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Effect of Freeze/Thaw Cycles on the Performance and Microstructure of Cement-Treated Soils

2016· article· en· W2463539901 on OpenAlexaff
Reza Jamshidi, Craig B. Lake, Peter Gunning, Colin D. Hills

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsTetra Tech (Canada)
Fundersnot available
KeywordsMicrostructureCementMaterials scienceOptical microscopeComposite materialSoil waterCompressive strengthScanning electron microscopeEnvironmental scienceSoil science

Abstract

fetched live from OpenAlex

In this paper, the performance and structural changes in cement-treated soils under influence of freeze/thaw (f/t) exposure are investigated. Specimens from plastic and compacted soil-cement mix designs were exposed to different f/t scenarios to study the influence of f/t dimensionality (i.e., one-dimensional versus three-dimensional exposure) and specimens’ age at the time of f/t exposure on changes in their performance. Changes in hydraulic conductivity, unconfined compressive strength, and longitudinal resonant frequency of the specimens were studied under each exposure scenario. An examination of the microstructure of the f/t exposed and control specimens using transmitted light optical microscopy was also performed to evaluate how the soil-cement matrix was disrupted after exposure to f/t cycling. Observations showed increases in water content of the mix design (when wet of optimum water content), as well as increased specimen age at the time of exposure may increase f/t susceptibility. On the other hand, comparison of the performance of the specimens exposed to 1D and 3D f/t exposure did not show any significant variation. Microstructural analysis of petrographic thin section samples from control and f/t exposed specimens showed that while optical microscopy can detect matrix disintegration for highly damaged specimens, it is not able to identify structural degradation at early stages of damage development.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.003
GPT teacher head0.183
Teacher spread0.179 · 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 designBench or experimental
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

Citations58
Published2016
Admission routes1
Has abstractyes

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