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COMPLETE AND SEMI-COMPLETE EXPLICIT ALGORITHMS OF A UNIFIED CRITICAL STATE MODEL FOR OVER-CONSOLIDATED SOILS

2023· article· en· W4367282146 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal for Multiscale Computational Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsConsolidation (business)AlgorithmConvergence (economics)Nonlinear systemRate of convergenceComputer scienceImplementationMathematics

Abstract

fetched live from OpenAlex

This paper presents a comparison of the performance of explicit algorithm and semi-complete explicit algorithm in the numerical implementations of an unconventional plastic model for soils. The new model, named CASM-S, is developed by incorporating the sub-loading surface theory into the standard unified clay and sand model (i.e., CASM), to enhance the prediction ability for the mechanical behavior of over-consolidated soils. The complete explicit algorithm of CASM-S is based on the sub-stepping method with the technique of automatic error control (SUBM), while the semi-complete explicit algorithm adopts the cutting-plane integration procedure (CPM). The complete implementation process of this model is performed, and the stability, accuracy, and efficiency of these two algorithms are compared through a series of numerical simulations, such as fluid-structure coupling problem, over-consolidation problem, and square-footing problem. These simulations demonstrate that CASM-S implemented by both the SUBM and CPM can obtain a reliable solution under appropriate size of increments. For the sub-loading surface model with highly nonlinear characteristics used in this paper, the CPM has faster local convergence rate, but the SUBM shows a higher efficiency and accuracy at global level.

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.

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)0.000
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: none
Teacher disagreement score0.794
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.038
GPT teacher head0.304
Teacher spread0.266 · 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