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Record W4388189936 · doi:10.18280/mmep.100543

A Parametric Study of Bridge Approach Slabs under Vehicle Loads Using SAP2000

2023· article· en· W4388189936 on OpenAlexvenueno aff
Abdullah Al-Hussein, Ihsan Al-abboodi

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Structural engineeringParametric statisticsEngineeringComputer scienceMathematicsStatisticsMedicine

Abstract

fetched live from OpenAlex

The transitional zone between a bridge and its adjoining roadway, known as the bridge approach, frequently experiences differential settlement.This study employs the threedimensional finite element software SAP2000 V22 to rigorously examine the performance of bridge approach slabs under vehicular loads, with a particular focus on the interaction between the slabs and embankment settlement.Bridge approach slabs and soil are modelled using shell and solid elements, respectively, with the soil characterized by the Drucker-Prager material model.A comprehensive investigation is undertaken to evaluate the effects of various soil and slab parameters on the system's performance, including slab thickness, slab length, approach slab restriction, fill material thickness, and soil's elastic modulus.Furthermore, a sensitivity analysis considering different boundary conditions is also conducted.The outcomes of the analysis include predicted slab deformations and bending moments under design traffic loads.Notably, a correlation is found between increased settlement and approach slab length at the slab's unrestricted boundary, particularly for soils of lower stiffness.The results also suggest that enhancing the compacted fill material thickness and the soil's elastic modulus can reduce slab deflection.The boundary condition and thickness of the slab are identified as key determinants of settlement values.These findings offer valuable insights for engineering professionals aiming to optimize bridge approach slab design, thereby boosting structural integrity and durability.

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 score0.495
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.060
GPT teacher head0.240
Teacher spread0.180 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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