Finite element approach to Bragg edge neutron strain tomography


  • Riya Aggarwal University of Newcastle
  • Mike Meylan University Of Newcastle
  • Bishnu Lamichhane University of Newcastle
  • Chris Wensrich University of Newcastle



A number of techniques and applications in neutron imaging that exploit wavelength resolved measurements have been developed recently. One such technique, known as energy resolved neutron imaging, receives ample attention because of its capability to not only visualise but to also quantify physical attributes with spatial resolution. The objective of this article is to develop a reconstruction algorithm for elastic strain tomography from Bragg edge neutron transmission strain images obtained from a pulsed neutron beam with high resolution. This technique has several advantages over those using monochromatic neutron beams from continuous sources; for example, finer wavelength resolution. In contrast to the conventional radon based computed tomography, wherein neutron transmission revolves around the inversion of the longitudinal ray transform that has uniqueness issues, the reconstruction in the proposed algorithm is based on the least squares approach, constrained by an equilibrium formulated through the finite element method.


  • B. Abbey, S. Y. Zhang, W. J. J. Vorster, and A. M. Korsunsky. Feasibility study of neutron strain tomography. Proc. Eng., 1\penalty 0 (1):185–188, 2009. doi:10.1016/j.proeng.2009.06.043.
  • R. Aggarwal, M. H. Meylan, B. P. Lamichhane, and C. M. Wensrich. Energy resolved neutron imaging for strain reconstruction using the finite element method. J. Imag., 6(3):13, 2020. doi:10.3390/jimaging6030013.
  • J. N. Hendriks, A. W. T. Gregg, C. M. Wensrich, A. S. Tremsin, T. Shinohara, M. Meylan, E. H. Kisi, V. Luzin, and O. Kirsten. Bragg-edge elastic strain tomography for in situ systems from energy-resolved neutron transmission imaging. Phys. Rev. Mat., 1:053802, 2017. doi:10.1103/PhysRevMaterials.1.053802.
  • C. Jidling, J. Hendriks, N. Wahlstrom, A. Gregg, T. B. Schon, C. Wensrich, and A. Wills. Probabilistic modelling and reconstruction of strain. Nuc. Inst. Meth. Phys. Res. B, pages 141–155, 2018. doi:10.1016/j.nimb.2018.08.051.
  • W. R. B. Lionheart and P. J. Withers. Diffraction tomography of strain. Inv. Prob., 31:045005, 2015. doi:10.1088/0266-5611/31/4/045005.
  • C. E. Rasmussen and C. K. I. Williams. Gaussian processes for machine learning. MIT Press, 2006. URL
  • C. M. Wensrich, E. Kisi, V. Luzin, and O. Kirstein. Non-contact measurement of the stress within granular materials via neutron diffraction. AIP Conf. Proc., 1542:441–444, 2013. doi:10.1063/1.4811962.
  • R. Woracek, J. Santisteban, A. Fedrigo, and M. Strobl. Diffraction in neutron imaging–-a review. Nuc. Inst. Meth. Phys. Res. A, 878:141–158, 2018. doi:10.1016/j.nima.2017.07.040.





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