Reduced Basis and Stochastic Modeling of Liquid Propellant Rocket Engine as a Complex System

Abstract

The four-institution research team has developed a framework for stochastic analysis of nonlinear combustion instability with triggering and in the use of reduced-basis models (RBM), large-eddy simulations, and multi-scale asymptotic models for the analysis. Results published during these three years and ongoing researches are briefly discussed and addenda with more detail are provided.

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Document Details

Document Type
Technical Report
Publication Date
Jul 02, 2015
Accession Number
AD1013234

Entities

People

  • A. Sideris
  • D. Ota
  • D. R. Kassoy
  • P. Tudisco
  • Pavel P. Popov
  • R. Munipalli
  • Rajesh Ranjan
  • S. Srinivasan
  • Suresh Menon
  • T. Dawson
  • William A. Sirignano
  • Zengqian Liu

Organizations

  • University of California, Irvine

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Boundary Layer
  • Combustion
  • Computational Fluid Dynamics
  • Computational Science
  • Energy Transfer
  • Equations Of State
  • Fluid Dynamics
  • Fluid Flow
  • Heat Of Combustion
  • Heat Transfer
  • Large Eddy Simulation
  • Mathematical Models
  • Physics Laboratories
  • Rocket Engines
  • Standing Waves
  • Thermodynamics
  • Turbulent Mixing

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Technical Research and Report Writing.