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Modeling the Effects of Backfilling and Soil Compaction beside Shallow Buried Pipes

2013· article· en· W1981824796 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

VenueJournal of Pipeline Systems Engineering and Practice · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsCompactionCulvertGeotechnical engineeringSoil compactionFinite element methodGeologySettlement (finance)Stress (linguistics)ThrustSoil structure interactionStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Compaction of the soil placed beside culverts (the side-fill) can have a significant effect on the behavior of flexible and rigid structures. This is particularly true for shallow buried structures when the stresses resulting from compaction represent a greater proportion of the total stresses present. Different techniques have been reported in the literature to model soil compaction during finite-element analyses. A new semiempirical technique is proposed, which takes into consideration the increase in lateral stress and soil kneading during compaction. A simple procedure is discussed to incorporate the compaction of granular material in finite-element analysis. The new technique is used to model five different pipe products composed of different materials and dimensions, and the results are compared to measured values reported in the literature. A new factor is proposed to account for soil kneading during compaction to provide an upper limit for the pipe deformations and stresses that result during installation. The technique can be used to estimate peaking in flexible culverts and the additional crown moments and thrust that result in rigid culverts.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.496
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.007
GPT teacher head0.204
Teacher spread0.198 · 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