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This paper deals with modelling and reconstruction of strain fields, relying upon data generated from neutron Bragg-edge measurements. We propose a probabilistic approach in which the strain field is modelled as a Gaussian process, assigned…

数据分析、统计与概率 · 物理学 2018-11-06 Carl Jidling , Johannes Hendriks , Niklas Wahlström , Alexander Gregg , Thomas B. Schön , Christopher Wensrich , Adrian Wills

This paper presents a proof-of-concept demonstration of triaxial strain tomography from Bragg-edge neutron imaging within a three-dimensional sample. Bragg-edge neutron transmission can provide high-resolution images of the average through…

Technological developments in high resolution time-of-flight neutron detectors have raised the prospect of tomographic reconstruction of elastic strain fields from Bragg-edge strain images. This approach holds the potential to provide a…

Bragg-edge strain imaging from energy-resolved neutron transmission measurements poses an interesting tomography problem. The solution to this problem will allow the reconstruction of detailed triaxial stress and strain distributions within…

Energy resolved neutron transmission techniques can provide high-resolution images of strain within polycrystalline samples allowing the study of residual strain and stress in engineered components. Strain is estimated from such data by…

计算工程、金融与科学 · 计算机科学 2020-04-28 Johannes Hendriks , Nicholas O'Dell , Adrian Wills , Anton Tremsin , Christopher Wensrich , Takenao Shinohara

Recently, a number of reconstruction algorithms have been presented for residual strain tomography from Bragg-edge neutron transmission measurements. In this paper, we examine whether strain tomography can also be achieved from diffraction…

计算物理 · 物理学 2020-01-29 A. W. T. Gregg , J. N. Hendriks , C. M. Wensrich , V. Luzin , A. Wills

Point by point strain scanning is often used to map the residual stress (strain) in engineering materials and components. However, the gauge volume and hence spatial resolution is limited by the beam defining apertures and can be…

We consider a method for neutron residual strain/stress analysis combining features of transmission strain tomography (e.g. through Braggs edge imaging) and neutron diffraction techniques. Analogous to transmission strain tomography, our…

应用物理 · 物理学 2019-06-18 V. Luzin , A. W. T. Gregg , J. N. Hendriks , C. M. Wensrich

Residual strain, a tensor quantity, is a critical material property that impacts the overall performance of metal parts. Neutron Bragg edge strain tomography is a technique for imaging residual strain that works by making conventional…

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,…

材料科学 · 物理学 2021-06-16 Axel Henningsson , Johannes Hendriks

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…

应用物理 · 物理学 2020-03-06 J. N. Hendriks , C. M. Wensrich , A. Wills

A pulsed neutron imaging technique is used to reconstruct the residual strain within a polycrystalline material from Bragg edge strain images. This technique offers the possibility of a nondestructive analysis of strain fields with a high…

计算工程、金融与科学 · 计算机科学 2020-02-28 Riya Aggarwal , Mike Meylan , Bishnu Lamichhane , Chris Wensrich

The microscopic distribution of strain and stress plays a crucial role for the performance, safety, and lifetime of components in aeronautics, automotive and critical infrastructure [1]. While non-destructive methods for measuring the…

材料科学 · 物理学 2025-04-09 Peter Modregger , James. A. D. Ball , Felix Wittwer , Ahmar Khaliq , Jonathan Wright

Gaussian process regression techniques have been used in fluid mechanics for the reconstruction of flow fields from a reduction-of-dimension perspective. A main ingredient in this setting is the construction of adapted covariance functions,…

流体动力学 · 物理学 2026-01-13 Adrian Padilla-Segarra , Pascal Noble , Olivier Roustant , Éric Savin

Examples with bound information on the regression function and density abound in many real applications. We propose a novel approach for estimating such functions by incorporating the prior knowledge on the bounds. Specially, a Gaussian…

统计方法学 · 统计学 2018-10-30 Jize Zhang , Lizhen Lin

Gaussian process regression is a popular Bayesian framework for surrogate modeling of expensive data sources. As part of a broader effort in scientific machine learning, many recent works have incorporated physical constraints or other a…

机器学习 · 计算机科学 2021-01-07 Laura Swiler , Mamikon Gulian , Ari Frankel , Cosmin Safta , John Jakeman

We set forth a new method for generating model-agnostic, nonparametric priors for neutron star equation-of-state inference that are stable, causal and thermodynamically consistent by construction. This generalizes Gaussian processes to…

高能天体物理现象 · 物理学 2026-05-12 Tyler Gorda , Oleg Komoltsev , Aleksi Kurkela , Eirik Sunde

Over the past decade, a number of algorithms for full-field elastic strain estimation from neutron and X-ray measurements have been published. Many of the recently published algorithms rely on modelling the unknown strain field as a…

计算物理 · 物理学 2020-07-10 A. W. T. Gregg , J. N. Hendriks , C. M. Wensrich , N. O'Dell

The projected gradient descent (PGD) method has shown to be effective in recovering compressed signals described in a data-driven way by a generative model, i.e., a generator which has learned the data distribution. Further reconstruction…

机器学习 · 计算机科学 2021-09-03 Muhammad Fadli Damara , Gregor Kornhardt , Peter Jung

In the past few decades, fibre Bragg grating (FBG) sensors have gained a lot of attention in the field of distributed point strain measurement. One of the most interesting properties of these sensors is the presumed linear relationship…

应用物理 · 物理学 2018-08-17 Aydin Rajabzadeh , Richard Heusdens , Richard C. Hendriks , Roger M. Groves
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