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Record W2528441821 · doi:10.2965/jwet.16-026

Dynamic Simulation of Trickling Filter Process with Hydraulic Stress Tests

2016· article· en· W2528441821 on OpenAlexaff
Nguyen Duong Quang Chanh, Bing Liu, Mitsuharu Terashima, Rajeev Goel, Hidenari Yasui

Bibliographic record

VenueJournal of Water and Environment Technology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsHydromantis Environmental Software Solutions (Canada)
FundersJapan Society for the Promotion of Science
KeywordsTrickling filterEffluentNitrificationWastewaterFilter (signal processing)Activated sludgeEnvironmental scienceSewage treatmentHydraulic retention timeEnvironmental engineeringPulp and paper industryChemistryNitrogenEngineering

Abstract

fetched live from OpenAlex

Trickling filter process is focused on developing Asian countries in recent years as an alternative energy-saving wastewater treatment to conventional activated sludge systems. This paper investigated influential hydraulic operational parameters on the process performance using a nitrification reactor. The trickling filter process was expressed as 2-dimensional biofilm layers where the influent flowed to the bottom of the filter bed while oxygen was dissolved from the ambient air. The 4 m-height pilot-scale trickling filter filled with tubular plastic media (1.5 cm × 1.5 cm, 371 m2/m3-reactor volume) was installed at a municipal wastewater treatment plant in Da Nang, Vietnam. During the 2-day hydraulic stress test, the nitrogen and hydraulic loadings were changed in a step-wise manner. Focusing on the nitrification which was a dominant oxygen uptake, the process performance was dynamically simulated with a modification of IWA Activated Sludge Model (International Water Association). The effluent concentrations of dissolved oxygen and inorganic soluble nitrogenous compounds were reasonably calculated under the hydraulic loading ranging between 2.4 and 18 m/h. The reactive wetted surface area of the filter seemed to increase when high linear velocity of the fluid was applied, which resulted in the increase of volumetric biological reaction rates.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.216

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 head0.205
Teacher spread0.199 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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