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Record W4393394206

Recycling of dredged sediments in self-consolidating concrete : mix design optimization and durability study

2020· dissertation· fr· W4393394206 on OpenAlexaboutno aff
Amine el Mahdi Safhi

Bibliographic record

Venuetheses.fr (ABES) · 2020
Typedissertation
Languagefr
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsnot available
Fundersnot available
KeywordsDurabilitySelf-consolidating concreteEngineeringCivil engineeringWaste managementConstruction engineeringMaterials scienceComposite materialCompressive strength
DOInot available

Abstract

fetched live from OpenAlex

La demande en matériaux de construction a considérablement augmenté, dont la grande majorité est d’origine naturelle. Etant donné que ces matériaux ne sont pas renouvelables, il est essentiel de trouver des matériaux alternatifs. Les études récentes menées à l’IMT Lille Douai ont montré que les matériaux issus de dragage possèdent des propriétés pouzzolaniques intéressantes et peuvent être utilisées comme ajouts cimentaires alternatifs ou comme filler. Vu le volume important dragué annuellement, cette valorisation aura des impacts environnementaux et économiques très positifs.Les objectifs visés dans cette recherche portent sur : la valorisation des sédiments du Grand Port Maritime de Dunkerque (GPMD, France) dans les bétons autoplaçants (BAPs) comme ajouts cimentaires ; la valorisation des sédiments fluviaux du Château l’Abbaye (France) dans des mortiers comme ajouts cimentaires afin d’évaluer la mobilité et la stabilité des éléments traces métalliques ; la solidification des sables dragués des Iles-de-la-Madeline (Québec) par liant hydraulique afin de produire des roches artificielles.Dans l’ensemble, les résultats de ce travail sur les sédiments mettent en exergue la contribution substantielle de ces matériaux à l’amélioration des performances des bétons et supportent leur emploi comme ajouts cimentaires. Ces résultats contribuent à réduire l’empreinte du CO2 dans le béton, ainsi que les exploitations minières. Ils permettent de mieux comprendre le comportement des sédiments dans les bétons à partir de certaines analyses et traitements, et d’identifier les milieux agressifs convenables à l’utilisation des sédiments.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.045
GPT teacher head0.277
Teacher spread0.232 · 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.

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
Published2020
Admission routes1
Has abstractyes

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Same venuetheses.fr (ABES)Same topicRecycling and utilization of industrial and municipal waste in materials productionFrench-language works237,207