Challenges in kinetic optimization
Paper in proceeding, 2015

Computational fluid dynamics (CFD) is an important tool for designing and optimizing combustion systems. However, CFD modeling of industrial combustion applications is a computationally demanding task. Today the integration of kinetics into turbulent flame simulations is one of the most difficult challenges in the combustion community. Numerous methods have been proposed for integrating kinetics into turbulent reaction flow, such as tabulation ideas [1] and trajectories in composition space [2]. However, run-time and computational power becomes a more difficult issue when such methods must be used in unsteady simulations such as hybrid URANS/LES and LES models where the conservation equations must be solved at each time step. For this reason, it is often necessary to apply simplified reaction mechanisms to reduce the computing effort. Given a detailed mechanism for a specific fuel mixture, a global mechanism can then be generated for a wide range of operating conditions matching any number of combustion parameters. To simplify the reaction mechanism it is necessary to determine which parameters may be important for the specific combustion case. For example, when generating a global mechanism for use in premixed CFD simulations, laminar flame speed is important. Other parameters may be important, such as the species production rates, the temperature and the species concentrations at equilibrium, the residence time for ignition and the 1D profiles for species and temperatures for a wide range of initial temperature, ϕ and pressures.

CFD

Combustion

global reaction mechanisms

Author

Abdallah Abou-Taouk

Chalmers, Applied Mechanics, Fluid Dynamics

1st General Meeting & SECs for Power, Industry and Engines Workshop, 20150825, Thessaloniki, Greece.

Subject Categories

Mechanical Engineering

Energy Engineering

Fluid Mechanics and Acoustics

Driving Forces

Sustainable development

Areas of Advance

Transport

Production

Energy

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

More information

Created

10/8/2017