Chrome Extension
WeChat Mini Program
Use on ChatGLM

Effect of Irradiation-Induced Strength Anisotropy on the Reorientation Trajectories and Fragmentation Behavior of Grains in BCC Polycrystals under Tensile Loading

ACTA MATERIALIA(2024)

Univ Alabama | Univ Illinois | Argonne Natl Lab

Cited 0|Views18
Abstract
We present a combined experimental and computational study exploring the effects of strength anisotropy on the grain reorientation trajectories in neutron-irradiated BCC polycrystals subjected to uniaxial tensile loading. We observe through in situ high-energy X-ray diffraction microscopy measurements of a model BCC alloy, Fe-9wt.%Cr, that the grains in irradiated samples exhibit reorientation trajectories that deviate more substantially from classical expectations than those in the unirradiated counterpart. We hypothesize that irradiation-induced strength anisotropy is a major influence on this behavior. Utilizing crystal plasticity finite element modeling, we isolate the effects of strength anisotropy by performing a suite of simulations in which we systematically strengthen select slip systems. Reorientation trajectories are compared against a datum of Taylor model predictions, and the deviation from classical expectations is analyzed through the lens of slip activity and availability. We further describe observations regarding the propensity of samples with high degrees of strength anisotropy to exhibit grain fragmentation. Overall, computational results provide insight on and quantification of the effects of strength anisotropy on reorientation trajectories and grain fragmentation, and align well with experimental observations, suggesting strength anisotropy as a plausible contributing mechanism to the observed phenomena.
More
Translated text
Key words
Crystal plasticity finite element method,High energy diffraction microscopy,Strength anisotropy,Reorientation,Irradiation
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest