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Record W2048810589 · doi:10.13031/2013.22085

Development of a Mechanical Device for Landmine Neutralization

2006· article· en· W2048810589 on OpenAlexaboutno aff
T.L. BURTON, R. L. Kushwaha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsDeflection (physics)Computer scienceMechanical designSimulationEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The use of mechanical devices such as chain flails for landmine neutralization and/or area reduction has the potential of greatly aiding landmine clearance. However, mechanical clearance methods have not been fully accepted in the landmine clearance community due to a lack of knowledge and scientific data concerning the actual soil-tool interaction and the landmine clearance effectiveness. The research objective was to develop a mechanical device that will deliver sufficient force to produce adequate ground deflection for detonating typical antipersonnel landmines at depths up to 200 mm. Other design parameters included design simplicity, high durability with low and ease of maintenance and flexible operation. A design matrix was employed to select an appropriate design for further analysis, resulting in preliminary testing and evaluation of a Tamper and Jackhammer. It was concluded that a tamper design resulted in superior demining capabilities. A final testing phase was designed on further evaluation of the demining effectiveness of the tamper and to determine optimal operational parameters between two shoe sizes and the number of pass applications. Tests were conducted using the Terra Mechanics Rig facility at the University of Saskatchewan. The results revealed that the small tamper shoe configuration performed better than that of the large shoe, but only marginally. Results also indicated the optimal application was two passes. It was concluded that the optimal shoe configuration would be associated with the demining environment where the device would be used.

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: Methods · Consensus signal: none
Teacher disagreement score0.785
Threshold uncertainty score0.112

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.031
GPT teacher head0.278
Teacher spread0.247 · 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
GenreMethods

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

Citations0
Published2006
Admission routes1
Has abstractyes

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