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Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete...

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Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies Research Center Mas Hongoh Pratt & Whitney
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Page 1: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Mathematical Modeling of Inclusion Dissolution Processes:

The GROW Code

Ernesto Gutierrez-MiraveteRensselaer at Hartford

Brice CassentiUnited Technologies Research Center

Mas Hongoh Pratt & Whitney

Page 2: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Outline

• Introduction

• Model Description

• Description of the GROW Code

• Examples Runs of the Code

• Parametric and Sensitivity Studies

• Summary

Page 3: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Introduction

• Undetected N- and/or O-containing particles in Ti alloys (hard-alpha) can result in catastrophic failure of aircraft engine components.

• The process metallurgy of Ti alloys provides many potential sources of N and/or O.

• Better understanding of the dissolution behavior of N- and/or O containing Ti inclusions in Ti alloys during thermal processing is required.

Page 4: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Model Description• When N and/or O come in contact with Ti

several different phases can form depending on composition and temperature.– The Ti-N phase diagram (Fig 1a).– The Ti-O phase diagram (Fig 1b).

• If an isolated N-rich or O-rich seed particle is embedded in a Ti matrix, the various phases appear as concentric layers on the original particle.

Page 5: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 1a

Page 6: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 1b

Page 7: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Model Description (contd.)

• The concentration of impurity decreases with distance from the center of the seed particle.

• Dissolution of the resulting layers involves mass transport of N and/or O away from the seed particle.

• See Figure 2.

Page 8: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

C

x

L

Fig 2 Concentration profile around a dissolving inclusion.

Flux of N (or O)

Page 9: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Model Description (contd.)

• Assumptions and Limitations– Binary Systems (Ti-N or Ti-O)

– Chemical Equilibrium at all Interfaces

– All Phases form Ideal Solutions

– Temperatures restricted to within beta transus of pure Ti and first peritectic

• 882 - 2020 C for Ti-N and 882- 1720 C for Ti-O

– All Necessary Diffusivity Data readily Available

– Porosity is Neglected

Page 10: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Model Description (contd.)

• Governing Equation

c/t = div ( D grad a)where

c = concentration of N (or O)

D = diffusivity of N (or O)

a = activity of N (or O) (Figs 3 and 4)

Page 11: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

a

C

L

Fig 3 Activity-concentration relationship in Ti-N (or Ti-O)

Page 12: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

a*

a

L

Fig 4

Page 13: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Model Description (contd.)

• Solution Methodology: – Finite Difference Method– Fixed Mesh– Explicit Scheme

• Physico-Chemical Data:– Phase Diagrams– Diffusivities

Page 14: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

The GROW code• Derived from earlier code MICRO developed at

UTRC.• FORTRAN program embedded in a UNIX

wrapper.• Inputs:

– Inclusion size and geometry– Inclusion and matrix concentration– Thermal history– Mesh

Page 15: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

The GROW Code (contd.)

• Outputs– Concentration profiles around inclusion at

selected times during specified temperature history

– Extent of the various layers as functions of time.

– Extent of the diffusion zone surrounding the inclusion as function of time.

Page 16: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Example Runs (Ti-N)

• Isothermal Hold at 1200 C (Figs. 5a and 5b)

• Isothermal Hold at 1600 C (Figs. 6a and 6b)

• Isothermal Hold at 2020 C (Figs. 7a and 7b)

• Sample Thermal History (Figs. 8a and 8b) t (s) 0 1 5 10 12 13 15

T(C) 2000 1670 1000 1000 1300 1500 1000

Page 17: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 5a

Page 18: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 5b

Page 19: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 6a

Page 20: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 6b

Page 21: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 7a

Page 22: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 7b

Page 23: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 8a

Page 24: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 8b

Page 25: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Example Runs (Ti-N) (contd.)

• Two-dimensional system (250 by 1000 micron inclusion). Figs. 9a and 9b.

• Three-dimensional system (250 by 500 by 1000 micron inclusion). Figs. 10a and 10b.

Page 26: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 9a

Page 27: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 9b

Page 28: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 10a

Page 29: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 10b

Page 30: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Example Runs (Ti-O)

• Isothermal Hold at 1200 C (Figs. 11a and 11b)• Isothermal Hold at 1600 C (Figs. 12a and 12b)• Isothermal Hold at 1720 C (Figs. 13a and 13b)• Sample Thermal History (Figs. 14a and 14b) t (s) 0 1 5 10 12 13 15

T(C) 2000 1670 1000 1000 1300 1500 1000

Page 31: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 11a

Page 32: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 11b

Page 33: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 12a

Page 34: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 12b

Page 35: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 13a

Page 36: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 13b

Page 37: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 14a

Page 38: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 14b

Page 39: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Example Runs (Ti-N) (contd.)

• Two alternative calculation methods of phase thickness under thermal history (Figs. 15 and 16)

• Two alternative calculation methods of phase thickness under isothermal hold at 2020 C (Fig. 17).

Page 40: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 15

Page 41: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 16

Page 42: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Fig 17

Page 43: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Parametric and Sensitivity Studies

• Effect of Initial Seed Particle Size on Extent of Diffusion Zone under Specified Thermal History (Triple Melt VAR).

• Effect of Initial Seed Particle Concentration on Extent of Diffusion Zone under Specified Thermal History (Triple Melt VAR).

Page 44: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Summary (contd.)

• A mathematical model and associated computer code are now available to investigate the spread of diffusion zones around N- or O-rich inclusion particles in Ti as a function of thermal history, inclusion geometry and composition.

Page 45: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Summary (contd.)

• Once fully validated, the GROW code can help process engineers, designers, NDT and quality assurance personnel to achieve their goal of producing hard-alpha free aircraft engine components.

Page 46: Mathematical Modeling of Inclusion Dissolution Processes: The GROW Code Ernesto Gutierrez-Miravete Rensselaer at Hartford Brice Cassenti United Technologies.

Summary (contd.)

• Although the results of calculation are in reasonably good agreement with at least some of the existing empirical data on dissolution rates, full validation of the model requires comparison against results of carefully conducted experiments on selected systems.


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