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Record W2901558800 · doi:10.25071/10315/35426

Influence Of Flow Velocity On Erosion-Corrosion Performance Of 90º Carbon Steel Elbows In Potash Brine

2018· article· en· W2901558800 on OpenAlexaff
Raheem Elemuren, Richard W. Evitts, Ikechukwuka N. A. Oguocha, Glyn Kennell, A.G. Odeshi, Regan Gerspacher

Bibliographic record

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPotashBrineErosionCorrosionCarbon steelGeologyErosion corrosionFlow velocityFlow (mathematics)MetallurgyEnvironmental scienceMaterials scienceMining engineeringPotassiumGeomorphologyMechanics

Abstract

fetched live from OpenAlex

In this study, the effects of flow velocity and solid concentration on erosion-corrosion behavior of AISI 1018 long-radius steel elbows (Schedule 40) in saturated potash brine were investigated. Potash brine containing 10 and 30 wt% of silica sands flowing at 2.5, 3.0, 3.5 and 4.0 m/s through a continuous loop with pipe internal diameter of 2.54 cm was used as the slurry. All experiments were conducted at 30 C. The surface damage on elbows was evaluated using scanning electron microscopy (SEM). It was found that material loss per unit area was greater at high slurry velocity and solid concentration. Corrosion pits were visible on the elbow surfaces at low slurry velocities, but pits were not formed at higher velocities. Mechanical damage was concluded to be the dominant degradation mechanism at high flow velocities.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.982

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueProgress in Canadian Mechanical EngineeringSame topicErosion and Abrasive MachiningFrench-language works237,207