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Record W7083627457 · doi:10.1016/j.powtec.2025.121663

Design and optimize a novel hydrocyclone by combining mechanistic and data-driven models

2025· article· en· W7083627457 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePowder Technology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsnot available
FundersAustralian Research CouncilRio Tinto
KeywordsHydrocycloneLaminar flowConical surfaceInletSpiral (railway)Separation (statistics)Reduction (mathematics)VortexFlow (mathematics)Ligand cone angle

Abstract

fetched live from OpenAlex

New hydrocyclone designs can significantly enhance separation efficiency in applications such as water treatment and particle classification. Therefore, various hydrocyclone geometries with different inlet and cone configurations are explored through a validated mechanistic model, leading to a new cyclone design. The proposed design features a laminar spiral inlet and a straight-to-convex cone, achieving reductions of 44.2 % in separation sharpness and 58.4 % in water split. Its double-cone configuration reduces tangential velocities in the upper conical section, while the convex lower cone broadens the separation region, maintaining relatively high tangential velocities near the spigot. These effects reduce particle accumulation near the spigot and improve separation performance. Moreover, the laminar spiral inlet mitigates short-circuit flow near the vortex finder. To further enhance separation efficiency, the novel conical section is optimized by integrating mechanistic and data-driven models. Compared to the initial novel design, the optimized version exhibits an 18.2 % reduction in separation sharpness and a 16.2 % reduction in water split by optimizing four geometric variables characterizing the conical section. Internal flow field analysis confirms that the optimized configuration establishes favorable tangential velocities in the conical section, guiding fine and coarse particles along optimal paths and improving overall performance. • A novel design for the hydrocyclone is developed using the mechanistic model. • Mechanistic and data-driven models are combined to optimize the novel design. • The separation efficiency of the optimized novel design is improved significantly. • The laminar spiral inlet decreases the short-circuit flow near the vortex finder. • The longer and convex cone promotes the proper directional migration of particles.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score0.831

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 science0.0000.001
Research integrity0.0010.000
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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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