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Record W2164183295 · doi:10.3141/1772-14

Limit States and Factor of Safety in Design of an Anchored Sheet Pile Wall

2001· article· en· W2164183295 on OpenAlexafffund
A. B. Schriver, Arun J. Valsangkar

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2001
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsUniversity of New Brunswick
FundersU.S. Army Corps of EngineersNatural Sciences and Engineering Research Council of Canada
KeywordsEmbedmentStructural engineeringBending momentParametric statisticsSafety factorEngineeringLimit state designGeotechnical engineeringSoil nailingPileMoment (physics)Range (aeronautics)Factor of safetyRetaining wallMathematics

Abstract

fetched live from OpenAlex

Factors of safety in the traditional design of anchored sheet pile walls have been introduced in a variety of ways. Furthermore, empirical and semiempirical factors are used to modify the calculated depth of embedment, anchor rod force, and maximum bending moment in sheet piling. This leads to a range of designs within the traditional allowable stress design (ASD) approach. Even in the new ultimate limit states design (LSD) method, two approaches are available. One approach is to use load and resistance factor design (LRFD), and the other is to use partial safety factors on the material properties in combination with load factors. In view of the number of design alternatives available, a calibration study of LSD with ASD for an anchored bulkhead was performed. The practical problem of a steel sheet pile wall in a layered cohesionless soil and cohesionless soil overlying cohesive soil was analyzed. The depth of embedment, the anchor rod force, and the maximum bending moment in sheet piling were determined for a range of soil parameters by using LSD and ASD methods. The factors recommended in various codes, manuals, and handbooks were used to perform calibration studies. The results of the parametric study indicate that the load and resistance factors recommended in the LRFD approach must be reevaluated.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.058
GPT teacher head0.321
Teacher spread0.263 · 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

Citations3
Published2001
Admission routes2
Has abstractyes

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