Computational Optimization of Internal Combustion Engines (Paperback, Softcover reprint of the original 1st ed. 2011)

Computational Optimization of Internal Combustion Engines presents the state of the art of computational models and optimization methods for internal combustion engine development using multi-dimensional computational fluid dynamics (CFD) tools and genetic algorithms. Strategies to reduce computational cost and mesh dependency are discussed, as well as regression analysis methods. Several case studies are presented in a section devoted to applications, including assessments of: spark-ignition engines, dual-fuel engines, heavy duty and light duty diesel engines. Through regression analysis, optimization results are used to explain complex interactions between engine design parameters, such as nozzle design, injection timing, swirl, exhaust gas recirculation, bore size, and piston bowl shape. Computational Optimization of Internal Combustion Engines demonstrates that the current multi-dimensional CFD tools are mature enough for practical development of internal combustion engines. It is written for researchers and designers in mechanical engineering and the automotive industry.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Release date:	August 2016
Authors:	Yu Shi • Hai-Wen Ge • Rolf D. Reitz
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	309
Edition:	Softcover reprint of the original 1st ed. 2011
ISBN-13:	978-1-4471-6910-9
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Professional & Technical > Transport technology > Automotive technology > General Books > Professional & Technical > Mechanical engineering & materials > Mechanical engineering > Engines & power transmission > General Promotions
LSN:	1-4471-6910-7
Barcode:	9781447169109

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