Multiobjective Design Optimization of Merging Configuration for an Exhaust Manifold of a Car Engine

  • Masahiro Kanazaki
  • Masashi Morikaw
  • Shigeru Obayashi
  • Kazuhiro Nakahashi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2439)


Multiobjective design optimization system of exhaust manifold shapes for a car engine has been developed using Divided Range Multiobjective Genetic Algorithm (DRMOGA) to obtain more engine power as well as to achieve less environmental impact. The three-dimensional manifold shapes are evaluated by the unstructured, unsteady Euler code coupled with the empirical engine cycle simulation code. This automated design system using DRMOGA was confirmed to find Pareto solutions for the highly nonlinear problems.


Pareto Front Multiobjective Optimization Pareto Solution Automate Design System Exhaust Manifold 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Masahiro Kanazaki
    • 1
  • Masashi Morikaw
    • 2
  • Shigeru Obayashi
    • 1
  • Kazuhiro Nakahashi
    • 2
  1. 1.Institute of Fluid ScienceTohoku UniversitySendaiJapan
  2. 2.Dept. of Aeronautics and Space EngineeringTohoku UniversitySendaiJapan

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