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Record W2605913109 · doi:10.11159/icgre17.119

Numerical Investigation of the Bedding Factor of Concrete Pipes under Deep Soil Fill

2017· article· en· W2605913109 on OpenAlexvenueno aff
Saif Alzabeebee, David N. Chapman, Asaad Faramarzi

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersHigher Committee for Education Development in Iraq
KeywordsBeddingGeotechnical engineeringGeologyStructural engineeringComputer scienceEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

The Indirect Design Method is often used to design buried concrete pipes. This method is based on linking the required strength of the buried concrete pipe to the laboratory strength of the pipe by using an empirical factor called the bedding factor. Hence, the bedding factor is key in the Indirect Design Method. However, a thorough review of the literature showed that the bedding factor has not received signification attention in previous studies. This study therefore reports the preliminary results of ongoing research investigating the bedding factors and the behaviour of concrete pipes under deep soil fill using validated numerical modelling. The results showed that the AASHTO bedding factors for type 2, type 3 and type 4 AASHTO installations are conservative, while the bedding factor is unsafe for pipes buried in type 1 installation with a backfill height of less than 2.4 m. Comparing the results of the present study with the British Standard bedding factors showed that these factors are overly conservative. Hence, both design standards should be updated to enhance the robustness of the design approaches and make the design of concrete pipes more economic.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.722

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 science0.0010.000
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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207