A computational approach to flame hole dynamics using an embedded manifold approach

R. Knaus, C. Pantano

Research output: Contribution to journalArticlepeer-review

Abstract

We present a new numerical algorithm for tracking the evolution of flame holes in diffusion flames. The key element is the solution of an evolution equation for a flame state field defined on a complex moving surface. The surface itself can evolve in time and is defined implicitly as a level set of an associated Cartesian scalar field. The surface coordinates, or parameterization, do not need to be determined explicitly. Instead, the numerical method employs an embedding technique where the evolution equation is extended to the Cartesian space. In our application, the flame state field represents the chemical activity state of a diffusion flame; i.e. quenched and burning regions of the flame surface. We present a formulation that describes the formation, propagation, and growth of flame holes using edge-flame modeling in laminar and turbulent diffusion flames. The evolution equation is solved using a high-order finite-volume WENO method and a new extension algorithm defined in terms of propagation PDEs. The complete algorithm is demonstrated by tracking the dynamics of flame holes in a turbulent reacting shear layer and its applicability is also demonstrated in a turbulent reacting lifted jet simulation.

Original languageEnglish (US)
Pages (from-to)209-240
Number of pages32
JournalJournal of Computational Physics
Volume296
DOIs
StatePublished - Sep 1 2015

Keywords

  • Embedded manifold
  • Extinction/reignition
  • Flame hole dynamics
  • High-order WENO
  • Non-conservative systems
  • Turbulent diffusion flames

ASJC Scopus subject areas

  • Numerical Analysis
  • Modeling and Simulation
  • Physics and Astronomy (miscellaneous)
  • Physics and Astronomy(all)
  • Computer Science Applications
  • Computational Mathematics
  • Applied Mathematics

Fingerprint Dive into the research topics of 'A computational approach to flame hole dynamics using an embedded manifold approach'. Together they form a unique fingerprint.

Cite this