Mountain Scholar

Mountain Scholar is an open access repository service that collects, preserves, and provides access to digitized library collections and other scholarly and creative works from Colorado State University and the University Press of Colorado. It also serves as a dark archive for the Open Textbook Library.

Communities in Mountain Scholar

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Colorado State University, Fort Collins 28286
Explore the Colorado State University community’s scholarly output as well as items from the University at large and the CSU Libraries.
Open Textbook Library Archive 25
A limited number of titles are available here. To see all OTL titles, please visit the Open Textbook Library at https://open.umn.edu/opentextbooks. Only Open Textbook Library staff have access to all OTL Archive titles held in Mountain Scholar.
University Press of Colorado 1088
Access is limited to University Press of Colorado members. Non-members: to purchase books, please visit https://upcolorado.com/.

Recent Submissions

Access status: Open Access ,
From scaling laws to agentic grounding: a survey of emerging reliability risks in large language models
(2026-05-19) Ford, Jason, author
As the artificial intelligence industry exhausts high-quality, human-generated datasets, the shift toward recursive training on synthetic outputs has introduced significant systemic instabilities. This paper analyzes the compounding risks of model collapse and functional incoherence as failure modes that can result in the irreversible erosion of data diversity and model stability. The results of this analysis are an urgent call to both industry and the research community to recognize that current scaling laws are insufficient for resolving these defects, as increased compute may actually broaden the surface area for incoherent execution. To address these vulnerabilities, a transition toward agentic architectures is proposed that implements non-machine learning constraints as a way to ground model outputs. By integrating structural anchors like state-based persistence and parallel consensus loops, these frameworks provide a deterministic foundation for maintaining logical consistency in high-consequence environments. This research suggests that the path to sustainable, trustworthy AI lies in moving beyond purely probabilistic scaling toward verifiable, context-dependent reliability.
Access status: Open Access ,
Senior design project: galaxy clamp bike rack
(2026-05) Nakasone, Jayse, author; Roberts, Bonnie, advisor; Knaus, Pamela Vaughn, committee member
Cycling is popular worldwide for recreation and transportation. Bike racks, especially those mounted on personal vehicles, allow people to take their bikes farther for recreation. However, the bike racks currently on the market skimp on securing the rear tire, relying only on a flexible plastic ratcheting strap, which is vulnerable to theft targeting the rear wheel. A survey conducted by our team confirms that many cyclists are uncomfortable leaving their bikes unattended on these vehicle-mounted bike racks. Our senior design team’s goal is to improve durability and integrate a locking mechanism into the rear part of a bike rack. Our project sponsor, a patent attorney based in Colorado, intends to patent our design and then approach established bike rack manufacturers such as Thule, Yakima, and Küat. He plans to offer licenses for the patented design, enabling manufacturers to legally incorporate our innovation into their future products. Using the engineering design process, our four-person team clarified sponsor requirements, researched the market, and established design objectives. We adapted our design to an up-to-date hitch-mounted bike rack from Thule. After brainstorming alternatives to the flexible strap, the team decided on a handcuff-inspired design and iterated through CAD models and low-cost rapid prototyping. To create a more production-ready prototype, our team decided to laser-cut steel parts and outsource the plastic parts to be manufactured via SLS 3D printing. Finally, we tested our design by fitting multiple bike types that the team owned and applying a vertical pulling force on the mechanism. Our bike rack with the redesigned rear mechanism met most of our design requirements. The final prototype was able to withstand a vertical pulling force of 150 pounds, exceeding our target of 100 pounds. The bike rack continues to accommodate road and mountain bikes. An improved vehicle-mounted bike rack encourages more people to use their bikes for commuting or recreational purposes. Studies have shown that bicycles have health and environmental benefits. Cycling produces zero tailpipe emissions, which reduces pollution in cities and lowers greenhouse gases in the atmosphere that contribute to climate change.
Access status: Open Access ,
Human-AI teaming for water quality documentation analysis with large language models
(2025-06) Conrad, S., author; Rodriguez, J., author; Vizarreta Luna, G., author
Water quality management in urban systems depends on extensive documentation, including laboratory reports, field observations, regulatory guidance, and operational records. Manual analysis of these textual sources is time-intensive, inconsistent across reviewers, and often limited by workforce capacity. This study evaluates the use of large language models (LLMs) as part of a human-AI teaming workflow for identifying water quality concerns in documentation. Twenty water quality field and test documents were manually coded for concerns such as corrosion, pollutants, and chemical imbalances, then analyzed using OpenAI's GPT-4o, GPT-4o-mini, and o1-mini models. The models were tested using chunked document inputs and compared under open-text and localized prompting strategies that incorporated standard operating procedures and utility-specific water quality definitions. Performance was assessed using percent agreement, accuracy, precision, recall, and Fleiss’ Kappa. Results showed that localized chunked data improved model accuracy, agreement across iterations, and true positive identification compared with open-text prompting. The findings suggest that LLM-assisted document analysis can reduce interpretive workload, support more consistent review, and help water managers access previously underexamined textual data. Human-AI teaming offers a promising approach for improving the efficiency and reliability of water quality documentation analysis in urban water management.
Access status: Open Access ,
Adaptive hydrologic modeling approaches for optimizing water infrastructure design and management under nonstationarity
(2025-06) Hunu, K., author; Conrad, S., author
Traditional hydrologic design often assumes stationary climate conditions, limiting its ability to address changing precipitation patterns, evolving land use, and competing basin objectives such as water supply, recreation, energy production, and environmental flows. This study presents an adaptive hydrologic modeling approach for water infrastructure design and management under nonstationary conditions. The framework is demonstrated through a case study of the Buckhorn Creek Basin in North Carolina, a multi-use basin that includes key infrastructure such as Shearon Harris Lake, Sharon Harris Dam, and Buckhorn Dam. The methodology involved collecting terrain, land cover, soils, rainfall, infrastructure, and observed hydrologic data; developing future rainfall inputs from downscaled General Circulation Model projections; and building a two-dimensional HEC-RAS model to simulate basin conditions. Results comparing traditional and adaptive approaches show that the traditional method failed to meet several basin needs under future wet and dry scenarios, particularly for water supply, recreation, and environmental flows. In contrast, the adaptive approach satisfied basin requirements across all tested scenarios. The findings demonstrate that regularly updated hydrologic modeling, supported by revised climate projections and changing stakeholder priorities, can improve infrastructure decision-making and support resilient water management under uncertainty.
Access status: Open Access ,
Bridging the financial literacy gap: designing an educational unit on personal finance
(2026-05) Kessler, Sabrina. author; Luchs-Nunez, Jenny, advisor; Stekelberg, James, committee member
Financial literacy is a critical skill that influences individuals’ ability to make informed financial decisions and maintain long-term economic stability. This paper examines the importance of financial literacy, the consequences of low financial knowledge, and the effectiveness of school-based financial education programs. Drawing on existing research in personal finance and education, including studies on financial behavior, credit outcomes, and financial capabilities, this paper highlights how financial education improves both financial knowledge and real-world financial behaviors, like saving, borrowing, and credit management. Evidence suggests that structured financial education at the high school level can lead to measurable improvements in credit outcomes and long-term financial health. This paper explores effective instructional methods for teaching personal finance. Research indicates that experiential learning, real-world application, and student focused instruction are essential for developing both financial competence and confidence in applying financial concepts. Strategies such as simulations, collaborative activities, and applied financial tasks help students develop practical skills and confidence in decision-making. The paper presents a comprehensive semester long high school financial literacy unit aligned with the Colorado Academic Standards. The unit emphasizes progressive skill development, multiple forms of assessment, including a summative project that requires students to apply financial concepts in a realistic scenario. This paper argues that integrating structured, applied financial literacy education into high school curriculum is an effective approach to preparing students for real-world financial responsibilities and promoting long-term financial capability.