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Record W4387134634 · doi:10.18280/ijsse.130419

Impact of Stepped Structures on Tsunami Wave Propagation and Overtopping Engineering

2023· article· en· W4387134634 on OpenAlexvenueno aff
Fayçal Chergui, Mohamed Bouzit

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicEarthquake and Tsunami Effects
Canadian institutionsnot available
Fundersnot available
KeywordsGeologySeismologyEngineeringGeotechnical engineeringForensic engineering

Abstract

fetched live from OpenAlex

The urgent necessity to fortify coastal regions and safeguard both the natural environment and key coastal infrastructure underscores the significance of structural measures in coastal engineering.Among these, the seawall reigns as the primary fortification method.This study aims to elucidate the impact of a stepped structure on the propagation and overtopping of solitary waves when they encounter an impermeable seawall.The investigation has been conducted using ANSYS Fluent, a widely recognized commercial software.Although previous researchers have extensively used the two-dimensional volume of fluid (VOF) model, based on the Reynolds-Averaged Navier-Stokes (RANS) equations and the k-ε turbulence closure solver, this study fills the gap in the understanding of the stepped structure's effect.It shows a commendable agreement with experimental results, proving its reliability.Simulations were executed with varied configurations of stepped structures (Step width Sw=0.6 m, 1.2 m, 1.8 m, and Step height Sh=0.3 m, 0.6 m, 0.9 m), emulating tsunami waves of constant wave height and water depth over a stepped structure on a 1:20 sloped beach.Initially, the accuracy of the results was substantiated by comparing them with experimental and numerical data of the free surface and the distribution of the pressure field on the seawall.Numerical simulations, incorporating varying wave heights, water depths, and step heights, were performed to scrutinize the evolution of waves and the pressure exerted by waves impacting the seawall.

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 score0.244
Threshold uncertainty score0.536

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 head0.223
Teacher spread0.218 · 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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