Thermocouple Temperature Measurements in Metalized Explosive Fireballs
Bibliographic record
Abstract
Abstract The detonation of a metalized explosive generates a fireball that has a spatially non‐uniform distribution of particle concentration and gas temperature. The transient gas temperature field must be probed with ruggedized spatially‐ and temporally‐resolved diagnostics. The use of in‐situ thermocouples for temperature measurements within multiphase fireballs is demonstrated. Although the thermocouple temperature lags behind the local gas temperature, the transient gas temperature is assessed by modeling the sensor assuming first‐order response and using two analysis methods: (1) when the thermocouple temperature trace reaches a local extrema, the thermocouple temperature is instantaneously equal to the local gas temperature, and (2) reconstructing the gas temperature trace using multiple co‐located thermocouples of different lag responses. The temperature history within the fireball at various distances is presented for charges consisting of packed beds of particles saturated with liquid nitromethane. The results for reactive particles (Al, Ti, Zr) are compared with non‐reactive particles (Fe), as well as homogeneous NM charges. For NM charges, a maximum gas temperature of about 1100 K occurs at times on the order of 100’s of milliseconds, less than the temperature of the burning soot in the fireball (∼1900 K). With Al particles, the gas temperature is spatially non‐uniform due to particle jetting and non‐uniform particle combustion, but gas temperatures up to about 1800 K are recorded for times up to 0.5 s, less than the temperature of the burning particles (∼2700 K). Inert particles act as a heat sink and the thermocouple temperatures recorded did not exceed 400 K.
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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".