Top

Russian Journal of Nondestructive Testing

Published in:

01-03-2021 | X-RAY METHODS

Algorithms for Modeling the Formation and Processing of Information in X-Ray Tomography of Foam Materials

Authors: S. P. Osipov, I. A. Prischepa, S. V. Chakhlov, O. S. Osipov, E. Yu. Usachev

Published in: Russian Journal of Nondestructive Testing | Issue 3/2021

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract—

Algorithms for modeling the spatial structure of foams for the formation of projections in X-ray computed tomography and subsequent reconstruction of the internal structure of the samples have been proposed. Algorithms are the basis for numerical models of the analyzed systems as applied to foam control. To demonstrate the capabilities of the developed algorithms, sinograms and results of reconstruction of the internal structure of foam samples with variation of their parameters were obtained.

previous article Calculation Model of X-Ray Computed Tomography with Density Assessment Function

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Farhadi, S., Kafili, D., and Ziadloo, S., Review of aluminum foam applications in architecture, Eur. J. Eng. Sci. Technol., 2020, vol. 3, no. 1, pp. 62–70. https://doi.org/10.33422/ejest.v3i1.162CrossRef

Kausar, A., Advances in polymer-anchored carbon nanotube foam: a review, Polym.-Plast. Technol. Mater., 2019, vol. 58, no. 18, pp. 1965–1978. https://doi.org/10.1080/25740881.2019.1599945CrossRef

Suvorova, O.V. and Makarov, D.V., Foam glass and foam materials based on ash-slag wastes from thermal power plants, Glass Ceram., 2019, vol. 76, no. 5—6, pp. 188–193. https://doi.org/10.1007/s10717-019-00162-xCrossRef

Chen, K., Guo, L., and Wang, H., A review on thermal application of metal foam, Sci. China. Technol. Sci., 2020, pp. 1–22. https://doi.org/10.1007/s11431-020-1637-3

Raj, A., Sathyan, D., and Mini, K.M., Physical and functional characteristics of foam concrete: A review, Constr. Build. Mat., 2019, vol. 221, pp. 787–799. https://doi.org/10.1016/j.conbuildmat.2019.06.052CrossRef

Fu, Y., Wang, X., Wang, L., and Li, Y., Foam concrete: A state of the art and state of the practice review, Adv. Mat. Sci. Eng., 2020, vol. 2020, Article ID: 6153602. https://doi.org/10.1155/2020/6153602CrossRef

Duarte, I., Fiedler, T., and Krstulović-Opara, L., and Vesenjak, M., Brief review on experimental and computational techniques for characterization of cellular metals, Metals, 2020, vol. 10, no. 6, article ID: 726. https://doi.org/10.3390/met10060726CrossRef

Spowage, A.C., Shacklock, A.P., Malcolm, A.A., May, S.L., Tong, L., and Kennedy, A.R., Development of characterisation methodologies for macroporous materials, J. Porous Mater., 2006, vol. 13, nos. 3—4, pp. 431–438. https://doi.org/10.1007/s10934-006-8042-1CrossRef

Peng, R., Yang, Y., Ju, Y., Mao, L., and Yang, Y., Computation of fractal dimension of rock pores based on gray CT images, Chin. Sci. Bull., 2011, vol. 56, No. 31, pp. 3346–3357. https://doi.org/10.1007/s11434-011-4683-9CrossRef

10.

Umbach, C., and Middendorf, B., 3D structural analysis of construction materials using high-resolution computed tomography, Mater. Today: Proc., 2019, vol. 15, pp. 356–363. https://doi.org/10.1016/j.matpr.2019.04.094CrossRef

11.

Abd Elrahman, M., El Madawy, M.E., Chung, S.Y., Majer, S., Youssf, O., and Sikora, P., An investigation of the mechanical and physical characteristics of cement paste incorporating different air entraining agents using X-ray micro-computed tomography, Crystals, 2020, vol. 10, No. 1, article ID: 23. https://doi.org/10.3390/cryst10010023CrossRef

12.

Miedzińska, D., Niezgoda, T., and Gieleta, R., Numerical and experimental aluminum foam microstructure testing with the use of computed tomography, Comput. Mater. Sci., 2012, vol. 64, pp. 90–95. https://doi.org/10.1016/j.commatsci.2012.02.021CrossRef

13.

Elmoutaouakkil, A., Fuchs, G., Bergounhon, P., Peres, R., and Peyrin, A., Three-dimensional quantitative analysis of polymer foams from synchrotron radiation x-ray microtomography, J. Phys. D: Appl. Phys., 2003, vol. 36, No. 10A, pp. A37–43. https://doi.org/10.1088/0022-3727/36/10A/308CrossRef

14.

Lin, C.L., Videla, A.R., Yu, Q., and Miller, J.D., Characterization and analysis of porous, brittle solid structures by X ray micro computed tomography, JOM, 2010, vol. 62, No. 12, pp. 86–89. https://doi.org/10.1007/s11837-010-0188-2CrossRef

15.

Utsunomiya, H. and Matsumoto, R., Deformation processes of porous metals and metallic foams, Proc. Mater. Sci., 2014, vol. 4, pp. 245–249.https://doi.org/10.1016/j.mspro.2014.07.614CrossRef

16.

Yuasa, N., Kasai, Y., and Matsui, I., Inhomogeneous distribution of compressive strength from surface layer to interior of concrete in structures, Spec. Publ., 2000, vol. 192, pp. 269–282.

17.

Wei, S., Yiqiang, C., Yunsheng, Z., and Jones, M.R., Characterization and simulation of microstructure and thermal properties of foamed concrete, Constr. Build. Mater., 2013, vol. 47, pp. 1278–1291. https://doi.org/10.1016/j.conbuildmat.2013.06.027CrossRef

18.

Qian, R., Liu, G., Liu, Z., She, W., Qiao, H., and Zhang, Y., Investigations on three-dimensional pore-structure in cementitious materials using metal centrifugation porosimetry and simulation, Mater. Lett., 2021, vol. 282, article ID: 128684. https://doi.org/10.1016/j.matlet.2020.128684CrossRef

19.

Wei, Y., Olsen, D.H., Miller, C.M., Wagner, K.B., Keyhani, A., Thadhani, N., and Zhou, M., Computational design of three-dimensional multi-constituent material microstructure sets with prescribed statistical constituent and geometric attributes, Multiscale Sci. Eng., 2020, vol. 2, pp. 7–19. https://doi.org/10.1007/s42493-020-00032-7CrossRef

20.

Hsieh, J., Computed tomography: principles, design, artifacts, and recent advances. 3rd rev. ed., Bellingham: SPIE Press, 2015.CrossRef

21.

Sarantites, D.G. and Sobotka, L.G., Computational templates for introductory nuclear science using Mathcad, Am. J. Phys., 2013, vol. 81, No. 1, pp. 44–49. https://doi.org/10.1119/1.4764079CrossRef

22.

Croom, B.P., Jin, H., Mills, B., Carroll, J., Long, K., Brown, J., and Li, X., Damage mechanisms in elastomeric foam composites: Multiscale X-ray computed tomography and finite element analyses, Compos. Sci. Technol., 2019, vol. 169, pp. 195–202. https://doi.org/10.1016/j.compscitech.2018.11.025CrossRef

23.

Jabarkhyl, S., Barigou, M., Zhu, S., Rayment, P., Lloyd, D.M., and Rossetti, D., Foams generated from viscous non-Newtonian shear-thinning liquids in a continuous multi rotor-stator device, Innovative Food Sci. Emerging Technol., 2020, vol. 59, article ID: 102231. https://doi.org/10.1016/j.ifset.2019.102231CrossRef

24.

Osipov S.P., Yadrenkin I.G., Chakhlov S.V., Osipov O.S., Usachev E.Yu. Simulation modelling in digital radiography with allowance for spatial outlines of test objects, Russ. J. Nondestr. Testing, 2020, vol. 56, no. 8, pp. 647–660. https://doi.org/10.1134/S1061830920080082CrossRef

25.

Osipov, S.P., Yadrenkin, I.G., Chakhlov, S.V., Osipov, O.S., Usachev, E.Yu., and Manushkin, A.A., Computational model of X-ray computed tomography with density estimation function, Defektoskopiya, 2021, no. 3, pp. 37–52.

26.

Feldkamp, L.A., Davis, L.C., and Kress, J.W., Practical cone-beam algorithm, J. Opt. Soc. Am. A, 1984, vol. 1, no. 6, pp. 612–619.CrossRef

27.

Hiriyannaiah, H.P., X-ray computed tomography for medical imaging, IEEE Signal Process. Mag., 1997, vol. 14, no. 2, pp. 42–59. https://doi.org/10.1109/79.581370CrossRef

28.

Kachelrieß, M., Knaup, M., and Kalender, W.A., Extended parallel backprojection for standard threedimensional and phase-correlated four-dimensional axial and spiral cone-beam CT with arbitrary pitch, arbitrary cone angle, and 100% dose usage, Med. Phys., 2004, vol. 31, No. 6, pp. 1623–1641. https://doi.org/10.1118/1.1755569CrossRef

29.

Gribbon, K.T. and Bailey, D.G., A novel approach to real-time bilinear interpolation, Proc. DELTA 2004. Second IEEE Int. Workshop Electron. Des., Test, Appl., 2004, pp. 126–131. https://doi.org/10.1109/DELTA.2004.10055

30.

Shepp, L.A. and Logan, B.F., The Fourier reconstruction of a head section, IEEE Trans. Nucl. Sci., 1974, vol. 21, no. 3, pp. 21–43. https://doi.org/10.1109/TNS.1974.6499235CrossRef

31.

Lehmhus, D., Vesenjak, M., de Schampheleire, S., and Fiedler, T., From stochastic foam to designed structure: Balancing cost and performance of cellular metals, Materials, 2017, vol. 10, No. 8, article ID: 922. https://doi.org/10.3390/ma10080922CrossRef

32.

Du Plessis, A., Yadroitsava, I., and Yadroitsev, I., Effects of defects on mechanical properties in metal additive manufacturing: A review focusing on X-ray tomography insights, Mater. Des., 2020, vol. 187, article ID: 108385. https://doi.org/10.1016/j.matdes.2019.108385CrossRef

Title: Algorithms for Modeling the Formation and Processing of Information in X-Ray Tomography of Foam Materials
Authors: S. P. Osipov
I. A. Prischepa
S. V. Chakhlov
O. S. Osipov
E. Yu. Usachev
Publication date: 01-03-2021
Publisher: Pleiades Publishing
Published in: Russian Journal of Nondestructive Testing / Issue 3/2021
Print ISSN: 1061-8309
Electronic ISSN: 1608-3385
DOI: https://doi.org/10.1134/S1061830921030050

Springer Professional

Abstract—

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Other articles of this Issue 3/2021

Effect of Grinding Environments on Magnetic Response of AISI D2 Tool Steel

Indirect Evaluation of the Compressive Strength of Recycled Aggregate Concrete at Long Ages and after Exposure to Freezing or Elevated Temperatures

Analyzing Ultrasonic Signal Parameters during High-Speed Rail Inspection

Calculation Model of X-Ray Computed Tomography with Density Assessment Function

Automated System for Complex Non-Destructive Testing of the Structure and Mechanical Properties of Mechanical Engineering Materials

Premium Partners