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Record W1596796141

An Undergraduate Course in Modeling and Simulation of Multiphysics Systems

2010· article· en· W1596796141 on OpenAlexaff
Estanislao Ortíz‐Rodríguez, Jorge Vázquez-Arenas, Luis Ricardez‐Sandoval

Bibliographic record

VenueChemical Engineering Education · 2010
Typearticle
Languageen
FieldEngineering
TopicNanotechnology research and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMultiphysicsCourse (navigation)CurriculumComputer scienceModeling and simulationOdeSoftwareSystems engineeringSoftware engineeringMechanical engineeringSimulationEngineeringFinite element methodAerospace engineeringProgramming languageApplied mathematics
DOInot available

Abstract

fetched live from OpenAlex

An overview of a course on modeling and simulation offered at the Nanotechnology Engineering undergraduate program at the University of Waterloo is presented in this paper. The motivation for having this course in the undergraduate nanotechnology curriculum, the course structure and its learning objectives are discussed. Further, one of the computational laboratories covered in the course, a relatively simple drug release model, is presented in this work. This computational laboratory is designed to expose the students to the modeling and simulation of a macroscopic model, given in the form of an ODE, coupled with one of the boundary conditions of the system’s microscopic behavior, given in the form of a PDE. The implementation of the proposed drug release model is performed in COMSOL, a commercial software application suitable to train students in the modeling and simulation of micro and nano systems.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.044
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0440.020

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 head0.007
GPT teacher head0.265
Teacher spread0.258 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2010
Admission routes1
Has abstractyes

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