MétaCan
Menu
Back to cohort
Record W4366492304 · doi:10.11159/icsect23.129

Sensitivity of Raft Foundation’s Structural Behaviour to Changes in Geometry and Materials

2023· article· en· W4366492304 on OpenAlexvenueno aff
Sami W. Tabsh, Magdi Elemam

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
FundersAmerican University of Sharjah
KeywordsRaftFoundation (evidence)Sensitivity (control systems)GeometryComputer scienceMaterials scienceMathematicsEngineeringComposite materialPolymerGeographyCopolymerArchaeology

Abstract

fetched live from OpenAlex

The finite element method is used to examine the sensitivity of the response of rafts subjected to concentrated loads to changes in geometry and material within the foundation.The parameters that are varied in the analysis include the mat thickness, soil modulus of subgrade reaction, concrete modulus of elasticity and spacing between columns.The structural response of the mat is studied by investigating the critical soil bearing pressure beneath the mat, as well as the internal bending moment and shear within the foundation.Findings of the study showed that the most important variables that can impact the structural behaviour of a mat are the thickness and spacing between columns, and to a lesser extent the soil modulus of subgrade reaction and concrete modulus of elasticity.Results of the sensitivity analysis are used to develop a relative mat rigidity factor that can quantitatively predict the degree of rigidity of a mat foundation, which can help in determining whether or not the traditional rigid approach can be safely used to analyse a given 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.792

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicStructural Engineering and Vibration AnalysisFrench-language works237,207