# A Bayesian Approach to Triaxial Strain Tomography from High-energy X-ray Diffraction

## TL;DR

This paper introduces a Bayesian Gaussian process model for 3D strain field tomography using high-energy X-ray diffraction, enabling rapid, high-resolution measurements with minimal rotation, and demonstrates its effectiveness through simulations.

## Contribution

It presents a novel GP-based method for 3D strain tomography from high-energy X-ray data, incorporating static equilibrium constraints and achieving single-axis rotation reconstruction.

## Key findings

- Effective in rejecting Gaussian noise in simulations
- Capable of 3D strain reconstruction with a single rotation axis
- Builds on previous 2D neutron measurement methods

## Abstract

Diffraction of high-energy X-rays produced at synchrotron sources can provide rapid strain measurements, with high spatial resolution, and good penetrating power. With an uncollimated diffracted beam, through thickness averages of strain can be measured using this technique, which poses an associated rich tomography problem. This paper proposes a Gaussian process (GP) model for three-dimensional strain fields satisfying static equilibrium and an accompanying algorithm for tomographic reconstruction of strain fields from high-energy X-ray diffraction. We present numerical evidence that this method can achieve triaxial strain tomography in three-dimensions using only a single axis of rotation. The method builds upon recent work where the GP approach was used to reconstruct two-dimensional strain fields from neutron based measurements. A demonstration is provided from simulated data, showing the method is capable of rejecting realistic levels of Gaussian noise.