MétaCan
Menu
Back to cohort
Record W1992235294 · doi:10.1115/1.4001157

Asymptotic Generalizations of the Lockhart–Martinelli Method for Two Phase Flows

2010· article· en· W1992235294 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Fluids Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLaminar flowPressure dropTurbulenceMechanicsFlow (mathematics)Open-channel flowIsothermal flowTwo-phase flowThermodynamicsPipe flowFlow coefficientPlug flowPhysics

Abstract

fetched live from OpenAlex

The Lockhart–Martinelli (1949, “Proposed Correlation of Data for Isothermal Two Phase Flow, Two Component Flow in Pipes,” Chem. Eng. Prog., 45, pp. 39–48) method for predicting two phase flow pressure drop is examined from the point of view of asymptotic modeling. Comparisons are made with the Lockhart–Martinelli method, the Chisholm (1967, “A Theoretical Basis for the Lockhart-Martinelli Correlation for Two Phase Flow,” Int. J. Heat Mass Transfer, 10, pp. 1767–1778) method, and the Turner–Wallis (1969, One Dimensional Two Phase Flow, McGraw-Hill, New York) method. An alternative approach for predicting two phase flow pressure drop is developed using superposition of three pressure gradients: single phase liquid, single phase gas, and interfacial pressure drop. This new approach allows for the interfacial pressure drop to be easily modeled for each type of flow regime such as bubbly, mist, churn, plug, stratified, and annular, or based on the classical laminar-laminar, turbulent-turbulent, laminar-turbulent, and turbulent-laminar flow regimes proposed by Lockhart and Martinelli.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.631
Threshold uncertainty score0.384

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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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