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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Texture and microstructure evolution in thermomechanically processed Mg-Ca and Mg-Zn-Ca alloys

Mg-Zn-Ca alloys have the potential for producing Mg alloy sheets with weaker basal textures and therefore improved formability. Thermomechanical processing (TMP) also plays a substantial role in determining the final sheet texture. The interplay of these variables, TMP and alloying, complicates comparisons of alloys across the literature. This work systematically explores the texture evolution and recrystallization behavior in Mg-Ca and Mg-Zn-Ca alloys during plane strain compression (PSC) using a Gleeble thermomechanical simulator. It is demonstrated that the basal texture intensity and texture characteristics change significantly during post-deformation annealing, particularly in the ternary alloys. It is also shown that careful selection of the TMP processing variables used during PSC is essential to producing weak textures. In particular, it is important to limit the recrystallization that occurs between compressive hits. This is achieved by adjusting solute content, strain rate, and the duration of the soak between passes.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evolution of Microstructure and Creep Behavior in an Fe-Ni-Cr-Nb-C Alloy during Service in Hydrocarbon Cracker Tubes

Heat resistant, cast austenitic Fe-Ni-Cr-Nb-C alloy tubes are used by the petrochemical industry to transport hydrocarbons at temperatures between 850 and 1050 °C. Exposure to carbon from the process stream and nitrogen from the air causes severe carburization and nitridation in the tube walls, which influences creep resistance and degrades their ductility. A better understanding of these processes would enable their service life to be extended. To this end, we report the results of an experimental and computational study of the changes in microstructure and creep behavior in a representative alloy during service. The microstructure of the fresh material is compared to that of 8- and 10-year-old tubes. The results confirm the presence of M{sub 23}C{sub 6}, M{sub 7}C{sub 3}, and M{sub 2}(CN) phases reported in prior studies, and also reveal the nucleation and growth of the carbo-nitride phase M{sub 6}(CN). We show that the spatial variations of carbide and nitride particle volume fractions in aged tubes can be predicted by a simple reaction–diffusion equation. In addition, the uniaxial compressive creep response of the fresh and aged tubes was obtained as functions of temperature and strain rate. The materials deform by power-law creep, with strain rate versus stress relation as ε-dot =Aσ{sup n}. Aging reduces the stress exponent from n = 8 in fresh tubes to n = 5 in aged tubes, and also reduces the pre-exponential coefficient A. Tests on model alloys with composition identical to that of the matrix combined with finite element simulations of creep in model microstructures reveal that Cr depletion is responsible for the change in stress exponent, while the change in A is caused by the increase in particle volume fraction. By combining the microstructure-scale simulations of creep with the predictions of the reaction–diffusion model of microstructure evolution, the creep behavior of tubes left in service beyond 10 years is estimated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗