0
Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

Combustor Design Optimization Using Co-Kriging of Steady and Unsteady Turbulent Combustion

[+] Author and Article Information
Moresh J. Wankhede

 University of Southampton, Southampton, SO17 1BJ United KingdomMoresh.Wankhede@soton.ac.uk

Neil W. Bressloff

 University of Southampton, Southampton, SO17 1BJ United KingdomN.W.Bressloff@soton.ac.uk

Andy J. Keane

 University of Southampton, Southampton, SO17 1BJ United KingdomAndy.Keane@soton.ac.uk

J. Eng. Gas Turbines Power 133(12), 121504 (Sep 12, 2011) (11 pages) doi:10.1115/1.4004155 History: Received April 15, 2011; Revised April 27, 2011; Published September 12, 2011; Online September 12, 2011

In the gas turbine industry, computational fluid dynamics (CFD) simulations are often used to predict and visualize the complex reacting flow dynamics, combustion environment and emissions performance of a combustor at the design stage. Given the complexity involved in obtaining accurate flow predictions and due to the expensive nature of simulations, conventional techniques for CFD based combustor design optimization are often ruled out, primarily due to the limits on available computing resources and time. The design optimization process normally requires a large number of analyses of the objective and constraint functions which necessitates a careful selection of fast, reliable and efficient computational methods for the CFD analysis and the optimization process. In this study, given a fixed computational budget, an assessment of a co-Kriging based optimization strategy against a standard Kriging based optimization strategy is presented for the design of a 2D combustor using steady and unsteady Reynolds-averaged Navier Stokes (RANS) formulation. Within the fixed computational budget, using a steady RANS formulation, the Kriging strategy successfully captures the underlying response; however with unsteady RANS the Kriging strategy fails to capture the underlying response due to the existence of a high level of noise. The co-Kriging strategy is then applied to two design problems, one using two levels of grid resolutions in a steady RANS formulation and the other using steady and unsteady RANS formulations on the same grid resolution. With the co-Kriging strategy, the multifidelity analysis is expected to find an optimum design in comparatively less time than that required using the high-fidelity model alone since less high-fidelity function calls should be required. However, using the applied computational setup for co-Kriging, the Kriging strategy beats the co-Kriging strategy under the steady RANS formulation whereas under the unsteady RANS formulation, the high level of noise stalls the co-Kriging optimization process.

Copyright © 2011 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Figure 1

Computational domain of the combustor with a flame-stabilizer step (All dimensions in mm)

Grahic Jump Location
Figure 2

Outlet temperature profiles as captured by different mesh sizes using steady RANS

Grahic Jump Location
Figure 3

Area-weighted average temperature (Ta ) fluctuations at the outlet as captured by different time step size URANS simulations

Grahic Jump Location
Figure 4

Reactive flowfield settlement into meta-stable state as captured by time step size 1e–05 URANS simulation

Grahic Jump Location
Figure 5

Position of the flame front inside the combustor as captured by steady RANS

Grahic Jump Location
Figure 6

Outlet temperature profile of the combustor (steady RANS)

Grahic Jump Location
Figure 7

Pulsed flame front captured by URANS over one excitation cycle (Vin  = 13.3 m/s, Tin  = 300 K, Φ = 0.86, excitation amplitude = 50%, frequency = 175 Hz)

Grahic Jump Location
Figure 8

Inlet velocity sinusoidal forcing function cycle (Vin  = 13 m/s, T = 0.0057s and Amp = 50%)

Grahic Jump Location
Figure 9

Outlet temperature profile of the combustor corresponding to humming cycle points (c.f. Fig. 8)

Grahic Jump Location
Figure 10

Humming cycle captured by unsteady RANS in comparison with experimental data of Keller [22] (Time interval between frames: 1ms)

Grahic Jump Location
Figure 11

Flame-stabilizer step design parameterization using spline control points

Grahic Jump Location
Figure 12

Comparison between steady RANS and time-averaged unsteady RANS baseline design outlet temperature profile against target outlet temperature profile

Grahic Jump Location
Figure 13

Optimization strategy based on Kriging response surface model

Grahic Jump Location
Figure 14

Comparison of Kriging RSM captured using fixed computational budget of six DoE + 15 update cycle runs against Kriging RSM of 100 CFD runs using a 10x10 regular grid data points

Grahic Jump Location
Figure 15

Optimization search histories over a fixed computational budget of sixDoE + 15 update cycle (45 update points) runs

Grahic Jump Location
Figure 16

Optimization strategy based on co-Kriging response surface model

Grahic Jump Location
Figure 17

Kriging response surfaces (overlapped) captured by low-fidelity and high-fidelity models over 10x10 grid data

Grahic Jump Location
Figure 18

Kriging and co-Kriging strategies optimization search histories over a fixed computational budget of DoE + 15 update cycles using three different initial samples

Grahic Jump Location
Figure 19

Kriging response surfaces (overlapped) captured by low-fidelity and high-fidelity models over 10x10 grid data

Grahic Jump Location
Figure 20

Kriging and co-Kriging strategies optimization search histories over a fixed computational budget of DoE + 15 update cycle runs using three different initial samples

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In