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Record W4367171937 · doi:10.18280/mmep.100243

Computational Calculation on the Shell and Tube-Type Heat Exchanger for Lanthanum Oxide (La2O3) Nanoparticle Production Process for Energy-Related Material Application

2023· article· en· W4367171937 on OpenAlexvenueno aff
Asep Bayu Dani Nandiyanto, Irine Sofianty, Adani Gina Puspita Sari, Rofi Fadilah Madani, Fitri Febrianti, Risti Ragadhita, Teguh Kurniawan, Rizky Jumansyah, E S Soegoto, Senny Luckyardi, Muhammad Aziz

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersUniversitas Pendidikan IndonesiaBadan Riset dan Inovasi Nasional
KeywordsLanthanumLanthanum oxideShell (structure)Tube (container)Materials scienceNanoparticleShell and tube heat exchangerHeat exchangerProcess (computing)Production (economics)OxideChemical engineeringNuclear engineeringProcess engineeringComposite materialNanotechnologyMechanical engineeringMetallurgyChemistryInorganic chemistryComputer scienceEngineering

Abstract

fetched live from OpenAlex

This paper introduced a design of a heat exchanger to get an optimum heat transfer enhancement technique that can be used for the production of lanthanum oxide (La2O3).The shell and tube type was selected since this type is one of the effective types for making excellent heat transfer, which was then compared to the Tubular Exchanger Manufacturers Association (TEMA) standard to obtain the dimensional specifications of the heat exchanger device.Several parameters were calculated to evaluate the performance of the designed heat exchanger.Numerical calculation obtained from the heat exchanger containing 138 tubes can be used to maintain the temperature in the reactor (prospective temperature can change from 40 to 60℃ with rapid heating) using heating liquid (controlling by transferring heat from 100 to 70℃) with the effective value of 96%.This study can be used as a reference for supporting information in the current issue of the need for the large production of La2O3 particles.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.030
GPT teacher head0.249
Teacher spread0.219 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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