LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Zhou, X.-Y.; Gosling, P.D.; Ullah, Z.; Kaczmarczyk, L.; Pearce, C.J. (2017)
Publisher: Elsevier BV
Journal: Applied Mathematical Modelling
Languages: English
Types: Article
Subjects: Applied Mathematics, Modelling and Simulation
This paper proposes a novel multi-scale approach for the reliability analysis of composite structures that accounts for both microscopic and macroscopic uncertainties, such as constituent material properties and ply angle. The stochastic structural responses, which establish the relationship between structural responses and random variables, are achieved using a stochastic multi-scale finite element method, which integrates computational homogenisation with the stochastic finite element method. This is further combined with the first- and second-order reliability methods to create a unique reliability analysis framework. To assess this approach, the deterministic computational homogenisation method is combined with the Monte Carlo method as an alternative reliability method. Numerical examples are used to demonstrate the capability of the proposed method in measuring the safety of composite structures. The paper shows that it provides estimates very close to those from Monte Carlo method, but is significantly more efficient in terms of computational time. It is advocated that this new method can be a fundamental element in the development of stochastic multi-scale design methods for composite structures.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] M.R. Gurvich, R.B. Pipes, Probabilistic strength analysis of four-directional laminated composites, Compos. Sci. Technol. 56 (6) (1996) 649-656.
    • [2] Q.-D. Zeng, L. Ling, Z.-L. Wang, Statistical strength of unidirectional composites and the effect of the interfacial shear strength, Compos. Sci. Technol. 56 (10) (1996) 1191-1200.
    • [3] A. Béakou, A. Mohamed, Influence of variable scattering on the optimum winding angle of cylindrical laminated composites, Compos. Struct. 53 (3) (2001) 287-293.
    • [4] D. Liu, N.A. Fleck, M.P.F. Sutcliffe, Compressive strength of fibre composites with random fibre waviness, J. Mech. Phys. Solids 52 (7) (2004) 1481-1505.
    • [5] D.J. Lekou, T.P. Philippidis, Mechanical property variability in FRP laminates and its effect on failure prediction, Compos. Part B: Eng. 39 (78) (2008) 1247-1256.
    • [6] M.R. Motley, Y.L. Young, Influence of uncertainties on the response and reliability of self-adaptive composite rotors, Compos. Struct. 94 (1) (2011) 114-120.
    • [7] M.B. Whiteside, S.T. Pinho, P. Robinson, Stochastic failure modelling of unidirectional composite ply failure, Reliab. Eng. Syst. Saf. 108 (0) (2012) 1-9.
    • [8] BS 4994, Specification for Design and Construction of Vessels and Tanks in Reinforced Plastics, British Standards Institution, London, 1987.
    • [9] C. Boyer, A. Bakou, M. Lemaire, Design of a composite structure to achieve a specified reliability level, Reliab. Eng. Syst. Saf. 56 (3) (1997) 273-283.
    • [10] B. Ellingwood, Toward load and resistance factor design for fiber-reinforced polymer composite structures, J. Struct. Eng. 129 (4) (2003) 449-458.
    • [11] M. Alqam, R. Bennett, A. Zureick, Probabilistic based design of concentrically loaded fiber-reinforced polymeric compression members, J. Struct. Eng. 130 (12) (2004) 1914-1920.
    • [12] H.G. Matthies, Uncertainty Quantification with Stochastic Finite Elements, John Wiley & Sons, Ltd, pp. 1-36.
    • [13] C.G. Soares, Reliability of components in composite materials, Reliab. Eng. Syst. Saf. 55 (2) (1997) 171-177.
    • [14] W. Chen, P. Jia, Interlaminar stresses analysis and the limit state function approximating methods for composite structure reliability assessment: A selected review and some perspectives, J. Compos. Mater. 47 (12) (2012) 1535-1547.
    • [15] M. Chiachio, J. Chiachio, G. Rus, Reliability in composites a selective review and survey of current development, Compos. Part B: Eng. 43 (3) (2012) 902-913.
    • [16] S. Sriramula, M.K. Chryssanthopoulos, Quantification of uncertainty modelling in stochastic analysis of FRP composites, Compos. Part A: Appl. Sci. Manuf. 40 (11) (2009) 1673-1684.
    • [17] S.W. Tsai, E.M. Wu, A general theory of strength for anisotropic materials, J. Compos. Mater. 5 (1) (1971) 58-80.
    • [18] M.J. Hinton, P.D. Soden, Predicting failure in composite laminates: the background to the exercise, Compos. Sci. Technol. 58 (7) (1998) 1001-1010.
    • [19] M. Hinton, A. Kaddour, The background to the second world-wide failure exercise, J. Compos. Mater. 46 (19-20) (2012) 2283-2294.
    • [20] A. Kaddour, M. Hinton, P. Smith, S. Li, The background to the third world-wide failure exercise, J. Compos. Mater. 47 (20-21) (2013) 2417-2426.
    • [21] P.D. Soden, M.J. Hinton, A.S. Kaddour, A comparison of the predictive capabilities of current failure theories for composite laminates, Composites Science and Technology 58 (7) (1998) 1225-1254.
    • [22] A.C. Orifici, I. Herszberg, R.S. Thomson, Review of methodologies for composite material modelling incorporating failure, Compos. Struct. 86 (1-3) (2008) 194-210.
    • [23] M.J. Hinton, A.S. Kaddour, P.D. Soden, A comparison of the predictive capabilities of current failure theories for composite laminates, judged against experimental evidence, Compos. Sci. Technol. 62 (12-13) (2002) 1725-1797.
    • [24] P. Nali, E. Carrera, A numerical assessment on two-dimensional failure criteria for composite layered structures, Compos. Part B: Eng. 43 (2) (2012) 280-289.
    • [25] H. Nakayasu, Z. Maekawa, A comparative study of failure criteria in probabilistic fields and stochastic failure envelopes of composite materials, Reliability Eng. Syst. Saf. 56 (3) (1997) 209-220.
    • [26] G. Cederbaum, I. Elishakoff, L. Librescu, Reliability of laminated plates via the first-order second-moment method, Compos. Structures 15 (2) (1990) 161-167.
    • [27] M.R. Gurvich, R.B. Pipes, Reliability of composites in a random stress state, Compos. Sci. Technol. 58 (6) (1998) 871-881.
    • [28] T.P. Philippidis, D.J. Lekou, Probabilistic failure prediction for FRP composites, Compos. Sci. Technol. 58 (12) (1998) 1973-1982.
    • [29] P.D. Gosling, Faimun, O. Polit, A high-fidelity first-order reliability analysis for shear deformable laminated composite plates, Compos. Struct. 115 (0) (2014) 12-28.
    • [30] D.M. Frangopol, S. Recek, Reliability of fiber-reinforced composite laminate plates, Probabilistic Engineering Mechanics 18 (2) (2003) 119-137.
    • [31] R.Y. Rubinstein, D.P. Kroese, Simulation and The Monte Carlo Method, Second, John Wiley & Sons, 2008.
    • [32] P.A.M. Lopes, H.M. Gomes, A.M. Awruch, Reliability analysis of laminated composite structures using finite elements and neural networks, Compos. Struct. 92 (7) (2010) 1603-1613.
    • [33] H.M. Gomes, A.M. Awruch, P.A.M. Lopes, Reliability based optimization of laminated composite structures using genetic algorithms and artificial neural networks, Struct. Saf. 33 (3) (2011) 186-195.
    • [34] M. Di Sciuva, D. Lomario, A comparison between monte carlo and forms in calculating the reliability of a composite structure, Compos. Struct. 59 (1) (2003) 155-162.
    • [35] K. Potter, B. Khan, M. Wisnom, T. Bell, J. Stevens, Variability, fibre waviness and misalignment in the determination of the properties of composite materials and structures, Compos. Part A: Appl. Sci. Manuf. 39 (9) (2008) 1343-1354.
    • [36] D.C. Charmpis, G.I. Schuýller, M.F. Pellissetti, The need for linking micromechanics of materials with stochastic finite elements: A challenge for materials science, Computational Materials Science 41 (1) (2007) 27-37.
    • [37] L.L. Graham-Brady, S.R. Arwade, D.J. Corr, M.A. Gutirrez, D. Breysse, M. Grigoriu, N. Zabaras, Probability and materials: from nano- to macro-scale: A summary, Probab. Eng. Mech. 21 (3) (2006) 193-199.
    • [38] Y. Rollet, M. Bonnet, N. Carrére, F.H. Leroy, J.F. Maire, Improving the reliability of material databases using multiscale approaches, Compos. Sci. Technol. 69 (1) (2009) 73-80.
    • [39] X.Y. Zhou, P.D. Gosling, Z. Ullah, L. Kaczmarczyk, C.J. Pearce, Exploiting the benefits of multi-scale analysis in reliability analysis for composite structures, Compos. Struct. 155 (2016) 197-212.
    • [40] M. Kami n´ski, M. Kleiber, Perturbation based stochastic finite element method for homogenization of two-phase elastic composites, Comp. Struct. 78 (6) (2000) 811-826.
    • [41] S. Sakata, F. Ashida, T. Kojima, Stochastic homogenization analysis on elastic properties of fiber reinforced composites using the equivalent inclusion method and perturbation method, Int. J. Solids Struct. 45 (25-26) (2008) 6553-6565.
    • [42] X.-Y. Zhou, P.D. Gosling, C.J. Pearce, L. Kaczmarczyk, Z. Ullah, Perturbation-based stochastic multi-scale computational homogenization method for the determination of the effective properties of composite materials with random poperties, Comput. Meth. Appl. Mech. Eng. 300 (2016) 84-105.
    • [43] C.C. Chamis, Probabilistic simulation of multi-scale composite behavior, Theor. Appl. Fract. Mech. 41 (1-3) (2004) 51-61.
    • [44] A. Shaw, S. Sriramula, P.D. Gosling, M.K. Chryssanthopoulos, A critical reliability evaluation of fibre reinforced composite materials based on probabilistic micro and macro-mechanical analysis, Compos. Part B: Eng. 41 (6) (2010) 446-453.
    • [45] H. Dehmous, H. Welemane, Multi-scale reliability analysis of composite structures application to the Laroin footbridge, Eng. Fail. Anal. 18 (3) (2011) 988-998.
    • [46] H. Welemane, H. Dehmous, Reliability analysis and micromechanics: A coupled approach for composite failure prediction, Int. J. Mech. Sci. 53 (11) (2011) 935-945.
    • [47] S. Sakata, F. Ashida, K. Enya, A microscopic failure probability analysis of a unidirectional fiber reinforced composite material via a multiscale stochastic stress analysis for a microscopic random variation of an elastic property, Comput. Mater. Sci. 62 (2012) 35-46.
    • [48] V.M.K. Akula, Multiscale reliability analysis of a composite stiffened panel, Compos. Struct. 116 (0) (2014) 432-440.
    • [49] C. Fang, M.C.H. Yam, A.C.C. Lam, L. Xie, Cyclic performance of extended end-plate connections equipped with shape memory alloy bolts, J. Constructional Steel Res. 94 (2014) 122-136.
    • [50] M.C.H. Yam, C. Fang, A.C.C. Lam, Y. Zhang, Numerical study and practical design of beam-to-column connections with shape memory alloys, J. Constructional Steel Res. 104 (2015) 177-192.
    • [51] M. Kleiber, T.D. Hien, The Stochastic Finite Element Method - Basic Perturbation Technique and Computer Implementation, John Wiley & Sons, 1992.
    • [52] M. Kami n´ski, The Stochastic Perturbation Method for Computational Mechanics, John Wiley & Sons, 2013.
    • [53] M. Kami n´ski, Homogenization with uncertainty in Poisson ratio for polymers with rubber particles, Compos. Part B: Eng. 67 (2015) 267-277.
    • [54] R.M. Christensen, The Theory of Materials Failure, Oxford University Press, United Kingdom, 2013.
    • [55] Kaczmarczyk et. al., Mesh Oriented Finite Element Method (MoFEM), Version 0.2, University of Glasgow, Glasgow, UK, 2015. URL https://bitbucket.org/ likask/mofem-cephas.
    • [56] R.E. Melchers, Structural Reliability Analysis and Prediction, Second, John Wiley & Sons, 2002.
    • [57] K. Breitung, Asymptotic approximations for multinormal integrals, J. Eng. Mech. 110 (3) (1984) 357-366.
    • [58] A. Der Kiureghian, H. Lin, S. Hwang, Second order reliability approximations, J. Eng. Mech. 113 (8) (1987) 1208-1225.
    • [59] A. Der Kiureghian, M. De Stefano, Efficient algorithm for second-order reliability analysis, J. Eng. Mech. 117 (12) (1991) 2904-2923.
    • [60] Y. Zhao, T. Ono, New approximations for sorm: Part 1 and 2, J. Eng. Mech. 125 (1) (1999) 79-93.
    • [61] Y.-G. Zhao, T. Ono, A general procedure for first/second-order reliabilitymethod (form/sorm), Struct. Safety 21 (2) (1999) 95-112.
    • [62] M.W. Hyer, Stree analysis of fiber-reinforced composite materials, Mechanical Engineering Series, McGraw-Hill, Boston, 1998.
    • [63] P.D. Soden, M.J. Hinton, A.S. Kaddour, Lamina properties, lay-up configurations and loading conditions for a range of fibre-reinforced composite laminates, Compos. Sci. Technol. 58 (7) (1998) 1011-1022.
    • [64] L. Van Den Einde, L. Zhao, F. Seible, Use of FRP composites in civil structural applications, Construction Build. Mater. 17 (67) (2003) 389-403.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

    Title Trust
    40
    40%
  • No similar publications.

Share - Bookmark

Cite this article