+) will assess perceived interface quality. The goal is to identify which AI system provides the most user-friendly and emotionally positive interaction, contributing to the development of emotionally adaptive AI interfaces
Deterministic Motion Planning for Highly Articulated Multi-Link Robots
No full textSlender, multi-link, highly articulated, and extensible robots designed for minimally invasive surgeries have the potential to significantly transform the performance of common medical procedures. These advanced robots can reduce uncertainties and risks associated with surgeries, leading to shorter patient recovery times, accelerated healing, and minimized scarring. Made possible by their numerous mechanical linkages and concentric mechanisms, these multi-link articulated robots can navigate along non-linear paths, a capability that traditional straight probes lack. This flexibility allows surgeons to perform minimally invasive procedures on clinically significant targets that were previously difficult or impossible to access while avoiding vital anatomical structures. Beyond their applications in medicine, the potential uses of these robots span various fields that may require non-linear trajectories and navigation to reach difficult-to-access targets. However, manually controlling such devices can be quite unintuitive due to the various kinematic constraints involved, highlighting the need for automatic planning methods. To fully harness the capabilities of these multi-link robots, automation is key. For any automated medical procedure to gain acceptance in clinical settings, it is crucial -- from the perspectives of patient care, safety, and regulatory compliance -- to certify the accuracy and effectiveness of the motion-planning algorithms used in the automation process. In this context, our proposed study will focus on developing accurate and efficient motion planners specifically for extensible snake-like robots. We will model the articulated motion of these robots using a recursively defined trajectory consisting of: i) Base step: Inserting a link into the workspace. ii) Recursive step: Extending the end link by a given distance and rotating the new extension. The goal is to guide the endpoint of the last link to a target point within the workspace while avoiding obstacles. Our study will center on two main research questions: 1) (Completeness) Can we devise a time- and space-efficient deterministic algorithm for computing a feasible trajectory when one exists? 2) (Optimality) Can we also ensure that the computed trajectory is optimal with respect to specific objectives, such as minimizing trajectory length and maximizing clearance from obstacles? Our goal is to create a deterministic motion planner that provides formal guarantees of both completeness and optimality. This planner should be capable of finding a solution in a finite number of steps for any given scenario while ensuring that the solution meets a desired cost metric
Asphalt Rubber Chip Seals a Cost Effective and Sustainable Solution for Road Infrastructure
Full text linkAsphalt Rubber Chip Seals provide a durable, cost effective, and environmentally friendly alternative to traditional paving methods by incorporating recycled waste tires. This study evaluates Asphalt Rubber Chip Seals implementation in Arizona and Michigan comparing its effectiveness to conventional paving approaches and the current applications in California. Variations in state funding for road maintenance significantly impact infrastructure quality and longevity, influencing the choice of paving solutions. ARCS has demonstrated resilience in extreme weather conditions, making it a viable option for expansion to states like Arizona and Michigan, where climate variations pose challenges for pavement longevity. The research assesses construction costs, maintenance frequency, and sustainability benefits to determine ARCS’ competitiveness in the road maintenance industry. Findings suggest that ARCS reduces construction costs, accelerates application timelines, and provides substantial environmental advantages by diverting waste tires from landfills and reducing reliance on virgin materials. Additionally, ARCS enhances pavement flexibility, minimizing cracking and increasing roadway lifespan. By lowering maintenance demands and improving durability, ARCS offers a sustainable and economically viable solution for infrastructure development. Its demonstrated success in warm climates and ongoing research in colder regions highlights its potential for broader adoption across diverse environmental conditions, reinforcing its role as an innovative approach to modern road maintenance and rehabilitation
