MétaCan
Menu
Back to cohort
Record W7132880045

A parallel multigrid method for predicting compressible flow in turbomachinery

2004· dissertation· W7132880045 on OpenAlexaff
Eric L Li

Bibliographic record

VenueTSpace · 2004
Typedissertation
Language
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsCanadian Association for Laboratory Animal SciencePublic Health Ontario
Fundersnot available
KeywordsMultigrid methodInviscid flowConvergence (economics)Domain decomposition methodsTurbomachineryFlow (mathematics)ComputationGridCompressible flowAcceleration
DOInot available

Abstract

fetched live from OpenAlex

A parallel multigrid method is developed for solving two-dimensional inviscid compressible flows on body-fitted multi-block mesh. The method utilizes a Godunov-type up-winding scheme, exact and approximate Riemann solvers and limited reconstruction to achieve higher-order spatial accuracy. The computation is carried out on a quadrilateral grid that is divided into blocks to facilitate scalable performance on parallel computers. A Full Approximation Storage multigrid scheme is employed to accelerate the convergence of an explicit multistage time integration scheme. Several example cases, including the flow about NASA rotor 67, are used to validate the parallel algorithm and to investigate its convergence and parallel performance. The effectiveness of the multigrid method is demonstrated and good convergence acceleration is obtained, particularly for problems of increasing complexity. The parallel efficiency of the method is found to be dependant on the problem size. The potential of the algorithm for solving large scale and three-dimensional problems is indicated.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.083
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.036
GPT teacher head0.412
Teacher spread0.376 · 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.

Study designSimulation or modeling
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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicAdvanced Numerical Methods in Computational MathematicsFrench-language works237,207