A Monte Carlo approach for scattering correction towards quantitative neutron imaging of polycrystals. Issue 2 (1st March 2018)

• Record Type: Journal Article
• Authors: Raventós, M.; Lehmann, E. H.; Boin, M.; Morgano, M.; Hovind, J.; Harti, R.; Valsecchi, J.; Kaestner, A.; Carminati, C.; Boillat, P.; Trtik, P.; Schmid, F.; Siegwart, M.; Mannes, D.; Strobl, M.; Grünzweig, C.
• Is Part Of: Journal of applied crystallography. Volume 51:Issue 2(2018)
• Page Start: 386
• Page End: 394
• Publication Date: 2018-03-01
• Subjects: neutron imaging -- quantification -- neutron scattering -- Monte Carlo methods; Crystallography -- Periodicals; 548.05
• DOI: 10.1107/S1600576718001607
• Languages: English
• ISSNs: 0021-8898

Abstract

Abstract : This article describes the development and application of a Monte Carlo tool to improve the quantification capabilities of neutron imaging applied to polycrystals. The combination of modelling and experimentation gives a better understanding of how scattering coming from polycrystalline samples affects neutron imaging experiments. Abstract : The development of neutron imaging from a qualitative inspection tool towards a quantitative technique in materials science has increased the requirements for accuracy significantly. Quantifying the thickness or the density of polycrystalline samples with high accuracy using neutron imaging has two main problems: (i) the scattering from the sample creates artefacts on the image and (ii) there is a lack of specific reference attenuation coefficients. This work presents experimental and simulation results to explain and approach these problems. Firstly, a series of neutron radiography and tomography experiments of iron, copper and vanadium are performed and serve as a reference. These materials were selected because they attenuate neutrons mainly through coherent (Fe and Cu) and incoherent (V) scattering. Secondly, an ad hoc Monte Carlo model was developed, based on beamline, sample and detector parameters, in order to simulate experiments, understand the physics involved and interpret the experimental data. The model, developed in the McStas framework, uses a priori information about the sample geometry and crystalline structure, as well as beamline settings, such as spectrum, geometry and detector type. The validity of the simulations is then verified with experimental results for the two problems that motivated this work: (i) the scattering distribution in transmission imaging and (ii) the calculated attenuation coefficients.