MétaCan
Menu
Back to cohort
Record W1492368535 · doi:10.21236/ada450471

Comparison of Explosives Residues from the Blow-in-Place Detonation of 155-mm High-Explosive Projectiles

2006· report· en· W1492368535 on OpenAlexaff
Michael R. Walsh, Marianne E. Walsh, Guy Ampleman, Sonia Thiboutot, Deborah D. Walker

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsDefence Research and Development Canada
FundersCold Regions Research and Engineering LaboratoryU.S. Army Corps of EngineersStrategic Environmental Research and Development Program
KeywordsExplosive materialDetonationProjectileMaterials scienceChemistryMetallurgy

Abstract

fetched live from OpenAlex

The disposal of unexploded ordnance is a potential source of explosives residues on ranges. Blow-in-place detonation of munitions currently is done to clear these areas for safety without an emphasis on the consumption of the explosive load. The general testing method is to detonate the horizontal fuzed projectile with one block of C4 explosive. Explosives residues from blow-in-place disposal were examined using several different detonation configurations. Seven 155-mm fuzed high-explosive projectiles were detonated on a snow-and-ice-covered range on Fort Richardson, Alaska, to obtain baseline data on the current testing method. Tests were then conducted using the same type of projectiles in three configurations: fuzed rounds vertically oriented, fuzed rounds horizontally oriented with two donor charges, and a non-fuzed horizontal round with one donor charge. Recovered energetic residues indicate explosive load consumption in excess of 99.998% for all tests, ranging from 12 to 62 mg per round. This compares to 0.31 mg per round for live-fire detonation of the same-type rounds. Although two orders of magnitude higher, residue quantities for proper blow-in-place detonation of these munitions are quite small and are unlikely to result in significant explosives residues on ranges when compared to low-order or unaddressed unexploded ordnance.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.310
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicCombustion and Detonation ProcessesFrench-language works237,207