Development and validation of an artificial intelligence platform for characterization of the exergy-emission-stability profiles of the PPCI-RCCI regimes in a diesel-methanol operation under varying injection phasing strategies: A Gene Expression Programming approach

[Display omitted] •Development of metamodels through Gene Expression Programming Metamodelling technique.•Characterization of PCCI-RCCI and intersperse combustion regimes.•Stability, emissions and sustainability index (exergy efficiency) calibration of the operations.•Comprehensive set of correlatio...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Fuel (Guildford) Ročník 299; s. 120864
Hlavní autoři:	Kakati, Dipankar, Roy, Sumit, Banerjee, Rahul
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.09.2021 Elsevier BV
Témata:	Artificial intelligence Decision making Diesel Diesel engines Divergence Emission Emissions Exergy Exergy efficiency Gene expression Gene expression programming Goodness of fit Injection Methanol Methanol-diesel dual fuel operation Opacity Overall reactivity PPCI-RCCI Response spectra Stability System characterization Thermodynamics Training System characterization CDC PPCI Methanol-diesel dual fuel operation FLR UHC FHR PDFC NOx COVIMEP Exergy efficiency Ro Gene expression programming MIA CNo AI PIA CAI PPCI-RCCI OFAT RCCI GEP PIM Exgeff Overall reactivity
ISSN:	0016-2361, 1873-7153
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!