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Record W2886606445 · doi:10.2478/johh-2018-0020

Calculation of critical flow depth using method of algebraic inequality

2018· article· en· W2886606445 on OpenAlex
Tiejie Cheng, Jun Wang, Jueyi Sui

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.

Bibliographic record

VenueJournal of Hydrology and Hydromechanics · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsUniversity of Northern British Columbia
FundersNational Natural Science Foundation of China
KeywordsMathematicsAlgebraic numberPolynomialFlow (mathematics)Energy (signal processing)Algebraic equationOpen-channel flowApplied mathematicsProcess (computing)Channel (broadcasting)Calculus (dental)Mathematical analysisComputer scienceGeometryPhysicsNonlinear systemStatistics

Abstract

fetched live from OpenAlex

Abstract To calculate the critical depth and the least specific energy of steady non-uniform flows in open channels, one has to solve the polynomial equations. Sometimes, the polynomial equations are too difficult to get them solved. In this study, the theory of algebraic inequality has been used to derive formulas for determining the critical depth and the least specific energy of a steady non-uniform flow in open channel. The proposed method has been assessed using examples. Results using this new method have been compared to those using other conventional methods by engineers and scientists. It is found that the proposed method based on algebraic inequality theory not only makes the calculation process to be easy, but also gives the best calculation results of the critical depth and the least specific energy of a steady nonuniform flow.

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)0.001
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: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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