Modelling of Radiographic Inspections

  • A. Schumm
  • P. Duvauchelle
  • V. Kaftandjian
  • R. Jaenisch
  • C. Bellon
  • J. Tabary
  • F. Mathy
  • S. Legoupil
Conference paper
Part of the RILEM Bookseries book series (RILEM, volume 6)

Abstract

Computer modelling of non-destructive testing methods has come a long way from the beginnings in the mid 90s to today. Radiographic modelling for components with higher wall thicknesses, as they are typical for nuclear applications, must include precise predictions of scattered radiation and its impact in terms of contrast reduction. Dedicated or general purpose Monte Carlo methods with the ability to calculate higher order scattering events are the state of the art for these applications. Aerospace applications, on the other hand, have stronger requirements on the modelling code’s capabilities to import complex CAD geometries, and can benefit from faster analytical scatter models, limited to first or second order scattering events. Similar distinctions can be made for the various approaches proposed to accurately model geometrical and film unsharpness, film granularity, film responses, film/foil cartridges and photon noise. This article presents a state-of-the-art review of radiographic modelling from the perspective of two important application domains with very different requirements, nuclear and aerospace.

Keywords

Computer modelling film Monte-Carlo radiography selenium 

References

  1. [1].
    J. Tabary, P. Hugonnard, F. Mathy, “SINDBAD : a realistic multi-purpose and scalable X-ray simulation tool for NDT applications”, International Symposiun on DIR and CT, Lyon, June (2007)Google Scholar
  2. [2].
    R. Fernandez, A. Schumm, J. Tabary, P. Hugonnard, “Simulation Studies of Radiographic inspection with CIVA”, World Conference of Non Destructive Testing, Shanghai, (2008)Google Scholar
  3. [3].
    G.-R. Jaenisch, C. Bellon, and U. Ewert, “aRTist – Analytical RT Inspection Simulation Tool for Industrial Application.” Proceedings of the 17th World Conference on Non-Destructive Testing, Shanghai, China, International Committee on NDT, CDrom paper 64 (2008)Google Scholar
  4. [4].
    A. Bonin, B. Chalmond, B. Lavayssière, “Monte Carlo simulation of industrial radiography Images and experimental designs”, NDT&E International 35 (2002), pp 503–510CrossRefGoogle Scholar
  5. [5].
    G.-R. Jaenisch, C. Bellon, U. Samadurau, M. Zhukovskiy, S. Podoliako, “Monte Carlo Radiographic Model with CAD-based Geometry Description”, Insight 48(10) (2006), pp 618–623CrossRefGoogle Scholar
  6. [6].
    F. Inanc, “Scattering and its role in radiography simulations”, NDT&E International, Vol. 35(8), (2002), pp 581–593CrossRefGoogle Scholar
  7. [7].
    N. Freud, P. Duvauchelle, S. A. Pistrui-Maximean, J. -M. Létang and D. Babot “Deterministic simulation of first-order scattering in virtual X-ray imaging”, NIM B, Vol. 222., (2004), pp 285–300CrossRefGoogle Scholar
  8. [8].
    Ph. Duvauchelle, Nicolas Freud, Valérie Kaftandjian, Daniel Babot, “A computer code to simulate X-ray imaging techniques”. Nuclear Instruments and Methods in Physics Research B. (2000). pp 245–258Google Scholar
  9. [9].
    J. Tabary, A. Glière, R. Guillemaud, P. Hugonnard, F. Mathy, “Combination of high resolution analytically computed uncollided flux images with low resolution Monte Carlo computed scattered flux images”, IEEE Transactions on Nuclear Science, Vol. 51(1), pp 212–217, (2004).CrossRefGoogle Scholar
  10. [10].
    A. Schumm, U. Zscherpel, “Using the EN584-1 film characterization in radiographic modeling”, International Symposiun on DIR and CT, Lyon, June 2007Google Scholar
  11. [11].

Copyright information

© RILEM 2013

Authors and Affiliations

  • A. Schumm
    • 1
  • P. Duvauchelle
    • 2
  • V. Kaftandjian
    • 2
  • R. Jaenisch
    • 3
  • C. Bellon
    • 3
  • J. Tabary
    • 4
  • F. Mathy
    • 4
  • S. Legoupil
    • 5
  1. 1.Electricité de France R&DClamartFrance
  2. 2.INSA LyonLyonFrance
  3. 3.BAMBerlinGermany
  4. 4.CEA-LETI MINATECGrenobleFrance
  5. 5.CEA-LISTSaclayFrance

Personalised recommendations