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Experimental and Numerical Investigation of Particle Kinematics in Shotcrete

2014· article· en· W2085132848 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2014
Typearticle
Languageen
FieldMaterials Science
TopicEngineering and Material Science Research
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNozzleShotcreteKinematicsMechanicsParticle (ecology)Particle velocityMechanical engineeringProcess (computing)AirflowStructural engineeringEngineeringMaterials scienceComputer scienceClassical mechanicsPhysicsGeology

Abstract

fetched live from OpenAlex

The intent of this paper is to identify the basic physical laws governing particle kinematics in a shotcrete spray. This paper presents a governing equation based on Newton’s second law where nozzle and airflow characteristics, and particle features are used to predict impact velocity of the material exiting the nozzle. Experimental values obtained using high-speed imaging measurements on marbles and aggregate particles correlate well with the results of numerical simulations on a simplified spraying system. With the controlling parameters of particle kinematics fully understood, the analysis of the governing equations offers essential elements for nozzle optimization and new mix design investigations. This paper also addresses the necessity of broadening the investigation to the entire spray of particles exiting the nozzle for a complete understanding of the spraying process on placement mechanisms at a process scale.

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.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.018
GPT teacher head0.266
Teacher spread0.249 · 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