Paper Title:
High Resolution Orientation Distribution Function
  Abstract

A new method for reconstructing a High Resolution Orientation Distribution Function (HRODF) from X-ray diffraction data is presented. It is shown that the method is capable of accommodating very localized features, e.g. sharp peaks from recrystallized grains on a background of a texture component from the deformed material. The underlying mathematical formalism supports all crystallographic space groups and reduces the problem to solving a (large) set of linear equations. An implementation on multi-core CPUs and Graphical Processing Units (GPUs) is discussed along with an example on simulated data.

  Info
Periodical
Materials Science Forum (Volumes 702-703)
Chapter
Chapter 4: Technique
Edited by
Asim Tewari, Satyam Suwas, Dinesh Srivastava, Indradev Samajdar and Arunansu Haldar
Pages
536-539
DOI
10.4028/www.scientific.net/MSF.702-703.536
Citation
S. Schmidt, N. F. Gade-Nielsen, M. Høstergaard, B. Dammann, I. G. Kazantsev, "High Resolution Orientation Distribution Function", Materials Science Forum, Vols. 702-703, pp. 536-539, 2012
Online since
December 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Zi Long Hao, Xin Jian Liu
Chapter 10: Sensors, Measurement, Detection and Intelligent Information and Data Processing, Fault Diagnosis
Abstract:A faster algorithm for calculating the shortest distance between two spatial bodies based on existing algorithms was presented. A simulation...
1560
Authors: Xiao Feng Li, Peng Fan, Xiao Hua Liu, Xing Chao Wang, Chuan Hu, Chun Xiang Liu, Shi Guang Bie
Chapter 3: Automation, Information Technologies and Data Processing
Abstract:Because of abundant deep scene nodes in 3D emulational scene of live working, the existing three-dimensional scene data organization methods...
1021