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Record W4402626652 · doi:10.1016/j.tust.2024.106096

Stresses induced in a buried corrugated metal arch culvert due to backfilling compaction efforts

2024· article· en· W4402626652 on OpenAlexafffund
Islam Ezzeldin, Hany El Naggar, John Newhook

Bibliographic record

VenueTunnelling and Underground Space Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCulvertArchCompactionGeotechnical engineeringEngineeringStructural engineeringGeologyForensic engineering

Abstract

fetched live from OpenAlex

• Compaction forces increased the soil stresses as expected. • The maximum compaction impact is in the backfill layer that is directly under compaction. • Culvert deformation peaking occurs when the backfill height is at crown level. • Maximum culvert internal forces are developed when the backfill height is at crown level. • The developed 3D models were able to mimic the monitored culvert performance. The use of flexible buried corrugated metal culverts (CMCs) for traffic and watercourses has recently expanded as a promising technique for shallow underground tunnelling. However, in the design of such structures it is challenging to mimic the performance of the mobilized soil-structure interaction. The backfilling process, with the use of compaction forces, can be considered the major loading mode that develops the predominant deformations and internal forces in the culvert body. Therefore, a thorough understanding of the backfilling process and its effects can contribute to improving CMC design methodology. In this study, a laboratory experiment was used to investigate a flexible buried corrugated metal open-bottom arch culvert, where the compaction impact was monitored during each backfill stage. Following the installation of the culvert in a rigid steel tank, seven sequenced backfill layers were added and compacted, until the target cover depth was reached. Culvert deformations and internal forces were recorded during each backfilling stage. Moreover, the variations in vertical soil stresses developed due to backfilling were measured at two locations: the surface of the bedding soil, and just above the culvert crown. In addition, the lateral perpendicular stresses induced at the exterior circumference of the culvert body near the midpoint of each side backfill layer were measured during backfilling. Finally, a numerical analysis using 3D finite element modelling was performed to simulate the construction sequence of the laboratory test during the backfilling process. The numerical modelling results for the culvert deformations and internal forces were then validated against the recorded measurements obtained in the laboratory experiment and a numerical procedure to simulate the induced backfilling efforts was recommended.

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 categoriesMeta-epidemiology (narrow)
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 score0.104
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.231
Teacher spread0.221 · 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.

Study designSimulation or modeling
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

Citations10
Published2024
Admission routes2
Has abstractyes

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