Modeling and Parameter Design of a Laser Shock Peening Process

Abstract

Laser shock peening (LSP) is a surface treatment technique that has been applied to improve fatigue and corrosion properties of metals. The ability to use a high energy laser pulse to generate shock waves, inducing a compressive residual stress field in metallic materials, has applications in multiple fields such as turbomachinery, airframe structures, and medical appliances. In the past, researchers have investigated the effect of LSP parameters experimentally [1, 2, 3, 4, 5] and performed a limited number of simulations on simple geometries [6, 7, 8, 9]. However, monitoring the dynamic, intricate relationship of peened material experimentally is expensive and challenging. With an increasing number of applications on complex geometries, these limited experimental and simulations capabilities are not sufficient for LSP process design. A computational mechanics procedure is required that can perform simulations of multiple treatments of LSP at the same location, sequential LSP at multiple locations, different overlapping configurations of LSP locations, and complex geometries. With increased computer speed as well as increased sophistication in non-linear finite element (FE) analysis software, it is now possible to develop a simulation-based design investigation approach for an effective LSP process design. In this paper, the process parameters are identified and a three-dimensional simulation is adopted and validated. This simulation is then used in sensitivity analysis of performance metrics of residual stress for variations in the LSP parameters such as pressure pulse magnitude and shape, spot shape and size, component thickness, number of shots, layout of shots, and multiple shot sequences.

Keywords:

• Laser peening
• Surface treatment
• Residual stress
• Non-linear finite element analysis
• 3-D laser peening simulation
• LP parametric design

Acknowledgments

The first two authors acknowledge the support from U.S. Air Force contract FA8650-04-D-3446-025. We thank Dr. A.H. Clauer and Mr. David Lahrman from LSP Technologies, Inc., Columbus, OH, for technical exchange during this research. We also thank the Ohio Supercomputing Center and Dassault Systemes for access to ABAQUS.