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Record W4388628112 · doi:10.1016/j.jrmge.2023.09.007

A coupled cryogenic thermo-hydro-mechanical model for frozen medium: Theory and implementation in FDEM

2023· article· en· W4388628112 on OpenAlexafffund
Lei Sun, Xuhai Tang, Kareem Ramzy Aboayanah, Qi Zhao, Quansheng Liu, Giovanni Grasselli

Bibliographic record

VenueJournal of Rock Mechanics and Geotechnical Engineering · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaHong Kong Polytechnic UniversityUniversity of TorontoResearch Grants Council, University Grants CommitteeEnergi Simulation
KeywordsCoupling (piping)Porous mediumFrost heavingPermeability (electromagnetism)MechanicsHeat transferMaterials scienceGeotechnical engineeringGeologyPhysicsPorosityChemistry

Abstract

fetched live from OpenAlex

This paper presents the development of a coupled modeling approach to simulate cryogenic thermo-hydro-mechanical (THM) processes associated with a freezing medium, which is then implemented in the combined finite-discrete element method code (FDEM) for multi-physics simulation. The governing equations are deduced based on energy and mass conservation, and static equilibrium equations, considering water/ice phase change, where the strong couplings between multi-fields are supplemented by critical coupling parameters (e.g. unfrozen water content, permeability, and thermal conductivity). The proposed model is validated against laboratory and field experiments. Results show that the cryogenic THM model can well predict the evolution of strongly coupled processes observed in frozen media (e.g. heat transfer, water migration, and frost heave deformation), while also capturing, as emergent properties of the model, important phenomena (e.g. latent heat, cryogenic suction, ice expansion and distinct three-zone distribution) caused by water/ice phase change at laboratory and field scales, which are difficult to be all revealed by existing THM models. The novel modeling framework presents a gateway to further understanding and predicting the multi-physical coupling behavior of frozen media in cold regions.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.408

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 head0.020
GPT teacher head0.254
Teacher spread0.235 · 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

Citations45
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Rock Mechanics and Geotechnical EngineeringSame topicClimate change and permafrostFrench-language works237,207