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Record W7126147310

RANCANG BANGUN PEMBANGKIT LISTRIKTENAGA UAP (PLTU) SEDERHANA MENGGUNAKAN BAHAN BAKAR LIMBAH OLI BEKAS

2025· other· en· W7126147310 on OpenAlexaboutno aff
DEVA GUNAWAN SULAIMAN, Herawati Afriyastuti, Amri Rosa M. Khairul

Bibliographic record

VenueUniversity of Bengkulu Scholar Repository (University of Bengkulu) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBar (unit)Electricity
DOInot available

Abstract

fetched live from OpenAlex

Keterbatasan sumber energi fosil dan meningkatnya limbah oli bekas menjadi latar belakang perlunya pemanfaatan energi alternatif yang ramah lingkungan. Penelitian ini bertujuan untuk menganalisis kinerja Pembangkit Listrik Tenaga Uap (PLTU) sederhana dengan menggunakan oli bekas sebagai bahan bakar alternatif. Penelitian ini dilakukan melalui proses perancangan dan pengujian sistem PLTU sederhana dengan variasi tekanan uap sebesar 1 bar, 2 bar, 3 bar, 4 bar, dan 5 bar. Hasil pengujian menunjukkan bahwa pada tekanan 1 bar dengan konsumsi bahan bakar 1,5 liter, turbin menghasilkan putaran sebesar 106,8 rpm dan generator sebesar 274,47 rpm, dengan tegangan 0 volt, daya 0 watt, dan efisiensi 0%. Pada tekanan 2 bar dengan konsumsi 2 liter, dihasilkan tegangan 6,27 volt, daya 1,7 watt, dan efisiensi 6,01%. Pada tekanan 3 bar, konsumsi 3 liter menghasilkan daya 13,4 watt dan efisiensi 29,13%. Selanjutnya, tekanan 4 bar dengan konsumsi 4,5 liter menghasilkan daya 24 watt dan efisiensi 36,75%. Tekanan tertinggi, yaitu 5 bar dengan konsumsi 6 liter, menghasilkan daya 31 watt dan efisiensi 36,41%. Berdasarkan hasil tersebut, dapat disimpulkan bahwa peningkatan konsumsi bahan bakar dan tekanan uap berbanding lurus terhadap peningkatan putaran turbin dan generator, tegangan, serta daya listrik yang dihasilkan. Sistem PLTU sederhana ini menunjukkan potensi sebagai alternatif pembangkit listrik skala kecil yang memanfaatkan limbah oli secara efektif. Kata Kunci : Pembangkit Listrik Tenaga Uap, Turbin De Laval, Oli Bekas, Efisiensi, Energi Alternatif.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0050.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.174
Teacher spread0.168 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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