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Record W2178131807 · doi:10.1002/hyp.10711

Laboratory study of infiltration into two frozen engineered (sandy) soils recommended for bioretention

2015· article· en· W2178131807 on OpenAlexaff
Shahab Moghadas, A-M Gustafsson, Peter Viklander, Jiří Maršálek, Maria Viklander

Bibliographic record

VenueHydrological Processes · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsSoil waterWater contentInfiltration (HVAC)Environmental scienceSoil scienceMoistureGradationGeotechnical engineeringMaterials scienceGeologyComposite material

Abstract

fetched live from OpenAlex

Abstract Infiltration of water into two frozen engineered soils of different gradation was studied in laboratory soil columns 1.2 m long and 0.1 m in diameter. Prior to testing, the soil moisture was adjusted to two levels, described by the gravimetric water content of 5% or 10%, and soils were compacted to about 80–90% of the maximum dry density and refrigerated to temperatures ranging from −8 to −2 °C. Water with temperatures 8–9 °C was thereafter fed on the top of columns at a constant head, and the times of water breakthrough in the column and reaching a steady percolation rate, as well as the percolation rate, were recorded. The soil water content was a critical factor affecting the thawing process; during freezing, soil moisture was converted into ice, which blocked pores, and its melting required high amounts of energy supplied by infiltrating water. Hence, the thawing of soils with higher initial water content was much slower than in lower moisture soils, and water breakthrough and the attainment of steady percolation required much longer times in higher moisture soils. Heat transfer between infiltrating water, soil ice, and frozen soil particles was well described by the energy budget equations, which constitute a parsimonious model of the observed processes. The finer grained soil and more compacted soil columns exhibited reduced porosity and required longer times for soil thawing. Practical implications of study results for design of bioretention facilities (BFs) in cold climate include the use of coarse engineered soils and fitting bioretention facilities with a drain facilitating soil drainage before the onset of freezing weather. Copyright © 2015 John Wiley & Sons, Ltd.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.394

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 head0.045
GPT teacher head0.275
Teacher spread0.230 · 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 designObservational
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

Citations38
Published2015
Admission routes1
Has abstractyes

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