MétaCan
Menu
Back to cohort
Record W2804043209 · doi:10.1155/2018/3105384

Rock Dynamic Fracture Characteristics Based on NSCB Impact Method

2018· article· en· W2804043209 on OpenAlexaff
Yanbing Wang

Bibliographic record

VenueShock and Vibration · 2018
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsGeomechanica (Canada)
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsSplit-Hopkinson pressure barMaterials scienceDynamic loadingFracture toughnessFracture (geology)Fracture mechanicsClampingDynamic testingStructural engineeringGeotechnical engineeringComposite materialGeologyEngineeringStrain rateMechanical engineering

Abstract

fetched live from OpenAlex

In 2012, the International Society for Rock Mechanics (ISRM) recommended a new Notched Semicircular Bend (NSCB) method for the determination of dynamic fracture toughness of rock materials, but it did not consider the effect of some uncontrollable factors in the course of the experiment on the test result. This thesis firstly carried out dynamic fracture toughness experiments on several typical rock materials such as sandstone using the modified Split‐Hopkinson Pressure Bar (SHPB) experimental system with high‐speed photography, directly compared the dynamic fracture failure characteristics of several rock materials, and examined the loading rate dependency of the dynamic fracture toughness of rock materials. Based on the numerical analysis method of Discrete Lattice Spring Model (DLSM), it focused on the effect of bullet impact loading rate, loading area of incident bar, support restraints of clamping specimen, and other uncontrollable factors in the course of SHPB experiment on test results. The findings can be referenced for the improvement of NSCB method.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.370

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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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 designSimulation or modeling
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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueShock and VibrationSame topicRock Mechanics and ModelingFrench-language works237,207