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Record W2728656516 · doi:10.1109/cscs.2017.8

Real-Time Temperature Control of a One Dimensional Metal Plate

2017· article· en· W2728656516 on OpenAlexaff
D. Necsulescu, Bilal Jarrah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicNumerical methods in inverse problems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTaylor seriesMathematical analysisLaplace transformMathematicsInverse Laplace transformTransfer functionInversePole–zero plotHeat equationZero (linguistics)Control theory (sociology)GeometryControl (management)EngineeringComputer science

Abstract

fetched live from OpenAlex

One Dimensional metal plate heat equation is solved using Laplace transform. The transfer function for both direct and inverse problem were obtained as function of integer power of s from Zero-Pole and Taylor expansions of the resulting hyperbolic functions. Two types of expansions were compared, Zero-Pole and Taylor, using the root locus plots of inverse problem for different number of terms. As a result of this comparison Zero-Pole expansion was chosen to control the surface temperature of a thin plate on one side using the temperature measurement on the other side, based on both open loop and closed loop control schemes.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.060
GPT teacher head0.344
Teacher spread0.284 · 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 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

Citations2
Published2017
Admission routes1
Has abstractyes

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