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Record W3101677594

Kajian eksperimental Penggunaan Natural Gas dan Biosolarpada Mesin Diesel

2015· dissertation· id· W3101677594 on OpenAlexaboutno aff
Suardi

Bibliographic record

Venuenot available
Typedissertation
Languageid
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDiesel fuelPhysicsWaste managementEngineeringChemistry
DOInot available

Abstract

fetched live from OpenAlex

Cadangan minyak bumi Indonesia yang semakin menipis mendorong manusia untuk terus mencari dan mengembangkan bahan bakar alternatif, salah satunya adalah kombinasi sistem bahan bakar minyak bumi dan gas atau biasa disebut diesel dual fuel (DDF) system. Jenis penelitian yang digunakan adalah metode eksperimental dengan tujuan desain rancang bangun sistem bahan bakar hingga menghasilkan suplai yang optimal dengan memanfaatkan kombinasi bahan bakar antara biosolar dan CNG (Compressed natural gas). Instalasi system DDF ini sedikit berbeda dengan instalasi mesin pada umumnya karena menggunakan alat pengontrol otomasi yang mengatur timing injection bahan bakar CNG, sedangkan pada sistem bahan bakar biosolar dilakukan modifikasi injektor (packing Injektor) untuk mencapai tingkat komposisi bahan bakar yang ideal. Penelitian ini menunjukkan performa mesin yang paling baik pada sampel DF CNG 1 dengan SFC 263 gr/kW.h dan efisiensi termal sebesar 32,91%. Penambahan CNG pada mesin DDF memberikan tingkat efisiensi biosolar mulai dari 39% hingga 74% dibandingkan menggunakan bahan bakar biosolar murni. ====================================================================================================== Ariana, I.M. (2012), Sistem Permesinan Lanjut: a Lecture Note, Institut Teknologi Sepuluh November Surabaya Arismunandar, W, & Tsuda K. (1993).”Motor DieselPutaran Tinggi”. Pradaya Paramita.Jakarta Bao Yan, Sin Wei, Chengxun Xi, Yifu Liu, Ke Zeng, Ming-Chia Lai. (2011). “Experimental study of the effects of natural gas injection timing on the combustion performance and emissions of a turbocharged common rail dual-fuel engine”. Internasional Journal of applied energy Elsevier,Vol. 87, Hal. 297-304. Bernard Challen, Rodica Baranescu, (1999), Diesel Engine Reference Book, Second Edition.Oxford, UK. Biro Klasifikasi Indonesia (2013) BKI 2013 Part 1. Vol 24 Guidelines For The Use of Gas As Fuel For Ships 2013 Edition, Indonesia BP Statistical Review of World Energy. (2014) 63rd edition. London Chedthawut Poompipatpong. (2011). “A modified diesel engine for natural gas operation: Performance and emission tests”. Internasional Journal of applied energy Elsevier,Vol. 36, Hal. 6862-6866. Clarke, S. DeBruyn, J. (2012), Vehicle Conversion to Natural Gas or Biogas. OMAFRA Factsheet Order No.12-043, Canada Ditjen Migas (2015) Pertumbuhan-Kebutuhan-Gas-Bumi-2015-2030-Capai7-Persen. [Internet], Indonesia. Available From : [Accesed 24nd Januari 2015] Ehsan, Md. (2009), “Dual Fuel Performance of a Small Diesel Engine for Applications with Less Frequent Load Variations”. Internasional Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol 09 No 10, Bangladesh

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.015
GPT teacher head0.269
Teacher spread0.255 · 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
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
Published2015
Admission routes1
Has abstractyes

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