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Use of Rigid Geofoam Insulation to Mitigate Frost Heave at Shallow Culvert Installations

2019· article· en· W2950541662 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Cold Regions Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsResearch ManitobaUniversity of Manitoba
Fundersnot available
KeywordsCulvertFrost heavingGeotechnical engineeringGeologyFrost (temperature)Environmental scienceGeomorphology

Abstract

fetched live from OpenAlex

Roadways over culverts experience severe distresses due to frost action in the subgrade. Thermal insulation placed near the culvert can reduce frost penetration in the soil surrounding the culvert. Three culvert sites backfilled with clay in Manitoba, Canada were instrumented with thermistors to monitor the changes in the soil thermal profile near culverts with and without thermal insulation placed below the culvert barrels. Temperature data from the instrumented sites were used to calibrate and validate a two-dimensional (2D) numerical model which was used in evaluating the performance of different placements of thermal insulation near culverts through a parametric study. The parametric study included evaluation of the use of thermal insulation above the culvert, below the culvert, and attached to the walls of culvert barrels to reduce the thermal disturbance in the soil. It was concluded that the least thermal disturbance in the soil was achieved when 75-mm thermal insulation was attached to the walls of the culvert. The outcomes of this study can be used to mitigate road roughness over culverts that is caused by frost action.

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: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.801

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 head0.011
GPT teacher head0.189
Teacher spread0.178 · 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