A Multi-objective Optimization Approach for Automotive Disc Brakes: Integrating Castability, Strength, and NVH
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Brake squeal in automotive disc brakes remains a significant quality challenge. This issue is further complicated by design requirements for weight reduction, strength, and manufacturability, which often are conflicting; addressing these factors individually in the current process has led to development rework. In this study, a multi-objective optimization method that accounts for brake squeal in the early design stage was established, targeting objectives related to structural strength and stiffness, noise and vibration and harshness (NVH), and castability. Although castability evaluation typically relies on large-scale fluid dynamic analyses, a heat transfer analysis was introduced from an analogical perspective to enhance efficiency. Furthermore, since brake squeal is a bifurcation phenomenon exhibiting discrete characteristics, an evolutionary algorithm (an AI-based optimal solution search method) was employed.
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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 it