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Record W3098227836 · doi:10.18280/ijdne.150501

Hierarchical Criticality Analysis of Clean Technologies Applied to a Coal-Fired Power Plant

2020· article· en· W3098227836 on OpenAlexvenueno aff
Andressa Padilha de Oliveira, Giulio Lorenzini, Zeban Shah, Marcos Antônio Klunk, José Eduardo de Carvalho Lima, Luíz Alberto Oliveira Rocha, Nattan Roberto Caetano

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCoalWaste managementClean coalElectricity generationPower stationEngineeringProcess engineeringCoal combustion productsEnvironmental scienceEnergy sourceWork (physics)Energy securityEnvironmental economicsPower (physics)Renewable energyMechanical engineeringEconomics

Abstract

fetched live from OpenAlex

Mineral coal is the main source of energy generation in the world. In Brazil, this energy source has a smaller share in the internal energy supply, 5.5% of the total. Despite this, issues of energy security, stable and low prices make coal a strategic source. Due to this source's importance, this work aims to evaluate the clean technologies used to mitigate the emission resulting from the combustion of coal from a thermoelectric plant that applies low quality coal in Brazil using an analytical hierarchy process to classify the viable technological alternatives for the production process. The articulation of the environmental management system was adequate to meet the environmental demands and the energy efficiency of the thermoelectric plant. However, the results suggest that the investment in a coal processing plant would increase the fuel quality, a critical factor in the reduction of operating milling costs, in the ash circuit, and the treatment of gaseous emissions.

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 score0.500
Threshold uncertainty score0.307

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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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Same venueInternational Journal of Design & Nature and EcodynamicsSame topicRecycling and Waste Management TechniquesFrench-language works237,207