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Record W4385453329 · doi:10.11159/ijci.2023.003

Development of Relative Rigidity Measure for Shallow Foundations

2023· article· en· W4385453329 on OpenAlexvenueno aff
Sami W. Tabsh, Magdi Elemam

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
FundersAmerican University of Sharjah
KeywordsRigidity (electromagnetism)Measure (data warehouse)GeologyGeotechnical engineeringMathematicsStructural engineeringComputer scienceEngineeringData mining

Abstract

fetched live from OpenAlex

This study investigates the influence of the structureto-soil relative rigidity on the structural behaviour of shallow foundation.The effect of change in the material and geometrical properties on the critical soil pressure intensity, bending moment and shear force of spread footings and rafts is investigated numerically using the finite element method.The parameters that are addressed in the analysis include the foundation thickness, soil modulus of subgrade reaction, concrete modulus of elasticity and plan geometry of the foundation.The foundation is modelled by thick shell elements while the soil by Winkler elastic springs.Findings of the study showed that the most important variables that affect the structural response of shallow foundations are the thickness and plan dimensions of the foundation, and to a lesser extent the soil modulus of subgrade reaction and concrete modulus of elasticity.A relative foundation-to-soil rigidity measure that can quantitatively predict the degree of stiffness of a shallow foundation was developed.The rigidity measure can help engineers in forecasting whether the traditional rigid foundation approach can be safely used to analyse a given spread footing or raft.

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 score0.830
Threshold uncertainty score0.336

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 integrity0.0000.000
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 head0.015
GPT teacher head0.258
Teacher spread0.244 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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