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Record W2075905759 · doi:10.1680/adcr.2010.22.4.211

Thermodynamic modelling: state of knowledge and challenges

2010· article· en· W2075905759 on OpenAlexaff
Barbara Lothenbach, D. Damidot, Thomas Matschei, J. Marchand

Bibliographic record

VenueAdvances in Cement Research · 2010
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCementitiousCementWork (physics)Thermodynamic equilibriumThermodynamicsDissolutionBiochemical engineeringThermodynamic systemMaterials scienceChemistryEngineeringPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

Over recent decades, understanding of the fundamental aspects of the chemistry of cement has advanced. Many of the leading-edge contributions on the subject were either authored by Professor Glasser and his colleagues or heavily inspired by their work. In the present paper, the limits and recent evolutions of thermodynamic models applied to cement systems are briefly presented, and their current limitations and future challenges are discussed. A number of examples illustrate how such models can be used to predict the influence of different factors such as cement composition, hydration, relative humidity or temperature on the composition and the properties of a hydrated cementitious system. The combination of chemical and transport models makes it possible to calculate the interactions of cementitious systems with the environment. However, precipitation and dissolution processes can be slow so that thermodynamic equilibrium may not always be reached, particularly during the first stages of the hydration process. This is why an approach that couples thermodynamics and kinetics could provide useful information. The introduction of kinetics would not only help understanding of the intricate influence of various factors, such as solution concentrations, on the hydration of cement but it would also provide the theoretical basis for the development of fully coupled thermo-poro-mechanical models for the prediction of the volume stability of cement systems exposed to chemically aggressive environments.

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 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 score0.715
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.071
GPT teacher head0.358
Teacher spread0.287 · 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

Citations36
Published2010
Admission routes1
Has abstractyes

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