Measurement and modelling of the fatigue life of rubber mounts for an automotive powertrain at high temperatures
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
A fatigue experiment is carried out on filled natural rubber specimens with two different Shore hardnesses (45 and 50) and three different temperatures (23 °C, 60 °C and 90 °C) under uniaxial tension loads. The measured fatigue life data obtained under different displacement loads are used to formulate fatigue life prediction models corresponding to different operating temperatures for the two hardnesses using the peak engineering strain as the damage parameter. The influences of the temperature, the stress softening at high temperatures and the hardness on the fatigue life of rubbers are measured and discussed. The proposed models are used to predict the fatigue life of a rubber mount for a powertrain mounting system. The validity of the prediction model is demonstrated by comparisons with the measured fatigue life data of the rubber mount at 90 °C. A method for determining the damage parameters required for predicting the fatigue life is presented on the basis of the finite element model of the rubber mount. The Mooney–Rivlin constitutive constants of the hyperelastic rubber material are identified on the basis of the measured data on the specimens. Comparisons of the measured and the estimated fatigue lives of the rubber mount at 90 °C revealed reasonably good agreement. The ratio of the predicted fatigue life to the measured fatigue life was within a factor of 2 under the range of loading conditions considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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