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Research Papers: Gas Turbines: Microturbines and Small Turbomachinery

Multi-Objective Optimization of a Microturbine Compact Recuperator

[+] Author and Article Information
Diego Micheli, Valentino Pediroda

Dipartimento di Ingegneria Meccanica, Università degli Studi di Trieste, Trieste 34100, Italy

Stefano Pieri

Dipartimento di Ingegneria Navale, del Mare e per l’Ambiente, Università degli Studi di Trieste, Trieste 34100, Italy

www.esteco.com.

J. Eng. Gas Turbines Power 130(3), 032301 (Apr 02, 2008) (11 pages) doi:10.1115/1.2836479 History: Received May 25, 2007; Revised May 29, 2007; Published April 02, 2008

An automatic approach for the multi-objective shape optimization of microgas turbine heat exchangers is presented. According to the concept of multidisciplinary optimization, the methodology integrates a CAD parametric model of the heat transfer surfaces, a three-dimensional meshing tool, and a CFD solver, all managed by a design optimization platform. The repetitive pattern of the surface geometry has been exploited to reduce the computational domain size, and the constant flux boundary conditions have been imposed to better suit the real operative conditions. A new approach that couples cold and warm fluids in a periodic unitary cell is introduced. The effectiveness of the numerical procedure was verified comparing the numerical results with available literature data. The optimization objectives are maximizing the heat transfer rate and minimizing both friction factor and heat transfer surface. The paper presents the results of the optimization of a 50kWMGT recuperator. The design procedure can be effectively extended and applied to any industrial heat exchanger application.

Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

Design loop for the microturbine compact recuperator with the use of a process integration environment

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Figure 2

Geometric modeling and parameterization in Catia

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Figure 3

Bezier prameterization of the inlet surface

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Figure 4

A possible cross section obtained by setting the parameters

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Figure 5

Final CAD model for the recuperator (90deg case)

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Figure 6

Passage from CAD model to meshing model (blocks)

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Figure 7

Final mesh (case 90deg)

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Figure 8

Convergence profiles for the three objectives; it is possible to note how the multi-objective algorithm finds the compromises between the objective functions

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Figure 9

Convergence profiles for the design variables and t-student chart

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Figure 10

Pareto frontier graph; encircled in black the solutions belonging to the Pareto frontier

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Figure 11

Objective function convergence profiles for the second optimization

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Figure 12

Pareto frontier of the final optimization. Design 134 has been chosen as best configuration of the entire project.

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Figure 13

Grid independence comparison

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Figure 14

Initial geometry final optimized geometry (Design 134)

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Figure 15

Wall heat flux for the initial geometry (a) and the final optimized geometry (design 134) (b)

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Figure 16

Streamlines for both the geometries

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Figure 17

Cross sections for plot visualization

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Figure 18

Velocity contours at perpendicular cross sections for both geometries

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