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Record W4414871815 · doi:10.1016/j.powtec.2025.121733

Experimental and theoretical quantification of in-situ crushing characteristics of irregularly-shaped particles under multi-axis pressure with X-ray micro-computed tomography (μCT) and discrete element method (DEM)

2025· article· en· W4414871815 on OpenAlexafffund
Xiangyu Wang, Daoyong Yang, Chenwei Liu, Mingzhong Li

Bibliographic record

VenuePowder Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Regina
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDiscrete element methodCompactionParticle (ecology)Hardening (computing)Strain hardening exponentStress (linguistics)Fracture (geology)Overburden pressureFinite element methodExtended discrete element method

Abstract

fetched live from OpenAlex

In this study, an integrated and robust framework has been developed to experimentally and theoretically quantify the in-situ crushing characteristics of irregularly-shaped particles under reservoir conditions. Experimentally, a multi-axis pressure loading system was customized to evaluate the in-situ crushing behaviour of packed proppants utilizing the X-ray micro-computed tomography (μCT) analysis. Based on the reconstructed CT images, the particle crushing behaviour was evaluated and analyzed, and its key parameters (e.g., failure modes, particle size distribution (PSD), and mean coordination number (CN)) were quantitatively determined. Based on force chain and fracture propagation dynamics, theoretically, the discrete element method (DEM) has been employed to generate irregularly-shaped particles and thus confirm their morphologies of the reconstructed images so as to determine the simulation parameters. Particle failure modes are found to be influenced by both particle morphology and pressure loading conditions. Stress propagates along the force chains and then extends in chain-like or networked patterns. Along these paths, the principal stress directions of individual proppants vary, resulting in diverse failure modes. The crushing process transitions from a dynamic state to a steady one, during which sub-particles generated from crushed particles are compacted under the applied load and filled the entire pore spaces. Such compaction increases the overall average CN, while higher CNs are less likely to crush the larger particles in a given system. With lateral confining stress, the internal force chain network of the packed proppants is found to be more homogeneous, leading to the strain hardening effect and significant improvement of the compressive strength. • In-situ crushing characteristics of irregularly-shaped proppants under reservoir conditions was quantified. • Multi-axis crushing tests were integrated with μCT scanning to visualize and quantify the in-situ fracture dynamics. • Such scanned 3D morphology of particles was digitized and encoded as customized functions. • Crushing dynamics of irregularly-shaped proppants were described as a function of confining pressure.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.248
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

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".

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Citations1
Published2025
Admission routes2
Has abstractyes

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