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A validated DEM modelling framework on plate and pile penetrations in a double-layer scour protection system

2025· article· en· W4406057869 on OpenAlexaff
Hao Shi, Cihan Cengiz, Giulia Macaro, Mario Martinelli, Jovana Jovanova, Dingena Schott

Bibliographic record

VenueOcean Engineering · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsCarleton University
Fundersnot available
KeywordsPileLayer (electronics)Structural engineeringGeotechnical engineeringMarine engineeringEngineeringGeologyForensic engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Monopiles are the dominant foundation type for offshore wind turbines, accounting for approximately 80% of the installed capacity. Installing offshore monopile foundations on seabeds susceptible to scour erosion requires monopiles to penetrate several pre-installed scour protection rock layers before securing them into the seabed. The accurate prediction of the pile penetration resistance is crucial to ensure successful monopile installations. To complement, and potentially reduce the dependence on the costly and labour-intensive experimental small-scale penetration tests, a numerical model has been developed using the Discrete Element Method (DEM) that captures the discrete nature of interactions between rocks and piles and predicts the resistance during the penetration process. The developed DEM model includes armour and filter rocks represented by multispheres and sand particles represented by spheres. A multistage calibration, verification and validation DEM modelling framework is proposed and examined with small-scale penetration tests conducted using plates and piles in a double-layer scour protection configuration. The sand material model is calibrated and verified using penetrometer tests and the rock material models are calibrated and verified using a plate penetration test. The DEM model with three verified materials predicts the penetration resistance well in small-scale pile penetration tests and proves the validity of the proposed framework. The DEM model presented in this paper facilitates the modelling in areas where traditional continuum-based numerical methods give less accurate predictions and provide insights that are difficult or nearly impossible to obtain through experimental methods. • A novel DEM modelling framework is proposed for penetration in scour protection layers. • Various experiments are used for multistage DEM model calibration, verification and validation. • Scour protection rocks and sand are modelled using multispheres and spheres, respectively. • Different optimisation methods are deployed to calibrate the unknown model parameters. • The calibrated DEM model predicts well the penetration behaviours of different geometries.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2025
Admission routes1
Has abstractyes

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