Thermal Analysis and Optimization of a Disc Brake Rotor for a Formula SAE Race Car
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Bibliographic record
Abstract
Society of Automotive Engineers (SAE) is organizingFormula SAE (FSAE) competitions considering university students since 1981 targeting development of students via designing, manufacturing and racing with one-seated open wheeled race cars.The brake system plays a crucial role as a major component in designing a one-seated race vehicle for FSAE student competition.To avoid failures from brake fade and thermal stress, car brakes must not only be robust enough to withstand extreme mechanical loads but also dissipate the heat generated during braking in order to prevent the temperature breach the Maximum Design Temperature (MDT) limit.Additionally, the weight of the brake disc rotors plays a crucial role in the overall weight and of course performance of the vehicle.The methodological analysis, in order to determine a disc brake rotor's temperature profile under sporadic loads during consecutive braking and acceleration/cruise events considering a race, is presented in this work.OptimumLap software is used to determine a time-dependent vehicle speed and braking intensity profile for the 2019 Formula SAE competition Michigan endurance track and default Formula SAE vehicle configuration in OptimumLap software.The temperature distribution of the bicycle brake disc rotor during a sequence of successive braking and acceleration/cruise events across 2 laps is simulated using "SolidWorks" thermal analysis.Thermal simulations are continued until the temperature difference between consecutive laps is less than 10 K.A total of 106 thermal simulations were performed where the maximum temperature of the disc rotor is simulated as 1713 K which is above the MDT and the consecutive simulation are replaced with a single simulation maintaining the maximum simulation temperature via modifying thermal simulation input parameters.A DOE based optimization is carried using the single simulation method and the maximum temperature is reduced below the MDT limit.This study examines a practical approach for Formula SAE racing car disc brake temperature profile analysis and optimization.
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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