Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".