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CAED Shop Entrance Wall Redesign
Get PDFThis project involved the replacement and redesign of the north wall at the CAED Support Shop at Cal Poly, San Luis Obispo. The redesign aligned the wall with the adjacent Engineering West building. The original concrete wall was designed with jagged recesses to accommodate large trash bins. These recesses no longer serve their intended function due to the permanent relocation of these bins. The replacement CMU low lift grouted wall optimizes courtyard space, enhances aesthetic cohesion, and maintains architectural features consistent with the existing structure. The following report outlines the process necessary to complete this project, including the permitting process, structural design, and construction. It is a holistic project, which involves students from the university’s Architectural Engineering and Construction Management programs in each step of the process. The report covers existing condition documentation, permitting, design considerations, design documentation, construction, and the necessary communication and organization needed to allow the project to move forward
Genome-Wide Association and Metabolomic Studies for Fertility Traits in Dairy Cattle
No full textWhile milk production is a direct product of fertility, the two are negatively correlated. As reproductive inefficiency is a top cause of economic loss for the dairy industry, it is imperative to gain an understanding of molecular mechanisms controlling fertility traits in dairy cattle. This allows producers to select for high fertility while still maintaining a high milk yield. The goal of the first study was to identify significant single nucleotide polymorphisms (SNPs), genes, and biological pathways. The study revealed ten significant SNPs, six genes, and several biological pathways including the regulation of canonical Wnt signaling pathway (P \u3c 0.02), secondary metabolic process (P \u3c 9.5e-05), and cGMP metabolic process (P \u3c 7.8e-04). The objectives of the second study were to identify significant metabolites, biological processes and potential biomarkers. As a result, nine metabolites, four biological pathways, including purine metabolism, valine, leucine, and isoleucine biosynthesis, glycerophospholipid metabolism, and valine, leucine, and isoleucine degradation, and two potential biomarkers were determined. These biological mechanisms and candidate biomarkers may be used as management and selection tools to improve reproductive efficiency in dairy operations
Open Source Asic Design Curriculum
Get PDFThe ever-growing importance of Application-Specific Integrated Circuits (ASICs) in a high-compute world necessitates that college graduates entering the workforce are well prepared to design them. This thesis details the design of novel ASIC curriculum, using open source tools to teach at the undergraduate level. By moving to a higher level of abstraction than classical transistor-focused coursework, chip design material can be made accessible earlier in an undergraduate degree. Additionally, open source tools provide a powerful, free, and portable platform for students to create their own designs, solving assignments focused on industry readiness. Finally, this thesis studies the results and challenges of implementing this curriculum as a technical elective at Cal Poly San Luis Obispo
The Buzzard in the Abolitionist Sea; An examination of Maritime Suppression, Imperial Policy, and the Slave Trade through the Royal Navy’s HMS Buzzard, 1830s-1840s
Get PDFAnalysis of the Royal Navy through the microhistory of the HMS Buzzard following the abolition of the slave trade between 1807 and the 1840s by Great Britain offers insight into the moral ambiguities and complexities of the humanitarian mission. The historiography of the slave trade has primarily focused on the moral and economic ideology behind its abolition, pitting one against the other. Applying a micro-historic approach highlights the nuances of both arguments, and through the HMS Buzzard’s crew, captives, disease, voyages, and legal battles accentuates the blend of both argument approaches. The case study of its longevity through all six of its captains and their captures demonstrate the complexities of the mission, highlighting the ambiguities between moral and economic desire. The death of hundreds of enslaved Africans, the legal uphill conflict with foreign powers, and the Mixed Court of Commissions focus on monetary value contribute to a more nuanced analysis of the abolitionist mission and its applications to Britain’s new shifting imperial ideology. This work concludes that Royal Navy was only as successful as how you define it, and both sides of the abolitionist argument remain contextualized in the shadow of the lives lost across the Atlantic
A Fault-Tolerant, Multi-Heap Dynamic Memory Allocator For FreeRTOS
Get PDFThe use of dynamic memory allocation presents a significant challenge for embedded systems, particularly in applications that require high reliability. The software controlling these systems needs to perform critical operations within strict timing constraints, and memory management plays a critical role in a system’s ability to meet these constraints. Dynamic memory allocation is inherently non-deterministic: if a task requests memory, it is impossible to predict how long it will take for the memory to be allocated. If a critical task were to rely on dynamically allocated memory, its execution could become stalled leading to a missed deadline and system failure.
Due to the non-deterministic behavior of dynamic memory allocation, safety-critical or mission-critical tasks typically rely on static memory allocation, which is fully deterministic and more reliable. Dynamic memory allocation on these systems is reserved for non-critical tasks where a delay in memory allocation will not result in system failure. This strategy allows a system to take advantage of the benefits of dynamic memory allocation (such as reduced memory footprint), while containing potential memory-related failures to non-critical tasks. However, even failures in non-critical tasks can degrade overall system performance. Additionally, since dynamic memory allocators access and modify system memory, there remain ways for the memory allocator to inadvertently disrupt the operation of critical tasks. Therefore, dynamic memory allocators for the applications need to be as fault-tolerant and memory-safe as possible.
This thesis researches and implements a fault-tolerant, multi-heap dynamic memory allocator for the FreeRTOS real-time operating system. This memory allocator provides FreeRTOS new fault-tolerant robustness by implementing support for multiple heaps, along with additional protections to improve memory safety and prevent unpredictable behavior. This memory allocator isolates processes from one another and ensures more predictable behavior than the existing FreeRTOS dynamic allocator
Model-Based Design of Compressed Lithium-Metal Pouch Cell Battery Modules for eVTOL Applications
Get PDFBatteries with higher specific energy and power are essential for extending the range and performance of electric vertical takeoff and landing aircraft (eVTOLs). Anode-free lithium-metal pouch cells offer strong potential at the cell-level but require high compressive pressures to enhance cycle life and discharge performance. These pressures necessitate heavier structural components, reducing packaging efficiency at the module level.
To evaluate this tradeoff, a full-factorial enumeration model was developed to explore viable module designs within a constrained packaging volume. The model scales subsystem masses, enforces design rules and material limits, and accounts for large (~20%) cell thickness changes during cycling.
Results show that modules exceeding 300 Wh/kg and 1.5 kW/kg are achievable with commercially available lithium-metal cells. The study also recommends cell shape optimizations to further improve packaging efficiency. Despite simplifying assumptions, the model provides a practical tool for rapidly identifying optimal packaging strategies and supports the feasibility of these batteries for eVTOL applications
Thermal Modeling Techniques for Additively Manufactured Porous Metals
Get PDFAdvances in additive manufacturing have enabled the creation of metallic components with tailored porosity, offering design flexibility for thermal, structural, and fluid transport applications. This thesis investigates the effective thermal conductivity (ETC) of porous Inconel 625 (IN625) and Inconel-ceramic composites (IN625-RAM2) fabricated by Laser Powder Bed Fusion (LPBF) using Elementum 3D’s PermiAM technology. Experimental measurements of thermal conductivity using the laser flash method are compared to numerical models built from micro-computed tomography data. Simulations were performed using both finite element (FE) and finite volume (FV) methods to evaluate thermal transport in real microstructures. The study investigates the effects of micro- and macro-scale structural features on ETC and shows that voxel-based FV modeling in PuMA can predict ETC within 3% of experimental values. Analytical models are also fit to experimental data to extend ETC predictions across a wider range of porosities. This work provides a framework for simulating the thermal performance of complex porous metals and supports future materials-by-design approaches targeting specific thermal properties in additively manufactured structures
Expanded Polystyrene and Terpene Resin Tackifier Dispersions to be Used in Natural Rubber Latex Pressure Sensitive Adhesives
No full textExpanded polystyrene (EPS) poses a significant environmental danger due to its low recyclability and lack of reuse cases. Thanks to ITW – Global Tire Repair’s sponsorship, this study investigates the formulation, performance, and composition of three distinct levels of EPS tackifying dispersions including 0.7 wt%, 3.4 wt%, and 6.0 wt% EPS through peel testing, puncture testing, topographical analysis, and FTIR. Through the information gathered in this report, a new incentive for EPS recycling may be discovered
TopoDINO: Self-Supervised Topological Representation Learning for Neuronal Morphologies
Get PDFNeuronal cell types are categorized by transcriptomic identity, yet their morphological heterogeneity defies this classification. In response, researchers have adopted unsupervised graph representation learning as a tool to reveal morphological variation within single-class transcriptomic types. However, the complex geometry of neuronal morphology—especially long axons and dense dendrites—challenges graph neural networks, which struggle with message propagation across extended structures. To mitigate this, current approaches enforce sub-sampling on neuronal graphs and omit axons entirely, sacrificing critical biological features for computational efficiency. To overcome this trade-off, this thesis introduces TopoDINO, a self-supervised, topology-aware representation learning model designed to preserve the full hierarchical organization of neuronal morphology. Instead of relying on subsampled graph approximations, TopoDINO employs a novel topology-lifting approach that transforms neuronal graphs into combinatorial complexes, capturing the inherent hierarchical features of neurons. In addition, we pre-train TopoDINO on the SEU-D15K dataset. As a result, TopoDINO not only provides a biologically grounded embedding space by preserving neuronal compartmentalization, but also mitigates labeling inconsistencies across laboratories by learning in a fully data-driven manner from 12,353 dendritic reconstructions derived from 204 mouse brains, all registered to the Allen Mouse Common Coordinate Framework (CCF)
A Biologically Inspired Solution to Dynamic Multi-Agent Path Planning and Task Allocation for Underwater Autonomous Vehicles
No full textThis thesis presents a biologically inspired multi-agent control system for real-time path planning and task allocation in a dynamic and obstacle-laden underwater environment, specifically for teams of Autonomous Underwater Vehicles (AUVs). Traditional methods including classical heuristic algorithms and AI-based approaches often fail to effectively adapt to dynamic environments or require trained policies for each specific task space. To address these issues, this work proposes an approach that integrates Glasius Bio-Inspired Neural Networks (GBNNs) and a Collaborative Discrete Artificial Bee Colony (CDABC) algorithm, along with a ”gradient-of-neighbors” path planning algorithm based on local neural activity gradients, to produce smoother and more efficient trajectories and task assignments that adapt in real time to changing environments.
Simulation results with ten different random environments demonstrate that the new multi-agent control system policies significantly reduce mission completion time — achieving average improvements of 65.1% as compared to conventional GBNN-based systems, with a trade-off of increased average travel distance of 19.5%. More tests with more realistic environments will be performed to fully evaluate the performance of the proposed approach