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Record W1684612778 · doi:10.5539/mer.v5n1p42

Laws of Radiation From Large Gas Volumes and Claculation of Heat Transfer in Steam Boiler Boxes

2015· article· en· W1684612778 on OpenAlexvenueno aff
А. Н. Макаров

Bibliographic record

VenueMechanical Engineering Research · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsBoiler (water heating)TorchHeat transferThermal radiationCombustionRadiant heatCombustion chamberRadiationNuclear engineeringMechanicsEnvironmental scienceThermodynamicsWaste managementMaterials scienceMechanical engineeringChemistryEngineeringPhysicsNuclear physicsComposite material

Abstract

fetched live from OpenAlex

The progress in the development of methods for calculating heat transfer in torch furnaces, fireboxes, and combustion chambers is analyzed. In the XIX-XX centuries calculations of radiative heat exchange were followed the methods based on the laws of radiation from black body, disclosed in the XVII-XX. It is substantiated that there is crisis of methods for calculating heat transfer in torch furnaces, fire boxes and combustion chambers. In the early XXI century the author of this manuscript disclosed the laws of radiation from torch gas volumes, described in the article.

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)0.005
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.292
Teacher spread0.257 · 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

Citations6
Published2015
Admission routes1
Has abstractyes

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