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Record W4417507956 · doi:10.20873/saberesemcirculacao9

SIMULAÇÃO DE ROMPIMENTO DE UMA BARRAGEM DE REJEITOS INDUSTRIAIS DE FERTILIZANTES EM ARRAIAS, TOCANTINS, BRASIL

2025· article· W4417507956 on OpenAlexaboutno aff
Ricardo Ribeiro Dias, Talita Cintra Braga, Girlene Figueiredo Maciel, Rose Mary Gondim Mendonça

Bibliographic record

VenueDESAFIOS Revista Interdisciplinar da Universidade Federal do Tocantins · 2025
Typearticle
Language
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Yield (engineering)Quarter (Canadian coin)

Abstract

fetched live from OpenAlex

Barragens são estruturas versáteis utilizadas para diversas finalidades, inclusive a contenção de rejeitos decorrentes da atividade de mineração. Nos últimos anos, o rompimento dessas estruturas se tornou um fato recorrente no Brasil, com destaque para os desastres de Mariana e Brumadinho, que acarretaram impactos ambientais irreversíveis e perda de centenas de vidas. Isso vem mostrando o quanto a aplicação de modelos computacionais para prever cenários ocasionados pelo rompimento de barragem, é muito apropriada para antecipar as consequências do rompimento de barragens e balizar os planos de ação de emergência de barragens. No estudo realizado para a barragem de rejeitos da Itafós Arraias Mineração e Fertilizantes S.A., utilizou-se o HEC-RAS que incorpora a modelagem do rompimento de barragens de fluidos não newtonianos, combinado com o ArcGIS, modelo digital de elevação ALOS PALSAR e outros dados biofísicos da área de influência da barragem. A simulação do comportamento da onda de cheia foi por rompimento do tipo piping, com os resultados mostrando uma área de inundação 484,02 ha, profundidade máxima de 19,78 m, velocidade máxima de propagação da onda de 13 m/s e vazão máxima 2.619,25 m3/s (Seção 1), e as possíveis interferências/impactos em paisagens naturais, áreas de uso antrópico e obras públicas.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.262
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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDESAFIOS Revista Interdisciplinar da Universidade Federal do TocantinsSame topicTailings Management and PropertiesFrench-language works237,207