Energetics of glass fragmentation: Experiments on synthetic and natural glasses
Bibliographic record
Abstract
Natural silicate glasses are an essential component of many volcanic rock types including coherent and pyroclastic rocks; they span a wide range of compositions, occur in diverse environments, and form under a variety of pressure‐temperature conditions. In subsurface volcanic environments (e.g., conduits and feeders), melts intersect the thermodynamically defined glass transition temperature to form glasses at elevated confining pressures and under differential stresses. We present a series of room temperature experiments designed to explore the fundamental mechanical and fragmentation behavior of natural (obsidian) and synthetic glasses (Pyrex™) under confining pressures of 0.1–100 MPa. In each experiment, glass cores are driven to brittle failure under compressive triaxial stress. Analysis of the load‐displacement response curves is used to quantify the storage of energy in samples prior to failure, the (brittle) release of elastic energy at failure, and the residual energy stored in the post‐failure material. We then establish a relationship between the energy density within the sample at failure and the grain‐size distributions ( D ‐values) of the experimental products. The relationship between D‐values and energy density for compressive fragmentation is significantly different from relationships established by previous workers for decompressive fragmentation. Compressive fragmentation is found to have lower fragmentation efficiency than fragmentation through decompression (i.e., a smaller change in D‐value with increasing energy density). We further show that the stress storage capacity of natural glasses can be enhanced (approaching synthetic glasses) through heat treatment.
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How this classification was reachedexpand
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) | 0.003 | 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 teacher head, 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".