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Record W2141581573 · doi:10.1139/t09-145

Design load of rigid footings on sand

2010· article· en· W2141581573 on OpenAlexvenueno aff
Edgar G. Diaz, F Rodriguez-Roa

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
FundersPontificia Universidad Católica de ChileUniversidad de Chile
KeywordsGeotechnical engineeringEmbedmentPenetration testSettlement (finance)Lateral earth pressureFinite element methodShear strength (soil)EngineeringPore water pressureGeologyStructural engineeringSoil water

Abstract

fetched live from OpenAlex

Experimental evidence has shown that most current methods are not able to predict design loads of footings on cohesionless soil with an acceptable degree of accuracy. In the present study, a simple and realistic settlement-based method is proposed to estimate the design load of rigid footings on sand subjected to static vertical loading. The design criterion based on restricting the end-of-construction settlement to 16 mm because of the inherent variability of the real soil deposits is herein adopted. A series of finite-element analyses based on an advanced constitutive model were carried out to study the load–settlement response of footings supported on 14 sandy soils. Routine design charts were developed to predict the net allowable soil pressure of footings on normally consolidated and overconsolidated sands. These charts consider footing shape, embedment depth, grain diameters D 10 and D 60 , particle shape, unit weight (or submerged unit weight for saturated sands), and indirect measurements of the shear strength derived from in situ tests, such as relative density, standard penetration test (SPT) or cone penetration test (CPT). As shown, the proposed charts match well with available experimental data.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.523
Threshold uncertainty score0.571

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 integrity0.0000.001
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 head0.008
GPT teacher head0.187
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

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 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

Citations2
Published2010
Admission routes1
Has abstractyes

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