Three Dimensional Microstructures: Statistical Analysis of Second Phase Particles in AA7075-T651

Rollett, Anthony D.; Campman, R.; Saylor, David M.

doi:10.4028/www.scientific.net/msf.519-521.1

Cited by 24 publications

(17 citation statements)

References 19 publications

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“…Figure 13(c) shows the different phases in 7075 aluminum alloy (Al-7075). Many authors [36][37][38] have done extensive microstructural analysis on this material, especially regarding the distribution of the second phases into the matrix. The second phases are generally Fe-bearing inclusions (Al 7 Cu 2 Fe 2 ,A l 23 Fe 4 Cu) and Si-bearing inclusions (Mg 2 Si) which are uniformly distributed into the matrix, and their volume fraction could reach up to 3%.…”

Section: Discussionmentioning

confidence: 99%

Cavitation erosion: Using the target material as a pressure sensor

Roy

Franc

Fivel

2015

Journal of Applied Physics

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Section: Discussionmentioning

confidence: 99%

Cavitation erosion: Using the target material as a pressure sensor

Roy

Franc

Fivel

2015

Journal of Applied Physics

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“…Empirical life models that account for this dispersion do not provide insights into the physical mechanisms that lead to this scatter. Probabilistic analysis need to assist mechanistically based models in order to address the statistical nature of pitting, the behaviour of small cracks and microstructures [207,208,90].…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Corrosion-fatigue: a review of damage tolerance models

Larrosa

Akid

Ainsworth

2017

International Materials Reviews

107

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The synergistic combination of mechanical fatigue stresses and environmental agents acting together can be more detrimental than that of the summation of the contributions of each mechanism acting separately. Major attempts to understand the contribution of the different agents (microstructure, chemical composition of environment, temperature, loading conditions, etc.) have been reported in the literature. Nevertheless, current knowledge is insufficient to address life estimation with a sound physical basis from the initiation of localized corrosion (such as pitting) to the estimation of crack propagation. Major simplifications and assumptions have been required in the development of life prediction methodologies. This paper reviews recent effort made by the different interested parties, both in academia and industry, in the development of corrosion fatigue lifetime prediction procedures. The paper mainly focuses on methodologies proposed in the literature for O&G, nuclear, energy generation and aerospace applications, dealing with pitting corrosion-fatigue (CF) damage in aluminium alloys, carbon and stainless steels. The transition of a pit into a small crack and its growth is influenced by interaction of the pit stress/strain concentration and the local environmental conditions, making the modelling of this stages of the utmost complexity. A major trend in the models reviewed in this paper is to simplify the analysis by assuming the pit (a volumetric defect) as a sharp crack, decouple the CF problem and account for the mechanical and environmental contributions separately. These procedures heavily rely on fitting experimental data and exhibit low generality in terms of application to varying system conditions. There is a clear opportunity in this field to develop mechanistically based methodologies, considering the inherent dependence of the damage mechanism on the interaction of environmental, metallurgical and mechanical features, allowing more realistic lifetime estimates and defect tolerance arguments, where pit-to-crack transition and small crack initiation stages pose a significant challenge.

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“…Further techniques have been suggested in order to reproduce the statistical distribution of grain size and shape obtained from experimental observations of twodimensional orthogonal sections, cf., e.g., [13] and [83]. In [68,69,72] the three-dimensional characterization of DP steels result in statistically representative three-dimensional microstructures. An alternative approach is the construction of statistically similar RVEs (SSRVEs), cf.…”

Section: Introductionmentioning

confidence: 99%

Computational modeling of dual-phase steels based on representative three-dimensional microstructures obtained from EBSD data

et al. 2015

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The microstructure of dual-phase steels consisting of a ferrite matrix with embedded martensite inclusions is the main contributor to the mechanical properties such as high ultimate tensile strength, high work hardening rate, and good ductility. Due to the composite structure and the wide field of applications of this steel type, a wide interest exists in corresponding virtual computational experiments. For a reliable modeling, the microstructure should be included. For that reason, in this paper we follow a computational strategy based on the definition of a representative volume element (RVE). These RVEs will be constructed by a set of tomographic measurements and mechanical tests. In order to arrive at more efficient numerical schemes, we also construct statistically similar RVEs, which are characterized by a lower complexity compared with the real microstructure but which represent the overall material behavior accurately. In addition to the morphology of the microstructure, the austenite-martensite transformation during the steel production has a relevant influence on the mechanical properties and is considered in this contribution. This transformation induces a volume expansion of the martensite phase. A further effect is determined in nanoindentation test, where it turns out that the hardness in the ferrite phase increases exponentially when approaching the martensitic inclusion. To capture these gradient properties in the computational model, the volumetric expansion is applied to the martensite phase, and the arising equivalent plastic strain distribution in the ferrite phase serves as basis for a locally graded modification of the ferritic yield curve. Good accordance of the model considering the gradient yield behavior in the ferrite phase is observed in the numerical simulations with experimental data.Keywords Reconstruction of microstructure · Dual-phase steel · RVE · Microheterogeneous materials · EBSD-FIB · SSRVE · Volume expansion of martensite · Multiscale simulations

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Three Dimensional Microstructures: Statistical Analysis of Second Phase Particles in AA7075-T651

Cited by 24 publications

References 19 publications

Cavitation erosion: Using the target material as a pressure sensor

Cavitation erosion: Using the target material as a pressure sensor

Corrosion-fatigue: a review of damage tolerance models

Computational modeling of dual-phase steels based on representative three-dimensional microstructures obtained from EBSD data

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