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Record W4416020842 · doi:10.1007/s40571-025-01092-y

Advances in discrete element modeling of rock fracture for next-generation comminution models

2025· article· en· W4416020842 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.

Bibliographic record

VenueComputational Particle Mechanics · 2025
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsInstitute of Particle Physics
FundersDivision of Chemical, Bioengineering, Environmental, and Transport SystemsHrvatska Zaklada za ZnanostNational Science Foundation
KeywordsComminutionDiscrete element methodExtended discrete element methodElement (criminal law)Context (archaeology)Process (computing)

Abstract

fetched live from OpenAlex

Abstract This paper provides a methodological overview of the current state of the art in discrete element modeling of rock fracture in the context of comminution, an energy-intensive process of breaking down rocks into smaller sizes. This process is essential for liberating valuable metals and minerals that are in growing demand for the green transition and the electrification of society. The paper covers the most recent developments and addresses fundamental issues in the bonded discrete element method, the lattice element method, the particle replacement method, and the level-set discrete element method. We argue that the most effective modeling approach must emerge from a synergy between solid mechanics, rock mechanics, and the comminution field—an effort made by this collaborating multidisciplinary group, with the goal of making the next generation of comminution models, powered by GPU-accelerated high-performance computing, more reflective of real-life rock behavior, advancing energy-efficient mining.

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)0.000
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 score0.890
Threshold uncertainty score0.313

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 head0.043
GPT teacher head0.284
Teacher spread0.241 · 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