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Record W2378350426

Design and Operation of VT Deep Shaft Aeration Process in Wastewater Treatment Plant in Xingping

2010· article· en· W2378350426 on OpenAlexaboutno aff
Feng Sheng-hua

Bibliographic record

VenueChina Water & Wastewater · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAerationEffluentSewage treatmentWastewaterPollutantEnvironmental engineeringMixing (physics)Aerated lagoonPower consumptionEnvironmental scienceWaste managementActivated sludgeEngineeringPower (physics)Chemistry
DOInot available

Abstract

fetched live from OpenAlex

The VERTREATTM(VT) deep shaft aeration process was introduced by Xingping WWTP from Canada as its wastewater treatment process,firstly in China.The design capacity of this plant is 5×104 m3/d.The design effluent quality meets the second level criteria specified in Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant(GB 18918-2002).However,the first level B criteria are met in practice.The main body of VT consists of two shafts with diameter of 3.2 m and depth of 92 m.The area occupied by VT system is 4 400 m2.The oxygen transfer efficiency reaches 65% to 86%.The aeration has many purposes: it can meet the requirements of microbial metabolism,mixing,air lifting,flotation for separation of sludge and so on.Therefore,the operation cost is significantly saved.The power consumption is 0.8 kW·h/kgBOD5.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.524

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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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 designBench or experimental
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
Published2010
Admission routes1
Has abstractyes

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