Scopus
YÖKSİS DOI Eşleşti
SJR Q2
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
Journal of Energy Resources Technology Transactions of the ASME · Aralık 2022
YÖKSİS Kayıtları
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
ASME International · 2022 SCI-Expanded
Dr. Öğr. Üyesi BAHAR SAYIN KUL →
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME · 2022 SCI-Expanded
Doç. Dr. ALİ YAŞAR →
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME · 2022 SCI-Expanded
Doç. Dr. ALİ YAŞAR →
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
ASME International · 2022 SCI-Expanded
Prof. Dr. MURAT CİNİVİZ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
2022 ISSN: 0195-0738 SCI-Expanded Q3
Doç. Dr. ALİ YAŞAR →
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
2022 ISSN: 0195-0738 SCI-Expanded Q3
Dr. Öğr. Üyesi BAHAR SAYIN KUL →
Modeling the Performance of Fuzzy Expert System for Prediction of Combustion, Engine Performance, and Exhaust Emission Parameters of a Spark Ignition Engine Fueled With Waste Bread Bioethanol-Gasoline Blends
2022 ISSN: 0195-0738 SCI-Expanded Q3
Prof. Dr. MURAT CİNİVİZ →
Makale Bilgileri
ISSN01950738
Yayın TarihiAralık 2022
Cilt / Sayfa144
Scopus ID2-s2.0-85144817818
Özet
This article focuses on the use of a rule-based Mamdani-type fuzzy expert system for the prediction of Pmax, HRRmax, ID, and CD as combustion parameters, BTE and BSFC as engine performance parameters, and CO, CO2, HC, and NOx as exhaust emission parameters of fuel blends formed by blending waste bread bioethanol with gasoline in different proportions. For modeling of 55 test conditions created by being operated test engine with 11 different test fuels under five different engine loads. As a result of the study, while combustion parameters were predicted with correlation coefficients in the range of 0.948-0.973% for waste bread bioethanol-gasoline blends, correlation coefficients for engine performance and exhaust emission parameters were in the range of 0.968-0.977% and 0.955-0.991% respectively. Similarly, the ranges of correlation coefficients obtained for sugar beet bioethanol-gasoline blends with fuzzy expert system were as follows: 0.967-0.971% for engine performance parameters, 0.955-0.978% for exhaust emission parameters, and 0.951-0.964% for combustion parameters. These results prove that costly and labor-intensive engine tests can be predicted with minimum effort and high accuracy with the developed model.
Yazarlar (3)
1
Ali Yasar
2
Bahar Sayın Kul
3
Murat Ciniviz
Anahtar Kelimeler
air emissions from fossil fuel combustion
alternative energy sources
fuel combustion
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Journal of Energy Resources Technology
Q2
SJR Skoru0,464
H-Index74
YayıncıAmerican Society of Mechanical Engineers (ASME)
ÜlkeUnited States
Energy Engineering and Power Technology (Q2)
Geochemistry and Petrology (Q2)
Mechanical Engineering (Q2)
Fuel Technology (Q3)
Renewable Energy, Sustainability and the Environment (Q3)
Metrikler
3
Atıf
3
Yazar
3
Anahtar Kelime