Computational Optimization of Internal Combustion Engines

Nonfiction, Science & Nature, Technology, Engineering, Automotive, Mathematics, Applied
Cover of the book Computational Optimization of Internal Combustion Engines by Yu Shi, Hai-Wen Ge, Rolf D. Reitz, Springer London
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Author: Yu Shi, Hai-Wen Ge, Rolf D. Reitz ISBN: 9780857296191
Publisher: Springer London Publication: June 22, 2011
Imprint: Springer Language: English
Author: Yu Shi, Hai-Wen Ge, Rolf D. Reitz
ISBN: 9780857296191
Publisher: Springer London
Publication: June 22, 2011
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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:

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.

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