Title: Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

Abstract

Small crack propagation accounts for most of the fatigue life of engineering structures subject to high cycle fatigue loading conditions. Determining the fatigue crack growth rate of small cracks propagating into polycrystalline engineering alloys is critical to improving fatigue life predictions, thus lowering cost and increasing safety. In this work, cycle-by-cycle data of a small crack propagating in a beta metastable titanium alloy is available via phase and diffraction contrast tomography. Crystal plasticity simulations are used to supplement experimental data regarding the micromechanical fields ahead of the crack tip. Experimental and numerical results are combined into a multimodal dataset and sampled utilizing a non-local data mining procedure. Furthermore, to capture the propensity of body-centered cubic metals to deform according to the pencil-glide model, a non-local driving force is postulated. The proposed driving force serves as the basis to construct a data-driven probabilistic crack propagation framework using Bayesian networks as building blocks. The spatial correlation between the postulated driving force and experimental observations is obtained by analyzing the results of the proposed framework. Results show that the above correlation increases proportionally to the distance from the crack front until the edge of the plastic zone. Moreover, the predictions of the propagationmore » framework show good agreement with experimental observations. Finally, we studied the interaction of a small crack with grain boundaries (GBs) utilizing various slip transmission criteria, revealing the tendency of a crack to cross a GB by propagating along the slip directions minimizing the residual Burgers vector within the GB.« less

Authors:

Rovinelli, Andrea  ^[1];

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Sangid, Michael D. ^[1]; Proudhon, Henry  ^[2];

• Search DOE PAGES for author "Proudhon, Henry"
• Search DOE PAGES for ORCID "0000-0002-4075-5577"
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Guilhem, Yoann  ^[3];

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Lebensohn, Ricardo A. ^[4]; Ludwig, Wolfgang ^[5]

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+ Show Author Affiliations

1. Purdue Univ., West Lafayette, IN (United States). School of Aeronautics and Astronautics
2. MINES ParisTech, Paris (France). PSL Research Univ., MAT – Centre des materiaux
3. Laboratoire de Mécanique et Technologie (LMT), Paris (Fance)
4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
5. Univ. of Lyon (France)

Publication Date:

2018-03-11

Research Org.:

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:

1440486

Report Number(s):

LA-UR-17-31135
Journal ID: ISSN 0022-5096

Grant/Contract Number:  

AC52-06NA25396

Resource Type:

Accepted Manuscript

Journal Name:

Journal of the Mechanics and Physics of Solids

Additional Journal Information:

Journal Volume: 115; Journal Issue: C; Journal ID: ISSN 0022-5096

Publisher:

Elsevier

Country of Publication:

United States

Language:

English

Subject:

36 MATERIALS SCIENCE; A small crack propagation; B crystal plasticity; B polycrystalline material; C nondestructive evaluation; Machine learning