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Record W2114048566 · doi:10.1243/09544119jeim672

A Galerkin-type finite element solution for simulation of mass diffusion in the application of tissue engineering: Heterogeneous and non-porous media

2009· article· en· W2114048566 on OpenAlexaff
Hadi Mohammadi, Kibret Mequanint, Fereshteh Bahramian

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2009
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsWestern University
Fundersnot available
KeywordsPorous mediumFinite element methodDiscontinuous Galerkin methodDiffusionType (biology)PorosityGalerkin methodComputer scienceMechanicsMaterials scienceApplied mathematicsMathematicsEngineeringPhysicsStructural engineeringGeologyComposite materialThermodynamics

Abstract

fetched live from OpenAlex

This study is an effort to produce a generic and comprehensive solution to the simulation of mass diffusion through a multiphasic and heterogeneous material model. A Galerkin-type finite element formulation is developed to solve Fick's equation for steady-state and time-dependent analysis. The effect of the interface in modelling of a liquid-solid medium is presented in this work. To show the robustness of the proposed approach, the gas exchange (oxygen and carbon dioxide) process through the capillary network between the alveolar membrane and red blood cells has been analysed and then validated with experimental data. The current work is a significant asset to modelling the diffusion of oxygen between cells and scaffolds in tissue engineering or tissue regeneration/repair studies. It is one step towards the development of high-order elements for application of the simulation of mass transfer through a multiphasic and porous model with varying degrees of interconnectivity and pore size for tissue engineering applications.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.433
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in MedicineSame topicElasticity and Material ModelingFrench-language works237,207