MétaCan
Menu
Back to cohort
Record W2945510662 · doi:10.1139/tcsme-2018-0225

An experimental study on wearing of conical picks interacting with rock

2019· article· en· W2945510662 on OpenAlexvenueno aff
Qiuxia Fan, Qianqian Zhang, Guirong Liu, Xin Li, Wei Jia, Zhi‐wei Guo, Rui‐Min Han

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsnot available
FundersShanxi UniversityCommonwealth Scientific and Industrial Research Organisation
KeywordsConical surfaceWear resistanceCoatingMaterials scienceCemented carbideComposite materialStructural engineeringCarbideEngineering

Abstract

fetched live from OpenAlex

Wearing of conical picks on a coal mining machine and roadheaders are investigated experimentally using a full-scale rotary cutting machine. This study considers three types of conical picks with different tip materials to examine the effects of wear resistance of conical picks and wear characteristics in response to cutting load. The influence of pick wear on the cutting load and pick tip temperature are analyzed, thereby providing an experimental-based guideline for reducing pick wear. The results indicate that the cemented carbide pick has the best wear resistance among the three kinds of picks studied, and the pick life can be significantly extended for picks with a wear-resistant coating surface. It is also found that pick wear has the greatest influence on the normal force. Thermal fatigue and overloading are two factors that cause pick wear failure. The results can also be used to design the conical pick with wear-resistant coating and to validate the numerical models.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.218
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicTunneling and Rock MechanicsFrench-language works237,207