Design, Modeling, and Computational Fluid Dynamics (CFD) Analysis of an Autonomous Underwater Vehicle (AUV)
Bibliographic record
Abstract
This study comprehensively addresses the design and modeling processes of autonomous underwater vehicles (AUVs). The research examines the fundamental design principles that affect underwater vehicle performance, focusing on factors such as hydrodynamic efficiency, structural durability, buoyancy control, and stability. Considering the harsh marine environment, the selection of materials was thoroughly discussed based on criteria such as mechanical properties, corrosion resistance, and weight optimization. The production stages, from 3D modeling to manufacturing, were explained step by step. Engineering challenges encountered during the design process—such as waterproofing, stability, and balance—were emphasized, and solution approaches to these problems were presented. Computational Fluid Dynamics (CFD) analyses were employed to evaluate the hydrodynamic performance of the vehicle and to optimize the body geometry. Finally, based on the analysis results and design iterations, solution strategies and development suggestions were proposed, aiming to guide future studies in the development of autonomous underwater vehicles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".