Lump System Analysis Modelling for Enhanced Ballistic Performance of Clay Box Doped with Different Types of Additives
Bibliographic record
Abstract
The temperature of clay box used in the ballistic testing of body amour drops sharply upon removal from the oven. This implies that the clay has to be reinserted into the oven for another heating, which slows down the ballistic testing procedure. This paper attempts to solve the problem by studying the effect of addition of different percentages of rubber cuttings, saw dust and berley reeds additives on the cooling rate of clay used in clay box construction. The cooling rate is a measure of the ballistic performance of the clay box. The properties of the clay box such as the density, thermal conductivity and specific heat capacity are factored into the lump system analysis model. Minimum cooling rate of about 2.04×10-03 and 1.89×10-03oC/s were obtained when 0% and 10% rubber cuttings were used as dopands respectively. Rubber cuttings also proved to be the best additives that can be used to enhance the ballistic performance of clay box used in the ballistic testing of body armour.
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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 | 0.004 | 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 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".