Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 80 tok/s
Gemini 2.5 Pro 60 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 87 tok/s Pro
Kimi K2 173 tok/s Pro
GPT OSS 120B 433 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

Intragranular Strain Estimation in Far-Field Scanning X-ray Diffraction using a Gaussian Processes (2102.11018v2)

Published 15 Feb 2021 in cond-mat.mtrl-sci and physics.data-an

Abstract: A new method for estimation of intragranular strain fields in polycrystalline materials based on scanning three-dimensional X-ray diffraction data (scanning-3DXRD) is presented and evaluated. Given an apriori known anisotropic compliance, the regression method enforces the balance of linear and angular momentum in the linear elastic strain field reconstruction. By using a Gaussian Process (GP), the presented method can yield a spatial estimate of the uncertainty of the reconstructed strain field. Furthermore, constraints on spatial smoothness can be optimised with respect to measurements through hyperparameter estimation. These three features address weaknesses discussed for previously existing scanning-3DXRD reconstruction methods and, thus, offers a more robust strain field estimation. The method is twofold validated; firstly by reconstruction from synthetic diffraction data and, secondly, by reconstruction of previously studied tin (Sn) grain embedded in a polycrystalline specimen. Comparison against reconstructions achieved by a recently proposed algebraic inversion technique is also presented. It is found that the GP regression consistently produces reconstructions with lower root mean squared errors, mean absolute errors and maximum absolute errors across all six components of strain.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.