A Variable-Complexity Modeling Approach to Scramjet Fuel Injection Array Design Optimization

Abstract

The analysis of fuel air mixing in a scramjet is often accomplished either with Computational Fluid Dynamics (CFD) algorithms or through experimental research. These approaches, while accurate and reliable, are extremely expensive and thus not well suited for use with conventional design optimization methods. In this investigation, Variable Complexity Modeling (VCM) is used to significantly reduce the number of complex, expensive analyses required to optimize the design of a scramjet fuel injection array. A design problem formulation for a lateral transverse injection array is developed and a VCM approach to design optimization is conducted in two stages. Initially, a simplified analysis model is used to provide relatively inexpensive predictions of design fuel air mixing characteristics. A parametric analysis is conducted to explore the design region, and a preliminary optimal design is found using both Sequential Quadratic Programming and a Genetic Algorithm. In the second stage, response surface methodology is supplemented with preliminary stage information to minimize the number of expensive analyses required to finalize the design. It is shown that only 25 design evaluations are required to develop a near optimal design.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1998
Accession Number
ADA342233

Entities

People

  • Michael D. Payne

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Combustors
  • Computational Fluid Dynamics
  • Experimental Design
  • Fluid Dynamics
  • Fuel Injection
  • Genetic Algorithms
  • Heuristic Methods
  • Mathematical Models
  • Mathematical Programming
  • Operations Research
  • Optimization
  • Quadratic Programming
  • Ramjet Engines
  • Supersonic Combustion Ramjet Engines

Fields of Study

  • Engineering

Readers

  • Computational Fluid Dynamics (CFD)
  • Operations Research
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Biotechnology