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Record W2738373551

Análisis del intercambio de calor e incrustaciones en un sistema de enfriadores de ácido sulfhídrico

2017· article· es· W2738373551 on OpenAlexaff
Andrés A. Sánchez-Escalona, Ever Góngora-Leyva, Carlos Zalazar-Oliva, Edel Álvarez-Hernández

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2017
Typearticle
Languagees
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsNickel Institute
Fundersnot available
KeywordsFoulingHeat exchangerHeat transferShell and tube heat exchangerPlate heat exchangerMaterials scienceChemistryThermodynamicsPhysicsMembrane
DOInot available

Abstract

fetched live from OpenAlex

"Los enfriadores de ácido sulfhídrico (intercambiadores de calor de tubo y coraza enchaquetados) tienen la función de enfriar desde 416,15 K hasta 310,15 K el gas producido, así como de separar el azufre arrastrado por los gases que salen de la torre del reactor. Mediante el método de experimentación pasiva se realizó la investigación en un banco de enfriadores en operaciones, con el objetivo determinar los coeficientes de transferencia de calor y el grado de incrustaciones basado en su resistencia térmica. Se corroboró que la operación de estos equipos fuera de los parámetros de diseño provoca incremento de la temperatura del gas a la salida y del arrastre de azufre en estado líquido. La pérdida de eficiencia está influenciada por la presencia de elementos incrustantes en el fluido, que provoca variaciones en el coeficiente global de transferencia de calor. Se estableció la tendencia lineal de resistencia térmica de las incrustaciones en función del tiempo para tres valores de flujo de gas."

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 score0.002
Threshold uncertainty score0.004

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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