High-speed infrared thermography for measuring flash temperatures in sheared fault gouge analogues
Bibliographic record
Abstract
Abstract. Flash temperatures induced by flash heating can lead to thermal softening or decomposition of fault-zone materials at microscopic grain contacts and, consequently, cause a rapid reduction in fault strength during seismic slip. To quantify the efficiency of short-term frictional heating at the contact scales and its impact on the mechanical fault strength, we conducted rotary-shear friction experiments on Ottawa quartz sand “gouges” with variable grain sizes of 250–710 µm at a range of normal stresses of 1–7.5 MPa and slip velocities of 1–50 mm s−1 under room-dry and wet conditions. We employed a high-speed infrared camera to monitor temperature fluctuations along the outer circumference of the ring-shaped gouge layer during sliding, utilizing a frame rate of up to 1200 Hz with a spatial resolution of 15 µm to capture flash temperature occurring at asperity contacts. We show that flash temperature can be captured within the gouge layer in both room-dry and wet conditions with a peak value up to ∼ 220 and ∼ 100 °C, respectively. In addition, the flash temperature increases with increasing slip velocity and grain size, while decreasing at higher normal stress, which is likely associated with enhanced grain size reduction. In our study, we showed that flash temperatures in shearing fault gouges can be constrained using a fast thermal camera. Although difficulties remain in the experimental set-up related to the need to confine the gouge layer and to the evolution of contact size due grain size reductions, the trends in maximum temperatures we observed agree with those predicted from theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".