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Record W4386959852 · doi:10.9753/icce.v37.papers.38

FLEXIBLE FLUID-STRUCTURE INTERACTION OF A FLEXIBLE PLANT MODEL FOR NATURE-BASED SOLUTIONS

2023· article· en· W4386959852 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCoastal Engineering Proceedings · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsInstitut National de la Recherche ScientifiqueWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsDragPaceFluid–structure interactionComputer scienceMarshMarine engineeringVariety (cybernetics)Field (mathematics)Accretion (finance)SoftwareSalt marshEnvironmental scienceGeologyAerospace engineeringEngineeringOceanographyFinite element methodPhysicsEcologyMathematicsGeodesyStructural engineering

Abstract

fetched live from OpenAlex

Nature-based solutions (NBS) represent a new field of research and engineering applications, becoming increasingly popular in the coastal engineering field. Salt marsh restoration, an example of NBS, is particularly appealing due to the variety of benefits they can provide, especially their capacity to induce sediment accretion, potentially keeping pace with sea-level rise. This study investigates the applicability of the flexible fluid-structure (FSI) interaction module being developed for open-source software REEF3D to the motion of marsh plants under wave action using data from a physical model study performed by Paul et al. (2016). The model consistently overestimates the drag force response of a flexible plastic plant surrogate under wave action. This suggests that this new tool may not be suited for this case. However, further investigation must be performed to test the limits of the model’s application.

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.

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 score0.104
Threshold uncertainty score0.591

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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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