An Analytical Solution to Predict Temperatures of Dumbbell-Shaped Rubber Specimens Under Cyclic Deformation
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 The objective of this study is to propose an analytical solution that can predict the temperatures of dumbbell-shaped rubber specimens under cyclic deformation. Initially, a new mathematical equation was formulated by modifying the Mooney–Rivlin strain energy function, using the pseudo-elasticity theory and the inverse analysis method. This equation was utilized to calculate the internal heat generation rates of rubber compounds. With heat generation rates, the governing equation of heat conduction and the mathematical expression of boundary conditions were created to describe the heat transfer that occurs within the rubber compounds. By having these equations, a novel analytical solution was developed—the RTDS solution (a solution to predict Rubber Temperatures in Dumbbell-shaped Specimens). This RTDS solution was used to predict rubber temperatures in dumbbell-shaped specimens under cyclic deformation. The results showed that the RTDS solution took 11.9 s to derive the rubber temperature results with an average mean absolute percent error (MAPE) of 9.2% compared with lab recordings. The RTDS solution identified a logarithmic increase in rubber temperatures at rising strain levels, and it also identified an increase in rubber temperatures with the rising strain rates. According to the RTDS solution, there was an inverse correlation between the increases in rubber temperature and the ambient temperatures.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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