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Record W2320420856 · doi:10.1061/9780784412688.056

Study on the Analysis of Mat Foundations Using a Different Approach

2012· article· en· W2320420856 on OpenAlexaff
Rashedul H. Chowdhury, Mavinakere Eshwaraiah Raghunandan, A. Muqtadir

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsFinite element methodStructural engineeringSlabSettlement (finance)Foundation (evidence)Moment (physics)Shallow foundationMethod of analysisDifferential (mechanical device)Geotechnical engineeringComputer scienceEngineeringGeologyBearing capacityPhysics

Abstract

fetched live from OpenAlex

Mat foundations, in general, are reinforced concrete slabs to support and transfer structural load to the underlying soil, and are well suited to reduce differential settlement. Finite element (FE) method is widely used in the analysis, however the approach to solve and analyze the problem is of prime importance considering the engineering significance and cost involved in the structure. The main objective of this study was to analyze an idealized mat foundation soil system with different approach, which include the Mat foundation analyzed as an inverted flat slab by flat plate analysis and finite element analysis. The moment in longitudinal and transverse direction was determined from the analysis performed for models with two different KS of 4250kN/m2/m and 7250kN/m2/m. The results from flat plate analysis were similar to FE analysis, where direct design method overestimate the moment but certainly gives a more safe design when compared with the FE methods.

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: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.152

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 head0.057
GPT teacher head0.263
Teacher spread0.205 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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