Research Papers: Gas Turbines: Turbomachinery

Static and Modal Topology Optimization of Turbomachinery Components

[+] Author and Article Information
Andrea Rindi

MDM Laboratory,
Department of Industrial Engineering,
University of Florence,
Via di Santa Marta 3,
Firenze 50139, Italy
e-mail: andrea.rindi@unifi.it

Enrico Meli

Assistant Professor
MDM Laboratory,
Department of Industrial Engineering,
University of Florence,
Via di Santa Marta 3,
Firenze 50139, Italy
e-mail: enrico.meli@unifi.it

Enrico Boccini

MDM Laboratory,
Department of Industrial Engineering,
University of Florence,
Via di Santa Marta 3,
Firenze 50139, Italy
e-mail: enrico.boccini@unifi.it

Giuseppe Iurisci

General Electric Nuovo Pignone,
Via Felice Matteucci,
Florence 50127, Italy
e-mail: giuseppe.iurisci@ge.com

Simone Corbò

General Electric Nuovo Pignone,
Via Felice Matteucci,
Florence 50127, Italy
e-mail: simone.corbo@ge.com

Stefano Falomi

General Electric Nuovo Pignone,
Via Felice Matteucci,
Florence 50127, Italy
e-mail: stefano.falomi@ge.com

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received February 25, 2016; final manuscript received April 22, 2016; published online May 24, 2016. Editor: David Wisler.

J. Eng. Gas Turbines Power 138(11), 112602 (May 24, 2016) (9 pages) Paper No: GTP-16-1085; doi: 10.1115/1.4033512 History: Received February 25, 2016; Revised April 22, 2016

The need to be more and more competitive is pushing the complexity of aerodynamic and mechanical design of rotating machines at very high levels. New concepts are required to improve the current machine performances from many points of view: aerodynamics, mechanics, rotordynamics, and manufacturing. Topology optimization is one of the most promising new approaches in the turbomachinery field for mechanical optimization of rotoric and statoric components. It can be a very effective enabler to individuate new paths and strategies, and to go beyond techniques already consolidated in turbomachinery design, such as parametric and shape optimizations. Topology optimization methods improve material distribution within a given design space (for a given set of boundary conditions and loads) to allow the resulting layout to meet a prescribed set of performance targets. Topology optimization allows also to change the topology of the structures (e.g., when a shape splits into two parts or develops holes). This methodology has been applied to a turbine component to reduce the static stress level and the weight of the part and, at the same time, to tune natural frequencies. Thus, the interest of this work is to investigate both static and dynamic/modal aspects of the structural optimization. These objectives can be applied alone or in combination, performing a single analysis or a multiple analysis optimization. It has been possible to improve existing components and to design new concepts with higher performances compared to the traditional ones. This approach could be also applied to other generic components. The research paper has been developed in collaboration with Nuovo Pignone General Electric S.p.A. that has provided all the technical documentation. The developed geometries of the prototypes will be manufactured in the near future with the help of an industrial partner.

Copyright © 2016 by ASME
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Fig. 1

Sizing, shape, and topology optimizations [1]

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Fig. 2

The studied components is a gas turbine disk of GE Oil & Gas

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Fig. 3

Topology optimization and rendering: (a) element density of the optimized disk model and (b) turbine disk rendering

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Fig. 4

General architecture of the procedure

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Fig. 6

Definition of design and nondesign space

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Fig. 7

Comparison between the (a) volume minimization and the (b) compliance minimization, as objective optimization function

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Fig. 8

The generalized shape design problem of finding the optimal material

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Fig. 10

Example of surfaces rendering

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Fig. 11

Modal topology optimization and stress distribution

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Fig. 12

Comparison between the benchmark test and the optimized model, in terms of natural frequencies close to the blade mode

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Fig. 13

Optimized model rendering




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