advanced turbulence models for emission modelling...

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Antti Oksanen 10.2.2006Institute of Energy and Process Engineering

ADVANCED TURBULENCE MODELS FOR EMISSION MODELLING IN GAS COMBUSTION

TEKES project 40190/05Antti Oksanen, project leader, Tampere University of Technology

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Backgrounds

• Financing TekesKvaerner Power Oy, Andritz Oy, Vattenfall Utveckling Ab

• Budget 418 k€• Period 2005-2006• Participants (researchers)

TUT, Institute of Energy and Process Engineering (Satu Palonen, Ville Tossavainen)HUT, Laboratory of Applied Thermodynamics (Petri Majander)Åbo Akademi, PCC, Combustion and Materials Chemistry (Anders Brink)Stanford University, Research Group of Computational Energy Sciences (CES), USA, Prof. Heinz Pitsch

A part of Flow Physics and Computation Division, closely connected to Turbulence Research Center andCenter for Integrated Turbulence Simulations

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Aim of the Research

• To give better description and understanding of the interaction between chemistry and turbulence university LES (Large Eddy Simulation) code (TUT)

• To apply for emission formation and SNCR (Selective Non-Catalytic Reduction) process with detailed experimental techniques (TUT)

• The experiments provide validation data for LES computations (TUT)• To study the reduction phenomenon of nitric oxide and ammonia

with LES turbulence modelling in laboratory reactor environment comparison also with RANS computations (TUT)

• To model the reactor flow conditions without combustion using TKK LES code (TKK)

• To model the flame experimentally well studied using LES and RANS of commercial code (ÅA)

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Pilot Reactor (TUT)

• BurnerOilon GP-6.20H: 60-160 kWFuel: Liquefied petroleum gas, LPG

• Dimensions of the reactorInside cross section: 400 × 400 mm2

Outside cross section: 760 × 760 mm2

Total height: 2830 mm

• Air splittingPrimary/secondary air: 70 %/30 %

• Secondary air system8 pipes in both sides3 pipe diameters: 8, 10, 12 mm

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Pilot Reactor Measurements (TUT)

• LDA (Laser Doppler Anemometer)Two velocity components

• Concentrations22 measurements points at the reaction zone

• Temperature measurementsK-type thermocouples

• Flow ratesPrimary and secondary airNO and NH3

Fuel

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Computational Domains of Pilot Reactor (TUT)

© Satu Palonen

Pilot reactor in vertical directionRANS simulations

LES simulations

Earlier LES simulations

Pilot reactor in horizontal direction

Secondary air pipes

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Numerical Simulations in Pilot Reactor (TUT)

• Contribution is to model reactions between nitric oxide and ammonium (SNCR-process) using LES turbulence modelling (Stanford code)

• Computational flow cases:CASE 1: Cold flow without reactionsCASE 2: Reactive flow with substoichiometric primary air and staged secondary air feedingCASE 3: Reactive flow with added nitric oxide (NO) and ammonium (NH3) feedings main contribution of the research

• Each case is studied with three different jet mass flow rates (ReD = 10000, 12000 and 15000)

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• Both traditional RANS (Reynolds Averaged Navier-Stokes) and LES computations are performed

• RANS simulations:Whole turbulence length scale is modelledComputations made with commercial FLUENT 6.2 software

• LES simulations:Large scales are solved and small scales modelledLES computations are performed with academic code ”CHARLES” developed at Stanford UniversityTurbulence-chemistry interaction is based on laminar flamelet model Results are validated against experimental data from Osbourne pilot reactor at TUT

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Stanford Structured LES Code ”CHARLES” [1]

• Based mainly on Charles Pierce’s PhD work(http://www.stanford.edu/group/ctr/pdf/charles_pierce_thesis.pdf)

Solves 3D (cartesian/cylinder) turbulent flow using Large Eddy Simulation with dynamic subgrid-scalemodel (Germano et al., 1991)Chemistry/turbulence–interaction is modelled with fast chemistry, steady flamelets or progress-variable/unsteady flamelet models Currently problems to run parallel jobs using more than two processors

Velocity iso-surfacecolored by pressure

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Stanford Structured LES Code ”CHARLES” [2]

• Wall boundary conditions were modified to take into account secondary air inlets

Multiple round inlets will be inserted with velocity profilesCurrent velocity boundary conditions are stationary

• Implementation of test caseMain flow Reynolds number Remain = 5000 (Ujet = 2 x Umain)128 x 64 x 64 mesh (~ 2 x 1 x 1)2000 time steps ~ 30 minutes computation on 2 CPUs

Instantaneous y-velocity iso-surfacecolored by pressure

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RANS Computations [1]

• Several different mesh constructions were build for the reactor for comparison• Results of hex-core (hybrid) meshes were poor

Unstructured cells near walls make jets behave unphysical

Contours of x-velocity, 3rd jet from wall (d=8mm) Contours of x-velocity, 3rd jet from wall (d=12mm)

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• Block-structured grid was build around one secondary air jetGood accuracy, but too complex for total 16 jets this approach was abandoned

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• Present grid consists of several non-conformal (Chimera) meshes which is a good compromise between grid size and accuracy

Grid interface

Closer look of non-conformal mesh near secondary jet

Non-conformal grid interfaces

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Multiple Opposing Jets in a Cross-Flow (TKK)

• Inert Large Eddy Simulation of Osbourne reactor flow with TKK code• Three opposing pairs of jets included

2 m

V

U

V

0.4 m

Scalar contours

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Multiple Opposing Jets in a Cross-Flow (TKK)

• Current mesh includes 4 million control volumes• The flow possesses large range of scale a challenging case• IBMSC parallel computer of CSC applied• Figure below illustrates penetration of secondary air in main flow

Momentum flux in a secondary air pipe

Contours of mass (50%) coming from pipes

Secondary air pipes

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Test Case: Sandia Flame D (ÅA)

Dimensions: Nozzle diameter = 7.2 mm Pilot diameter = 18.2 mm

Main jet: 25% CH4, 75% air

Reaction kinetics: LES&RANS

Scalar Measurements: Raman/Rayleigh/LIF measurements of F, T, N2, O2, CH4, CO2, H2O, H2, CO, OH, and NO were obtained with a spatial resolution of 0.75 mm.

Velocity Measurements: Two-component LDV measurements were carried out at the Technical University of Darmstadt.

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Test Case: Sandia Flame D (ÅA)

Conclusions:

• LES temperature predictions in better agreement with measurementthan RANS

• Both models with 4-step chemistry over-predict CO mass fraction• LES computing time >1000 CPU hours (~0.1 s), statistics collected

for 100 CPU hours, too short! • RANS computing time ~ 1 CPU hour• LES only motivated for advanced application (complex chemistry,

time dependent applications)

advanced turbulence models for emission modelling...

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