Artificial neural network for correction of effects of plasticity in equibiaxial residual stress profiles measured by hole drilling

Abstract

The hole drilling method is a widely known technique for the determination of non-uniform residual stresses in metallic structures by measuring strain relaxations at the material surface caused through the stress redistribution during drilling of the hole. The integral method is a popular procedure for solving the inverse problem of determining the residual stresses from the measured surface strain. It assumes that the residual stress can be approximated by step-wise constant values, and the material behaves elastically so that the superposition principle can be applied. Required calibration data are obtained from finite element simulations, assuming linear elastic material behavior. That limits the method to the measurement of residual stresses well below the yield strength. There is a lack of research regarding effects caused by residual stresses approaching the yield strength and high through-thickness stress gradients as well as the correction of the resulting errors. However, such high residual stresses are often introduced in various materials by processes such as laser shock peening, for example, to obtain life extension of safety relevant components. The aim of this work is to investigate the limitations of the hole drilling method related to the effects of plasticity and to develop an applicable and efficient method for stress correction, capable of covering a wide range of stress levels. For this reason, an axisymmetric model was used for simulating the hole drilling process in ABAQUS involving plasticity. Afterward, the integral method was applied to the relaxation strain data for determining the equibiaxial stress field. An artificial neural network has been used for solving the inverse problem of stress profile correction. Finally, AA2024-T3 specimens were laser peened and the measured stress fields were corrected by means of the trained network. To quantify the stress overestimation in the hole drilling measurement, an error evaluation has been conducted.

Keywords

Residual stress hole drilling effect of plasticity artificial neural network finite element analysis inverse solution

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References

Schajer

Measurement of non-uniform residual stresses using the hole-drilling method. Part 1—stress calculation procedures. J Eng Mater: T ASME 1988; 110: 338–343.

Schajer

Measurement of non-uniform residual stresses using the hole-drilling method. Part 2—practical application of the integral method. J Eng Mater: T ASME 1988; 110: 334–349.

Schajer

Hole-drilling and ring core methods. Lilburn, GA: Fairmont Press, 1996, pp.5–20.

Lord

Re Grant

Whitehead

. The measurement of residual stresses by the incremental hole drilling technique (Measurement Good Practice Guide No. 53). Teddington: National Physical Laboratory, 2002.

Beaney

EM.

Accurate measurement of residual stress on any steel using the centre hole drilling. Strain 1976; 12(3): 99–106.

Diaz

Kaufmann

Galizzi

Determination of residual stresses using hole drilling and digital speckle pattern interferometry with automated data analysis. Opt Laser Eng 2000; 33: 39–48.

Schajer

Gazzarri

Surface profiling using sequential sampling and inverse methods. Part I: mathematical background. Exp Mech 2004; 44(5): 473–486.

Schajer

Steinzig

Full-field calculation of hole drilling residual stresses from electronic speckle pattern interferometry data. Exp Mech 2005; 45(6): 526–532.

Beghini

Bertini

Santus

A procedure for evaluating high residual stresses using the blind hole drilling method, including the effect of the plasticity. J Strain Anal Eng 2010; 45: 301–318.

10.

Cloud

Optical methods of engineering analysis. Cambridge: Cambridge University Press, 1995.

11.

McDonach

McKelvie

MacKenzie

. Improved moiré interferometry and applications in fracture mechanics, residual stress and damaged composites. Exp Techniques 1983; 7: 20–24.

12.

Miao

Zhang

. Determination of residual stress by use of phase shifting Moiré interferometry and hole-drilling method. Opt Laser Eng 2006; 44(1): 68–79.

13.

Antonov

Inspecting the level of residual stresses in welded joints by laser interferometry. Weld Prod 1983; 30: 29–31.

14.

Jones

Wykes

Holographic and speckle interferometry. 2nd ed.Cambridge: Cambridge University Press, 1989.

15.

Schajer

Application of finite element calculations to residual stress measurements. J Eng Mater: T ASME 1981; 103: 157–163.

16.

Seifi

Salimi-Majd

Effect of plasticity on residual stresses measurement by hole drilling method. Mech Mater 2012; 53: 72–79.

17.

Moharami

Sattari-Far

Experimental and numerical study of measuring high welding residual stresses by using the blind-hole-drilling technique. J Strain Anal Eng 2007; 43: 141–148.

18.

Liu

. Influence of the hole-side plastic deformation as a result of the stress concentration on the accuracy of residual welding stress measurement by small blind hole relaxation method and its modification. In: Proceedings of the international conference on welding for challenging environments, Toronto, ON, Canada, 15–17 October 1985. New York: Pergamon Press.

19.

Chupakhin

Kashaev

Huber

Effect of elasto-plastic material behaviour on determination of residual stress profiles using the hole drilling method. J Strain Anal Eng 2016; 51: 572–581.

20.

Clauer

Laser shock peening as a surface enhancement process. Key Eng Mater 2001; 197: 121–144.

21.

Rubio-Gonzales

Felix-Martinez

Ocana

. Effect of laser shock processing on fatigue crack growth of duplex stainless steel. Mater Sci Eng A: Struct 2011; 528(3): 914–919.

22.

Haykin

A comprehensive foundation. 2nd ed.New York: Pearson Education, 1998.

23.

Huber

Tsakmakis

A neural network tool for identifying the material parameters of a finite deformation viscoplasticity model with static recovery. Comput Method Appl M 2001; 191: 353–384.

24.

Dassault Systèmes. ABAQUS 6.13 user’s manual. Vélizy-Villacoublay: Dassault Systèmes, 2013.

25.

Lutz

Learning python. 4th ed.Sebastopol, CA: O’Reilly Media, 2009, p.1216.

26.

ASM Aerospace Specification Metals Inc. Aluminium 2024-T3, http://asm.matweb.com/search/SpecificMaterial.asp?bassnum=MA2024T3 (2007, accessed 14 July 2015).

27.

Zainul

Taib

Zaharinie

Characterization of 2024-T3: an aerospace aluminum alloy. Mater Chem Phys 2009; 113: 515–517.

28.

Garmo

Black

Kohser

Materials and processes in manufacturing. New York: John Wiley & Sons, 2003.

29.

Kacer

Atik

Miric

The effect of precipitation-hardening conditions on wear behaviours at 2024 aluminium wrought alloy. J Mater Process Tech 2003; 142(3): 762–766.

30.

Enz

Khomenko

Riekehr

. Single-sided laser beam welding of a dissimilar AA2024–AA7050 T-joint. Mater Design 2015; 76: 110–116.

31.

McClug

Literature survey on the stability and significance of residual stresses during fatigue. Fatigue Fract Eng M 2007; 30(3): 173–205.

32.

Ding

Laser shock peening: performance and process simulation. Cambridge: Woodhead Publishing, 2006.

33.

Spanrad

Tong

Characterisation of foreign object damage (FOD) and early fatigue crack growth in laser shock peened Ti-6Al-4V aerofoil specimens. Mater Sci Eng A: Struct 2011; 528(4–5): 2128–2136.

34.

Correa

Ruiz

Lara

Diaz

. Effect of advancing direction on fatigue life of 316L stainless steel specimens treated by double-sided laser shock peening. Int J Fatigue 2015; 107: 98–107.

35.

Spradlin

Process sequencing for fatigue life extension of large scale laser peened components. PhD Thesis, Wright State University, Dayton, OH, 2011.

36.

Ivetic

Meneghin

Ocana

. Fatigue in laser shock peened open-hole thin aluminium specimens. Mater Sci Eng A: Struct 2012; 534: 573–579.

37.

Sano

Adachi

Akita

. Enhancement of surface property by low-energy laser peening without protective coating. Key Eng Mater 2007; 345(3): 1589–1592.

38.

Steinzig

Ponslet

Residual stress measurement using the hole drilling method and laser speckle interferometry: part 1. Exp Techniques 2003; 27: 43–46.

39.

MSC Software. Partan user’s guide. Santa Ana, CA: MSC Software, 2012.

40.

Yagawa

Okuda

Neural networks in computational mechanics. Arch Comput Method E 1996; 3: 435–512.

41.

Willumeit

Feyerabend

Huber

Magnesium degradation as determined by artificial neural networks. Acta Biomater 2013; 9(10): 8722–8729.

42.

Huber

Tsakmakis

Determination of constitutive properties from spherical indentation data using neural networks. Part I: the case of pure kinematic hardening. J Mech Phys Solids 1999; 47(7): 1569–1588.

43.

Huber

Tsakmakis

Determination of constitutive properties from spherical indentation data using neural networks. Part II: plasticity with nonlinear isotropic and kinematic hardening. J Mech Phys Solids 1999; 47(7): 1589–1607.

44.

Huber

Tsagrakis

Tsakmakis

Determination of constitutive properties of thin metallic films on substrates by spherical indentation using neural networks. Int J Solids Struct 2000; 37(44): 6499–6516.

45.

Huber

Konstantinidis

Tsakmakis

Determination of Poisson’s ratio by spherical indentation using neural networks. Part I: theory. J Appl Mech 2001; 68: 218–223.

46.

Huber

Tsakmakis

Determination of Poisson’s ratio by spherical indentation using neural networks. Part II: identification method. J Appl Mech 2001; 68: 224–229.

47.

Huber

Nix

Gao

Identification of elastic-plastic material parameters from pyramidal indentation of thin films. Proc R Soc Lon Ser: A 2002; 458: 1593–1620.

48.

Tyulyukovskiy

Huber

Identification of viscoplastic material parameters from spherical indentation data. Part I: neural networks. J Mater Res 2006; 21: 664–676.

49.

Schajer

Abraham

Residual stress measurement in finite-thickness materials by hole-drilling. Exp Mech 2014; 54(9): 1515–1522.

50.

ASTM E837-13a:2013. Standard test method for determining residual stresses by hole drilling strain gage method.