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Record W3178115487 · doi:10.5539/jmr.v13n4p30

Theory and Application of the Numerical Simulation in the Frozen Soil Problems

2021· article· en· W3178115487 on OpenAlexvenueno aff
Liye Song, Yirang Yuan

Bibliographic record

VenueJournal of Mathematics Research · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersNatural Science Foundation of Shandong ProvinceNational Science Foundation
KeywordsFrost heavingFrost (temperature)Soil waterMathematicsWater contentSoil scienceEnvironmental scienceGeotechnical engineeringMeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

The freezing-thawing processes in soils are important components of terrestrial hydrology, which significantly influence energy and water exchanges between land surface and sub-surface. Long-term changes in frost and thaw depths are also an important indicator of climate change. A water-heat coupled movements model is established with frozen soil in this paper, which treats the freezing/thawing front as a moving interface governed by some Stefan problems with two free boundaries. The numerical simulation is conducted by using the modified finite difference method. The model is validated to compare its predictions with GEWEX Asian Monsoon Experiment(GAME)-Tibet observations at D66 site in Tibetan Plateau. The results show that the simulated soil temperature, soil water content and frost/thaw depth are in excellent agreement with the measured values. Finally, optimal error estimation for L^∞ norm is derived on the model problem by using coordinate transformation method. The numerical simulation system is established on the basis of rigorous mathematics and mechanics, which successfully solved the important and difficult problems of environmental science.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.119
GPT teacher head0.372
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Mathematics ResearchSame topicClimate change and permafrostFrench-language works237,207