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Record W2372686692

Experimental study of optimization on energy dissipation and erosion control effect on Xujiahe reservoir spillway danger control and reinforcement project

2009· article· en· W2372686692 on OpenAlexaff
Jing Li

Bibliographic record

VenueWater Sciences and Engineering Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsSpillwayPierDissipationErosion controlErosionGeotechnical engineeringSillEngineeringChannel (broadcasting)Flow (mathematics)Civil engineeringGeologyStructural engineeringMechanics
DOInot available

Abstract

fetched live from OpenAlex

This study through hydraulic integrated physical model that has the geometrical scale of 1∶50,takes verifying experiment of some related hydraulic problems on the primary design program of Xiaogan city Xujiahe reservoir spillway dan- ger control and reinforcement project. At the same time, carrys out optimization experiment on program further improving the energy dissipation and erosion control effect of spillway. The study results show: the flood discharge capacity and energy dissipation and erosion control effect could fulfill the design demand. In order to improve the flow pattern in the first and second stilling pool and in the open channel, some optimization measures could be adapted: building T-shaped pier in the first stilling pool, setting energy dissipation pier and rough pier in open channel, setting energy dissipation piers on both sides of the first stilling pool end profile sill top, reducing the height of the second stilling pool end profile sill. The construction of Xujiahe bridge raises the local water level in open channel. According to the erosion experiment result, it is need to take some proper protections on the back of the HanYu railway bridge pier and the 316 national road pier.

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 score0.012
Threshold uncertainty score0.361

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 head0.005
GPT teacher head0.213
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 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
Published2009
Admission routes1
Has abstractyes

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