Application of Coupled Structural Acoustic Analysis and Sensitivity Calculations to a Tire Noise Problem
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
Abstract REFERENCE: H. M. R. Aboutorabi and L. Kung, “Application of Coupled Structural Acoustic Analysis and Sensitivity Calculations to a Tire Noise Problem,” Tire Science and Technology , TSTCA, Vol. 40, No. 1, January – March 2012, pp. 25–41. ABSTRACT: Tire qualification for an original equipment (OE) program consists of several rounds of submissions by the tire manufacturer for evaluation by the vehicle manufacturer. Tires are evaluated both subjectively, where the tire performance is rated by an expert driver, and objectively, where sensors and testing instruments are used to measure the tire performance. At the end of each round of testing the evaluation results are shared and requirements for performance improvement for the next round are communicated with the tire manufacturer. As building and testing is both expensive and time consuming predictive modeling and simulation analysis that can be applied to the performance of the tire is of great interest and value. This paper presents an application of finite element analysis (FEA) modeling along with experimental verification to solve tire noise objections at certain frequencies raised by an original equipment manufacturer (OEM) account. Coupled structural-acoustic analysis method was used to find modal characteristics of the tire at the objectionable frequencies. Sensitivity calculations were then carried out to evaluate the strength of contribution from each tire component to the identified modes. Based on these findings changes to the construction were proposed and implemented that addressed the noise issue.
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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 | 0.002 |
| 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