Adjoint-Based Shape Optimization Of Fin Geometry Using An Isothermal Streamwise Periodic Flow Solver
Bibliographic record
Abstract
The optimal design of heat exchanges is critical for a wide range of existing and emerging technologies.Traditional design methods often use experimental correlations to estimate thermal and hydraulic performance.However, CFD-based design methods have recently evolved as an alternative to these conventional methods.This paper proposes a CFD-based shape optimization method to design a two-dimensional representation of cylindrical fins.The method consists of a CAD-based parametrization tool and uses a streamwise periodic flow solver to estimate the performance of the fins.In addition, to enable gradient-based optimization, the sensitivity of the objective function with respect to the design variables is provided to the optimizer through an adjoint-based method.The proposed shape optimization method was applied to design cylindrical fins operating at laminar and turbulent flow regimes.The optimization results show that the fluid dynamic performance of the fins increased by 16.5% for the laminar case and 35.8% for the turbulent case while maintaining their thermal performance to their baseline values.
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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 | 0.000 |
| 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".