Multiscale identification of parameters of inhomogeneous materials by means of global optimization methods

• Autorzy: Beluch W.
• Języki publikacji: EN

Abstrakty

EN

This paper deals with the identification of material parameters at a microscale on the basis of measurements at a macroscale. Inhomogeneous materials such as composites and porous media are considered. Numerical homogenization with the use of a representative volume element is performed to obtain a macroscopically homogenized equivalent material. The evolutionary algorithm is applied as the global optimization method to solve the identification task. Modal analysis is performed to collect data necessary for the identification. Different ranges of measurement errors are considered. A finite element method is employed to solve a boundary-value problem for both scales.

Słowa kluczowe

EN

identification; numerical homogenization; evolutionary algorithm; porous material; composite; measurement error

• Wydawca: Instytut Podstawowych Problemów Techniki PAN
• Czasopismo: Engineering Transactions
• Rocznik: 2017
• Tom: Vol. 65, iss. 1
• Strony: 19--24
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Beluch W.

• Institute of Computational Mechanics and Engineering Silesian University of Technology Konarskiego 18A, 44-105 Gliwice, Poland

Bibliografia

• 1. Zohdi T.I., Wriggers P., An introduction to computational micromechanics, Springer, Berlin – Heidelberg, 2005.
• 2. Kouznetsova V., Computational homogenization for the multi-scale analysis of multiphase materials, PhD thesis, Technische Universiteit Eindhoven, 2002.
• 3. Michalewicz Z., Fogel D., How to solve it: modern heuristics, Springer Science & Business Media, Berlin – Heidelberg, 2004.
• 4. He J., Fu Z-F., Modal analysis, Butterworth-Heinemann, Oxford (UK) – Woburn (United States), 2001.
• 5. Beluch W., Burczyński T., Two-scale identification of composites’ material constants by means of computational intelligence methods, Archives of Civil and Mechanical Engineering, 14(4): 636–646, 2014.
• 6. Deb K., Multi-objective optimization using evolutionary algorithms, Wiley, New York, 2001.
• 7. Beluch W., Długosz A., Multiobjective and multiscale optimization of composite materials by means of evolutionary computations, Journal of Theoretical and Applied Mechanics, 54(2): 397–409, 2016, doi: 10.15632/jtam-pl.54.2.397.
• 8. Ptaszny J., Fedeliński P., Numerical homogenization by using the fast multipole boundary element method, Archives of Civil and Mechanical Engineering, 11(1): 181–193, 2011, doi: 10.1016/S1644-9665(12)60182-4.
• 9. Hill R., Elastic properties of reinforced solids: Some theoretical principles, Journal of the Mechanics and Physics of Solids, 11(5): 357–372, 1963, doi: 10.1016/0022-5096(63)90036- X.
• 10. Zohdi T.I., Wriggers P., An introduction to computational micromechanics, Lecture Notes in Applied and Computational Mechanics, Springer, Berlin – Heidelberg, 2005.
• 11. Miehe C., Strain-driven homogenization of inelastic microstructures and composites based on an incremental variational formulation, International Journal for Numerical Methods in Engineering, 55(11): 1285–1322, 2002, doi: 10.1002/nme.515.
• 12. Mokhles Gerami F., Kakuee O., Mohammadi S., Porosity estimation of alumina samples based on resonant backscattering spectrometry, Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 373: 80–84, 2016, doi: 10.1016/j.nimb.2016.03.016.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).