Estimating fatigue sensitivity to polycrystalline Ni‐base superalloy microstructures using a computational approach

By M. Shenoy, Jixi Zhang, David L. McDowell. 2007

189 citations recorded by the source corpus.

Subfields: Mechanical Engineering, Mechanics of Materials, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1bd957fc1cdb4c4e44a95b3803175d69b0c6ef6e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Mechanical Engineering

1. Michael D. Sangid
2. Craig P. Przybyla
3. David L. McDowell
4. F. Dunne
5. Jun Jiang
6. Bo Chen
7. A. Wilkinson
8. Damiano Pasini

In Mechanics of Materials

1. Michael D. Sangid
2. Craig P. Przybyla
3. F. Dunne
4. David L. McDowell
5. Jun Jiang
6. Bo Chen
7. A. Wilkinson
8. Surya R. Kalidindi

In Statistics and Probability

1. Michael D. Sangid
2. David L. McDowell
3. Craig P. Przybyla

Citations in the corpus

• Microstructure-sensitive extreme value probabilities for high cycle fatigue of Ni-base superalloy IN100 (2010, methodology): “[31] constructed digital microstructure instantiations for IN100 using the same methods.”
• Is stored energy density the primary meso-scale mechanistic driver for fatigue crack nucleation? (2018, background): “In equation (12), k is related to material properties and chosen to be 0.5 for Nickel alloy systems (Findley, 2005; Fatemi and Socie, 1988; Shenoy et al., 2007).”
• The physics of fatigue crack initiation (2013, methodology): “modeled the fatigue behavior of Inconel 100 at elevated temperature through FE-CP [141,142].”