Journal of Nondestructive Evaluation

, Volume 33, Issue 2, pp 226–238 | Cite as

Optimized Dynamic Acousto-elasticity Applied to Fatigue Damage and Stress Corrosion Cracking

  • Sylvain HaupertEmail author
  • Jacques Rivière
  • Brian Anderson
  • Yoshikazu Ohara
  • T. J. Ulrich
  • Paul Johnson


The dynamic acousto-elasticity (DAE) technique uniquely provides the elastic (speed of sound and attenuation) behavior over a dynamic strain cycle. This technique has been applied successfully to highly nonlinear materials such as rock samples, where nonlinear elastic sources are present throughout the material. DAE has shown different nonlinear elastic behavior in tension and compression as well as early-time memory effects (i.e. fast and slow dynamics) that cannot be observed with conventional dynamic techniques (e.g. resonance or wave mixing measurements). The main objective of the present study is to evaluate if the DAE technique is also sensitive to (1) fatigue damage and (2) a localized stress corrosion crack. A secondary objective is to adapt the DAE experimental setup to perform measurements in smaller specimens (thickness of few cm). Several samples (intact aluminium, fatigued aluminium and steel with a stress corrosion crack) were investigated. Using signal processing not normally applied to DAE, we are able to measure the nonlinear elastic response of intact aluminium, distinguish the intact from the fatigued aluminium sample and localize different nonlinear features in the stress corrosion cracked steel sample.


Nonlinear acoustics Dynamic acousto-elasticity Micro-damage Stress corrosion crack Fatigue damage Polycrystalline metals 



This work was supported in part by the U.S. Dept. of Energy, Nuclear Energy Fuel Cycle Research and Development program under the Used Fuel Disposition campaign as part of the storage demonstration and experimentation efforts and by Institutional Support (LDRD) at Los Alamos.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Sylvain Haupert
    • 1
    Email author
  • Jacques Rivière
    • 2
  • Brian Anderson
    • 2
  • Yoshikazu Ohara
    • 3
  • T. J. Ulrich
    • 2
  • Paul Johnson
    • 2
  1. 1.Laboratoire d’imagerie paramétriqueCNRS UMR 7623, UPMC Paris 6ParisFrance
  2. 2.Geophysics Group MS D446, Earth and Environmental SciencesLos Alamos National LaboratoryLos AlamosUSA
  3. 3.Department of Materials Processing, Graduate School of EngineeringTohoku UniversitySendai Japan

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