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Record W4303449575 · doi:10.1142/s0218202522500592

Fluid–structure interaction modeling with nonmatching interface discretizations for compressible flow problems: Computational framework and validation study

2022· article· en· W4303449575 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

VenueMathematical Models and Methods in Applied Sciences · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Analysis Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFluid–structure interactionIsogeometric analysisCompressible flowFinite element methodCompressibilityBenchmark (surveying)Applied mathematicsFlow (mathematics)Computer scienceWork (physics)Block (permutation group theory)Incompressible flowInterface (matter)Mathematical optimizationMathematicsMechanicsPhysicsGeometryGeology

Abstract

fetched live from OpenAlex

This work presents a strongly-coupled fluid–structure interaction (FSI) formulation for compressible flows that is developed based on an augmented Lagrangian approach. The method is suitable for handling problems that involve nonmatching fluid–structure interface discretizations. In this work, the fluid is modeled using a stabilized finite element method for the Navier–Stokes equations of compressible flows and is coupled to the structure, which is formulated using isogeometric Kirchhoff–Love shells. The strongly-coupled system is solved using a block-iterative approach. The proposed method is validated using two compressible flow benchmark problems to assess the accuracy of the developed formulation.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.440
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.046
GPT teacher head0.382
Teacher spread0.335 · 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