A dataset for the development, verification, and validation of microstructure-sensitive process models for near-alpha titanium alloys

  • Adam L. PilchakEmail author
  • Jared Shank
  • Joseph C. Tucker
  • Shesh Srivatsa
  • Patrick N. Fagin
  • S. Lee Semiatin
Data Descriptor


Near-alpha titanium alloys are used for moderate-temperature applications in the early stages of the compressor in gas turbine engines. The quasi-static and fatigue properties of these alloys depend heavily on microstructure due to the absence of hard second phases and inclusions which can nucleate voids or cracks. Moreover, these alloys are known to exhibit a significant reduction in fatigue life when subjected to high mean stress or upon the application of dwell-fatigue cycles. Previous analysis has elucidated the microstructural features that drive these properties; the most important features are the volume fraction, size, and shape of clusters of similarly oriented alpha particles or microtextured regions (MTRs). To date, there have been few efforts to elucidate in a quantitative fashion the evolution of MTRs during thermomechanical processing (TMP). To meet this need, we have performed hot-compression tests on Ti-6Al-2Sn-4Zr-2Mo-0.1Si billet material with high-aspect-ratio MTRs at 0°, 45°, and 90° to the direction of primary metal flow during manufacture (i.e., the billet axis), thoroughly characterized the initial and final microstructures, and quantified field variables via finite-element method (FEM) process simulations for each experiment. These data can be used for a variety of purposes including the development, verification, and validation of models for microstructure/texture/microtexture evolution and defect formation.


Titanium Microstructure EBSD Texture Microtexture Process simulation Characterization 



This work was performed as part of the in-house research activities of the Air Force Research Laboratory’s Materials and Manufacturing Directorate. The support of laboratory management is greatly appreciated. Several of the authors (JS, JT, SS, PF) were supported through Air Force contract FA8650-10-D-5226 during the time this work was completed.

Authors’ contributions

ALP conceived the study, collected the EBSD data, coordinated the efforts at AFRL, and drafted the manuscript; ALP and JCT devised the microtexture segmentation routine while JCT implemented the algorithms in DREAM.3D; JS collected the BSE images, performed the MTR segmentation, and coordinated uploading the dataset to the NIST server; PNF performed and reduced the data from the isothermal compression tests; SS developed and validated the finite-element models; and SLS helped design the experiments, assisted with data analysis, and also assisted with drafting the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare they have no competing interests.


  1. 1.
    Van Stone RH, Low JR Jr, Shannon JL Jr (1978) Investigation of the fracture mechanism of Ti-5Al-2.5Sn at cryogenic temperatures. Metall Trans A 9:539–47CrossRefGoogle Scholar
  2. 2.
    Bowen AW (1975) Influence of crystallographic orientation on fatigue crack growth in strongly textured Ti-6Al-4V. Acta Metall 23(11):1401–1409CrossRefGoogle Scholar
  3. 3.
    Evans WJ, Jones JP, Whittaker MT (2005) Texture effects under tension and torsion loading conditions in titanium alloys. Int J Fatigue 27:1244–1250CrossRefGoogle Scholar
  4. 4.
    Woodfield AP, Gorman MD, Corderman RR, Sutliff JA, Yamrom B (1996) Effect of microstructure on dwell fatigue behavior of Ti-6242. Titanium’95: Science and Technology, P.A. Blenkinsop, W.J. Evans, and H.M. Flower, eds., Institute of Materials, Birmingham, UK:1116–23Google Scholar
  5. 5.
    Toubal L, Bocher P, Moreau A, Levesque D (2010) Macroregion size measurements in bimodal titanium forgings using two-dimensional autocorrelation method. Metall Mater Trans A 41:744–750CrossRefGoogle Scholar
  6. 6.
    Bridier F, Villechaise P, Mendez J (2005) Analysis of the different slip systems activated by tension in a α/β titanium alloy in relation with local crystallographic orientation. Acta Mater 53:555–567CrossRefGoogle Scholar
  7. 7.
    Echlin M, Stinville JC, Miller VM, Lenthe WC, Pollock TM (2016) Incipient slip and long range plastic strain localization in microtextured Ti-6Al-4V titanium. Acta Mater 114:164–175.zCrossRefGoogle Scholar
  8. 8.
    Semiatin SL, Furrer DU, Modeling of microstructure evolution during the thermomechanical processing of titanium alloys, ASM Handbook, Vol. 22A, Tenth Edition, ASM International, Materials Park, OH, 2009, p. 522Google Scholar
  9. 9.
    Semiatin SL, Shevchenko SV, Ivasishin OM, Glavicic MG, Chun YB, and Hwang SK, Modeling and simulation of texture evolution during the thermomechanical processing of titanium alloys, ASM Handbook, Vol. 22A, Tenth Edition, ASM International, Materials Park, OH, 2009, p. 536Google Scholar
  10. 10.
    Pilchak AL, Hutson A, Porter WJ, Buchanan DJ and John R (2016) Growth of small and long fatigue cracks in Ti-6Al-4V subjected to cyclic and dwell fatigue, Proc. of the 13th World Conference on Titanium, ed. V. Venkatesh et al. (Warrendale, PA: The Minerals, Metals & Materials Society; Hoboken, NJ: John Wiley & Sons, 2016), pp. 993–998.Google Scholar
  11. 11.
    Pilchak AL (2014) A simple model to account for the role of microtexture on fatigue and dwell fatigue lifetimes of titanium alloys. Scr Mater 74:68–71CrossRefGoogle Scholar
  12. 12.
    Dataset archived on the NIST repository:
  13. 13.
    Pilchak AL, Szczepanski CJ, Shaffer JA, Salem AA, Semiatin SL (2013) Characterization of microstructure, texture and microtexture in near-alpha titanium mill products. Metall Mater Trans A 44:4881–4890CrossRefGoogle Scholar
  14. 14.
    Altan T (1983) in Metals forming: fundamentals and applications, ASM International, Materials Park, OH, Chapter 10Google Scholar
  15. 15.
    Shiveley AR, Shade PA, Pilchak AL, Tiley JS, Kerns R (2011) A novel method for acquiring large scale automated scanning electron microscopy data. J Microsc 244(2):181–186CrossRefGoogle Scholar
  16. 16.
    Pilchak AL, Shiveley AR, Tiley JS, Ballard DL (2011) AnyStitch: a tool for combining electron backscatter diffraction data sets. J Microsc 244(1):38–44CrossRefGoogle Scholar
  17. 17.
    Pilchak AL, Shiveley AR, Shade PA, Tiley JS, Ballard DL (2012) Using cross-correlation for automated stitching of two-dimensional multi-tile electron backscatter diffraction data. J Microsc 248(2):172–186CrossRefGoogle Scholar
  18. 18.
    Groeber MA, Jackson MA (2014) DREAM.3D: a Digital Representation Environment for the Analysis of Microstructure in 3D. Integrating Materials and Manufacturing Innovation 3(5):1–17Google Scholar
  19. 19.
    Tucker JC, Pilchak AL, Groeber MA, Semiatin L (2015) Objective characterization, synthetic building and targeted analysis of microtextured regions from electron backscatter diffraction data. The 13th World Conference on Titanium 2015, San Diego, CA, August 2015Google Scholar
  20. 20.
    Pilchak AL, Williams JC (2011) Observations of facet formation in near-α titanium and comments on the role of hydrogen. Metall Mater Trans A 42(4):1000–1027CrossRefGoogle Scholar
  21. 21.
    Pilchak AL, Bhattacharjee A, Rosenberger AH, Williams JC (2009) Low ΔK faceted crack growth in titanium alloys. Int J Fatigue 31:989–994CrossRefGoogle Scholar

Copyright information

© The Author(s). 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Adam L. Pilchak
    • 1
    Email author
  • Jared Shank
    • 2
  • Joseph C. Tucker
    • 2
    • 3
  • Shesh Srivatsa
    • 4
  • Patrick N. Fagin
    • 2
  • S. Lee Semiatin
    • 1
  1. 1.Air Force Research LaboratoryAFRL/RXCMWright-Patterson AFBUSA
  2. 2.UES Inc.BeavercreekUSA
  3. 3.Present address: Exponent, Inc.AtlantaUSA
  4. 4.Srivatsa Consulting, LLCCincinnatiUSA

Personalised recommendations