Research Papers: Gas Turbines: Structures and Dynamics

Probabilistic Fracture Mechanics for Heavy-Duty Gas Turbine Rotor Forgings

[+] Author and Article Information
Kai Kadau

Siemens Energy Inc.,
5101 Westinghouse Boulevard,
Charlotte, NC 28273
e-mail: kai.kadau@siemens.com

Phillip W. Gravett

Siemens Energy Inc.,
11842 Corporate Boulevard,
Orlando, FL 32817
e-mail: phillip.gravett@siemens.com

Christian Amann

Siemens AG,
Mellinghofer Street 55,
Mülheim an der Ruhr 45473, Germany
e-mail: christian.amann@siemens.com

1Corresponding author.

2Note that a typical heavy-duty GT design has about 20 of those disks rotating at 50 Hz or 60 Hz.

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received September 1, 2017; final manuscript received September 27, 2017; published online January 23, 2018. Editor: David Wisler.

J. Eng. Gas Turbines Power 140(6), 062503 (Jan 23, 2018) (6 pages) Paper No: GTP-17-1488; doi: 10.1115/1.4038524 History: Received September 01, 2017; Revised September 27, 2017

We developed and successfully applied a direct simulation Monte Carlo (MC) scheme to quantify the risk of fracture for heavy-duty rotors commonly used in the energy sector. The developed probabilistic fracture mechanics (FM), high-performance computing methodology, and code ProbFM routinely assess relevant modes of operation for a component by performing billions of individual FM simulations. The methodology can be used for new design and life optimization of components, as well as for the risk of failure RoF quantification of in service rotors and their requalifications in conjunction with nondestructive examination techniques, such as ultrasonic testing (UT). The developed probabilistic scheme integrates material data, UT information, duty-cycle data, and finite element analysis (FEA) in order to determine the RoF. The methodology provides an integrative and robust measure of the fitness for service and allows for a save and reliable operation management of heavy-duty rotating equipment.

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Fig. 1

Heavy-duty GT rotor disk forgings at different manufacturing stages. After forging and heat treatment (left), ultrasonic contour (middle), rough machined contour (right). A typical weight is about 5 tons with diameters and thicknesses up to 2 m and 0.4 m, respectively. (Picture courtesy of Alexander Zimmer (Saarschmiede GMBH, Germany) and Johannes Vrana (iNDEC—International NDE consulting, Germany)) [1].

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Fig. 2

Schematic part-life distribution for a component exhibiting a narrow distribution (solid line) and a broader distribution (dashed line), respectively. The application of a deterministic design factor to the average life (dotted line) can lead to different failure risks at the deterministic design life (vertical line intersection with respective distribution).

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Fig. 3

Schematics of rotor disk fracture modeling. A rotor disk with a central hole rotates with angular velocity ω. The resulting stress field can be calculated in an axis-symmetric transient FEA model. The FM problem is simplified by projecting the stress fields onto a rectangular plate model. In this example, a semi-elliptical surface crack at the hub of the rotor is shown (solid lines show gradients in two directions).

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Fig. 4

Typical behavior of K1C of a high-quality rotor steel. Low toughness and brittle behavior at lower temperatures and higher toughness at higher temperatures. The average properties, as well as selected quantiles are shown.

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Fig. 5

Convergence of PoF with increasing MC sample size S

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Fig. 6

Convergence of H with increasing MC sample size S. Note, the larger sample sizes S needed for convergence as compared to PoF shown in Fig. 5.

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Fig. 7

Maximum component stress during transient operating for a C-S (top) and IGV-LFC (bottom). The transient thermal overshoot for the C-S in the interior of the disk near the bore is clearly visible. Axis symmetric model with bore at the bottom, see Fig. 3 for reference.

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Fig. 8

Single-mission PoF for C-S, ISO-S, and IGV-LFC

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Fig. 9

Multiple duty-cycle PoF compared to single-mission PoF for C-S, ISO-S, and IGV-LFC are shown

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Fig. 10

Risk contour for IGV-LFC only (top), C-S only (middle), and duty cycle consisting of 0.5% C-S and 99.5% IGV-LFC (bottom). The shown MC simulation consists of 10 × 109 samples and the spatial resolution is about 0.1 × 106 two-dimensional voxels. Note, the contours are shown on a logarithmic scale over a range of four decades—for clarity each contour has a different range.

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Fig. 11

Risk contour for 0.5% C-S and 99.5% IGV-LFC duty cycle. The number of MC samples increases from top to bottom 100 × 106 (top), 10 × 109 (middle), and 1 × 1012 samples (bottom), respectively. Note, the contours are shown on a logarithmic scale over a range of four decades, each contour has the same range.




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