Research Papers

An Efficient Reliability-Based Simulation Method for Optimum Laser Peening Treatment

[+] Author and Article Information
Peter J. Hasser

Parks College of Engineering,
Aviation and Technology,
Saint Louis University,
3450 Lindell Boulevard,
St. Louis, MO 63103
e-mail: hasser.peter@gmail.com

Arif S. Malik

Mechanical Engineering Department,
Erik Jonsson School of Engineering and
Computer Science,
The University of Texas at Dallas,
800 West Campbell Road,
Richardson, TX 75080
e-mail: arif.malik@utdallas.edu

Kristina Langer

Air Force Research Laboratory,
Wright-Patterson AFB, OH 45433
e-mail: kristina.langer@us.af.mil

Thomas J. Spradlin

Air Force Research Laboratory,
Wright-Patterson AFB, OH 45433
e-mail: thomas.spradlin@us.af.mil

Mohammad I. Hatamleh

Mechanical Engineering Department,
Erik Jonsson School of Engineering and
Computer Science,
The University of Texas at Dallas,
800 West Campbell Road,
Richardson, TX 75080
e-mail: mih150230@utdallas.edu

1Corresponding author.

Manuscript received February 23, 2015; final manuscript received April 12, 2016; published online June 23, 2016. Assoc. Editor: Hongqiang Chen.This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Manuf. Sci. Eng 138(11), 111001 (Jun 23, 2016) (14 pages) Paper No: MANU-15-1091; doi: 10.1115/1.4033604 History: Received February 23, 2015; Revised April 12, 2016

A method is introduced for efficient reliability-based design of laser peening (LP) surface treatment to extend fatigue life of metal components. The method includes nonparametric probability density estimation, surrogate modeling using a new finite element (FE or FEA) approach, and reliability analysis with correlated random variables (RVs). Efficient LP simulation is achieved via a new technique termed single explicit analysis using time-dependent damping (SEATD), which reduces simulation times by a factor of 6. The example study of a three-point bend coupon reveals that fatigue life reliability significantly affects optimal LP design, as 52 laser spots are needed for 99% reliability versus 44 spots for 95%.

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Fig. 2

Conventional explicit–implicit simulation approach of LP using FEA

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Fig. 3

The 2N + 1 approach to FEA of LP

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Fig. 4

Flowchart of the SEATD approach

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Fig. 5

Spectral radius versus normalized eigenvalue. (Reproduced with permission from Underwood [21]. Copyright 1983 Elsevier B. V.).

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Fig. 6

Strain energy history for three 2N + 1 constant-damping values and SEATD oscillatory damping

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Fig. 7

SEATD mass-proportional damping profile used for simulations in Sec. 2

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Fig. 8

Laser peened plate configuration, based on Ref. [11] (dimensions are in mm)

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Fig. 9

Spatial pressure profile of circular LP spot. Adapted from irradiance profile in Ref. [22].

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Fig. 10

Comparison between SEATD, replicated 2N + 1, and Brockman's experimentally verified 2N + 1 results, along Fig. 8 path

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Fig. 11

Strain energy history for constant damping (c = 2.8 × 106, c = 3.8 × 106, c = 5 × 106, and c = 1 × 107), and variable damping profile-1 and profile-2 after the second LP shot

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Fig. 12

Kinetic energy history for constant damping (c = 2.8 × 106, c = 3.8 × 106, c = 5 × 106, and c = 1 × 107), and variable damping profile-1 and profile-2 after the second LP shot

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Fig. 13

Total energy history for constant damping (c = 2.8 × 106, c = 3.8 × 106, c = 5 × 106, and c = 1 × 107), and variable damping profile-1 and profile-2 after the second LP shot

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Fig. 14

Reliability method for LP

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Fig. 15

Decision-making process for quantifying uncertainty of an RV

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Fig. 16

Flowchart of the RBDO process for LP. (Note: LHS refers to Latin hypercube sampling.)

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Fig. 17

Three-point bend specimen (shaded area indicates region for LP treatment)

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Fig. 18

Cross section of specimen (dimensions are in mm)

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Fig. 19

Peened area of the specimen

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Fig. 20

Temporal pressure profile for each LP spot, sampled from Ref. [11]

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Fig. 21

General LP pattern, showing how adjacent rows overlap

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Fig. 22

Axisymmetric top hat spatial pressure profile, indicating PPR variable definition

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Fig. 23

BI-based marginal PDFs for JC model parameters of Al 2014-T4: (a) A, MPa; (b) B, MPa; (c) C; and (d) n

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Fig. 24

Two-part RBDO process for case study

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Fig. 25

Longitudinal residual stress for optimal LP design

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Fig. 26

Residual stress along z-direction path from midpoint

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Fig. 27

Residual stress along x-direction path from midpoint




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