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Record W4251922130 · doi:10.5383/ijtee.10.02.011

Effect of Thermal Pretreatment on the Solubilization of Organic Matters in a Mixture of Primary and Waste Activated Sludge

2015· article· en· W4251922130 on OpenAlexvenueno aff
A. M. Aboulfoth, E. H. El Gohary, Ola Diaa El Monayeri

Bibliographic record

VenueInternational Journal of Thermal and Environmental Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsnot available
Fundersnot available
KeywordsAnaerobic digestionBiogasActivation energyChemistryActivated sludgeAnaerobic exerciseSolubilizationDigestion (alchemy)Reaction rate constantWaste managementSewage sludgeOrder of reactionPulp and paper industryKineticsNuclear chemistryChromatographyOrganic chemistrySewage treatmentBiochemistryMethaneBiology

Abstract

fetched live from OpenAlex

The increased demand for advanced techniques in anaerobic digestion over the last few years has led to the employment of various pre-treatment methods prior to anaerobic digestion to increase gas production. These pre-treatment methods alter the physical and chemical properties of sludge in order to make it more readily degradable by anaerobic digestion. Although the thermal pre-treatment presents high energy consumption, the main part of this energy to heat can be recovered from the biogas produced in the anaerobic process. In this research a mixture of primary and waste activated sludge was thermally pretreated at 100, 125, 150, 175 and 200 oC in order to determine the reaction kinetics for the increase of soluble organic fraction (expressed as CODs and VFAs). Experimental results proved that the solubilization of sludge is a 1st order reaction with respect to both CODs and VFAs, KCODs (reaction rate constant of CODs solubilization) increased from 4.59*10-3 (min-1) to 7.55*10-3 (min-1) as the temperature increased from 100 to 200 oC, with a reaction activation energy of 7447.21 (J/mole) and frequency factor of 0.051 (min-1), While KVFAs (reaction rate constant of VFAs solubilization) increased from 5.33*10-3 (min-1) to 7.97*10-3 (min-1) for the same increase in temperature, with a reaction activation energy of 5947.22 (J/mole) and frequency factor of 0.0364 (min-1).

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 score0.124
Threshold uncertainty score0.198

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 head0.004
GPT teacher head0.168
Teacher spread0.164 · 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
Published2015
Admission routes1
Has abstractyes

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