Research Papers

Integrated Design and Optimization of Gas Bearing Supported Rotors

[+] Author and Article Information
J. Schiffmann1

 Fischer Engineering Solutions AG, 3360 Herzogenbuchsee, Switzerlandjurg@mit.edu, juerg.schiffmann@fischerprecise.ch

D. Favrat

Industrial Energy Systems Laboratory (LENI), Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerlanddaniel.favrat@epfl.ch


Corresponding author. Present address: Department of Aeronautics and Astronautics, Gas Turbine Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139.

J. Mech. Des 132(5), 051007 (May 03, 2010) (11 pages) doi:10.1115/1.4001381 History: Received November 23, 2009; Revised February 28, 2010; Published May 03, 2010; Online May 03, 2010

The design of direct driven turbomachinery is an interdisciplinary task. Standard design procedures propose to split such systems into subcomponents and to design each one individually. This common procedure, however, tends to neglect the interactions between the different components leading to suboptimal solutions. The authors propose an approach based on the integrated philosophy for designing and optimizing gas bearing supported rotors. Based on the choice for herringbone grooved journal and spiral groove thrust bearings, the modeling procedure for predicting their properties and the linking to the rotordynamic behavior of a generic rotor supported on gas lubricated bearings is provided. The global model for gas bearing supported rotors is linked to a multiobjective optimizer for maximizing the dynamic stability and for minimizing the windage losses of the rotor and of the bearings. Two typical rotor layouts have been included in the optimization. The geometry of a proof of concept system, that has been designed previously using the fragmented component view, is represented as a comparison to the proposed integrated approach. It is shown that the integrated solution allows to reduce the windage losses by 25% or to increase the stability margin by 35%, emphasizing the advantage of the proposed integrated design tool.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

The compressor unit with its main subcomponents and their mutual interactions

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Figure 2

Definition of the geometry of a spiral groove thrust bearing and of a herringbone grooved journal bearing

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Figure 3

The approximate thermal analysis of a possible rotor layout based on a thermal resistance network approach. The solid lines indicate thermal resistances between the nodes. Qgen represents locations of significant power losses.

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Figure 4

The rotor model including the bearing stiffness and damping as well as soft bearing support

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Figure 5

The flow chart for calculating the whirl speed map and the corresponding stability as a function of the rotational speed of a gas bearing supported rotor

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Figure 6

The influence between the different elements composing the compressor unit. The dotted frame represents the boundary of the domain included in this particular integrated design and optimization process.

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Figure 7

The two analyzed layouts for the gas bearing supported spindle system and the corresponding variables

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Figure 8

The Pareto curve for the optimized spindle unit after 100,000 iterations for rotor architectures 1 and 2 as a function of the logarithmic decrement (stability). The scaled layouts are represented for maximum stability as well as for logarithmic decrements of 0 and 0.5. The star represents the solution resulting from the fragmented component view design.

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Figure 9

The stability margins (objectives) of the journal and of the thrust bearings, the ratio between the impeller forces and the trust bearing load capacity at an eccentricity of 0.7 (constraint), and the ratio between the first critical bending speeds and the maximum rotational speed (constraint) represented as a function of the logarithmic decrement for the Pareto optimum solutions and for the fragmented design (star)

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Figure 10

The absolute and the relative losses of the different components of the Pareto optimum solutions for rotor layouts 1 and 2 as well as for the fragmented design. The superposed bar at a logarithmic decrement of 0.6 for architecture 1 represents the relative losses of the fragmented design.

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Figure 11

The optimized rotor dimensions as a function of the logarithmic decrement after 100,000 iterations for layout 1 and 2 and for the actual solution (star)

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Figure 12

The optimized journal bearing dimensions as a function of the logarithmic decrement for architecture 1 and 2 and for the solution resulting from fragmented design (star)

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Figure 13

The optimized axial thrust bearing dimensions as a function of the logarithmic decrement for architecture 1 and 2 and for the solution resulting from fragmented design (star)

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Figure 14

The rotor mass, inertias relative to the center of gravity and the relative distance of the bearing midspan to the center of gravity for architectures 1 and 2, and for the fragmented design (star)




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