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SCI-Expanded JCR Q3 Özgün Makale Scopus
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 Cilt 144 Sayı 12
Scopus Eşleşmesi Bulundu
1
Atıf
144
Cilt
Scopus Yazarları: Ali Yasar, Bahar Sayın Kul, Murat Ciniviz
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.
Anahtar Kelimeler (Scopus)
air emissions from fossil fuel combustion alternative energy sources fuel combustion

Anahtar Kelimeler

air emissions from fossil fuel combustion alternative energy sources fuel combustion

Makale Bilgileri

Dergi ASME International
ISSN 0195-0738
Yıl 2022 / 12. ay
Cilt / Sayı 144 / 12
Makale Türü Özgün Makale
Hakemlik Hakemli
Endeks SCI-Expanded
JCR Quartile Q3
TEŞV Puanı 54,00
Yayın Dili İngilizce
Kapsam Uluslararası
Toplam Yazar 3 kişi
Erişim Türü Basılı+Elektronik
Erişim Linki Makaleye Git
Alan Mühendislik Temel Alanı Makine Mühendisliği

YÖKSİS Yazar Kaydı

Yazar Adı YAŞAR ALİ, SAYIN KUL BAHAR, CİNİVİZ MURAT
YÖKSİS ID 6786634

Metrikler

Scopus Atıf 1
JCR Quartile Q3
TEŞV Puanı 54,00
Yazar Sayısı 3