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Development of centrifugal slurry pumps in tailings disposal and comparison with positive displacement pumps

2019· article· en· W2945024254 on OpenAlexfundno aff
Jeffrey Crawford, N Bessett

Bibliographic record

VenuePaste/˜Pœaste · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsnot available
FundersFLSmidthSyncrude
KeywordsCentrifugal pumpTailingsSlurryDisplacement (psychology)Petroleum engineeringPositive displacement meterEnvironmental scienceWaste managementEngineeringMechanical engineeringEnvironmental engineeringMaterials scienceImpellerMetallurgy

Abstract

fetched live from OpenAlex

This paper covers FLSmidth KREBS® pump development, over the past 10 years, of an extensive range of highpressure centrifugal slurry pumps for multistage applications. The primary objective has been to produce safe, economical, energy efficient and maintenance friendly centrifugal slurry pumps to fulfil the expanding requirements of the mineral processing industries in the long distance transportation of tailings and mineral slurries. Two ranges of pumps have been developed, a double cased pump (based on the KREBS rubber lined slurryMAX™ XD pump) and an unlined white iron cased pump (based on the millMAX™ pump). The logic behind the development of the two pump ranges will be explained in depth covering the design and first article production, getting it right. The methodology of the hydraulic and structural criteria requirements that are considered during the pumps’ design are integrated with the use of computational fluid dynamics and finite element analysis to ensure that the pumps perform safely, reliably and with maximum efficiency. Application of the pumps to projected operating data is explained taking into consideration specific needs for flange and foundation loads, maintenance and condition monitoring. Consideration of slurry rheology and its implication on pumping performance is discussed. Cost comparison between actual field data and the theoretical positive displacement (PD) costs, as presented at the 21st International Seminar on Paste and Thickened Tailings, will be analysed in the Appendix.

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: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.805

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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