MétaCan
Menu
Back to cohort
Record W4253426017 · doi:10.22215/etd/2014-10094

Cartilage Simulation Using Smoothed Particle Hydrodynamics

2014· dissertation· en· W4253426017 on OpenAlexaff
Philip J. Boyer

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsCarleton University
Fundersnot available
KeywordsSmoothed-particle hydrodynamicsFinite element methodCartilageArticular cartilageRepresentation (politics)IndentationCompression (physics)Stress (linguistics)OsteoarthritisComputer scienceMechanicsBiomedical engineeringMaterials scienceEngineeringStructural engineeringPhysicsMedicineAnatomyComposite material

Abstract

fetched live from OpenAlex

Abnormal bone growth in the hip joint causing increased stress during motion is a condition known as Femoral Acetabular Impingement (FAI). FAI is considered to be a primary cause of osteoarthritis in this joint due to wear of articular cartilage. A computer simulation for preoperative evaluation of FAI requires the representation of cartilage for accurate force and stress determination, but current methodologies such as the finite element method (FEM) do not simultaneously provide both the accuracy and the computational speed necessary for such a representation. In this thesis, a fast and accurate simulation of articular cartilage is proposed using adaptations of previous research and unique extensions to the method of smoothed particle hydrodynamics (SPH). Strong correlation is found between simulations of compression and indentation experiments of cartilage with previously published experimental results, with simulations operating in excess of real-time rates.

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 score0.078
Threshold uncertainty score0.917

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 head0.011
GPT teacher head0.266
Teacher spread0.254 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicFluid Dynamics Simulations and InteractionsFrench-language works237,207