MétaCan
Menu
Back to cohort
Record W4319159879 · doi:10.3390/en16031501

Comparison on Hydraulic Characteristics of Vertical and Horizontal Air-Cushion Surge Chambers in the Hydropower Station under Load Disturbances

2023· article· en· W4319159879 on OpenAlexaff
Tingyu Xu, Sheng Chen, Jian Zhang, Xiaodong Yu, Jiawen Lyu, Haibin Yan

Bibliographic record

VenueEnergies · 2023
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Alberta
FundersGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsSurgeWater hammerHydropowerSurge tankMarine engineeringEnvironmental scienceRenewable energyFlow (mathematics)HydroelectricityVolume of fluid methodEngineeringGeotechnical engineeringMechanicsMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Hydroelectric energy is an increasingly vital and effective renewable energy for modern society. The protective effect on the water hammer in the pipeline, the operational stability of the hydropower system, and the flow regime in the air-cushion surge chamber (ACSC) are three main problems during the design of the hydropower station with an ACSC. Comprehensively comparing the above issues between the horizontal and vertical ACSCs is meaningful. This study established the one-dimensional (1D) model based on the Method of Characteristics (MOC) under large load disturbances (LLD) and the rigid water column theory under small load disturbances (SLD). At the same time, the three-dimensional (3D) model was built based on the Volume of Fluid (VOF) to obtain a more detailed flow regime in the ACSC under the load acceptance condition. The results showed that the vertical ACSC was superior to the horizontal one for its large safe water depth, smaller maximum air pressure, and more stable flow under LLD. In contrast, the horizontal one was better than the vertical one for its extensive water area to calm the SLD during the transient process and smaller fluctuation of the surge under SLD. This study will provide a reference for a future project on selecting the structure of the ACSC.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.229

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueEnergiesSame topicWater Systems and OptimizationFrench-language works237,207