Support for Decision Making in Design of Composite Laminated Structures. Part 1: Parametric Knowledge Model
Source abstract
Abstract
The design process of laminated composites faces two challenges: the engineer designs the product and its morphology, but also, simultaneously, the material. The number of design solutions can be huge since the solution space is very large. Standard CAE systems (CAD, Finite Element Simulation) do not offer to the designer an approach to explore design spaces easily handling design parameters that are intrinsic to the laminate structures: number of plies, layers’ constitutive laws, viscoelastic capacity of the matrix and volume fraction of fibers. This paper provides a new model of behavior making explicit these design parameters. This Parametric and reduced Behavior Model (PRBM) allows engineers to make rapid simulations of the product they are creating. Integrated in a meta-model of Knowledge, it is combined to usual specific knowledge that are typically the domain of composite experts and manufacturing experts. Our PRBM is made from a separated numerical method, next enabling (1) a multiscale approach: the engineer can implement reasoning either at the scale of the fiber, or at the scale of the ply, at the scale of the plies interfaces, at the scale of the lamination or at the scale of the structure, or, (2) a multiphysical approach: the engineer can independently manage the mechanical effect of each ply and each interface, either in static or dynamic cases; in the latter, the creeping behavior can be considered. Two simple cases are presented to illustrate the relevance of the PRBM when simulating composite structures: one under a static load and the having a dynamic behavior.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Composite Structure Analysis and Optimization · Topology Optimization in Engineering · Composite Material Mechanics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (32)
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1. Bassam, E.S., Hallett, S.R.: Multiscale surrogate modelling of the elastic response of thick composite structures with embedded defects and features. Compos. Struct. Compos. Struct. 200, 781–798, Elsevier (2018). https://doi.org/10.1016/j.compstruct.2018.05.07810.1016/j.compstruct.2018.05.078 ↗
2. Beaumont, P.W.R.: On the problems of cracking and the question of structural integrity of engineering. Compos. Mater. Appl. Compos. Mater. 21(1), 5–43, Springer (2014). https://doi.org/10.1007/s10443-013-9356-110.1007/s10443-013-9356-1 ↗
3. Bogdanor, M., Oskay, C., Clay, S.: Multiscale modeling of failure in composites under model parameter uncertainty. Comput. Mech. 56(3), 389–404, Springer (2015). https://doi.org/10.1007/s00466-015-1177-710.1007/s00466-015-1177-7 ↗
4. Bognet, B., Bordeu, F., Chinesta, F., Leygue, A., Poitou, A.: Advanced simulation of models defined in plate geometries: 3D solutions with 2D computational complexity. Comput. Methods Appl. Mech. Eng. 201–204, 1–12 (2012). https://doi.org/10.1016/j.cma.2011.08.02510.1016/j.cma.2011.08.025 ↗
5. Carrera, E.: Theories and finite elements for multilayered, anisotropic, composite plates and shells. Arch. Comput. Methods Eng. 9, 87–140 (2002). https://doi.org/10.1007/BF0273664910.1007/BF02736649 ↗
6. Carrera, E., Pagani, A.: Multi-line enhanced beam model for the analysis of laminated composite structures. Compos. Part B Eng. 57, 112–119 (2014). https://doi.org/10.1016/j.compositesb.2013.09.04610.1016/j.compositesb.2013.09.046 ↗
7. Chinesta, F., Leygue, A., Bordeu, F., Aguado, J.V., Cueto, E., Gonzalez, D., Alfaro, I., Ammar, A., Huerta, A.: PGD-based computational Vademecum for efficient design, optimization and control. Archives of Computational Methods in Engineering. 20(1), 31–59 (2013, Springer). https://doi.org/10.1007/s11831-013-9080-x10.1007/s11831-013-9080-x ↗
8. Darko, Ivančević, Smojver, I.: Explicit multiscale modelling of impact damage on laminated composites – part i: validation of the micromechanical model. Compos. Struct 145, Elsevier, (2016). doi: https://doi.org/10.1016/j.compstruct.2016.02.04810.1016/j.compstruct.2016.02.048 ↗
9. De Faria, A.R.: Optimization of composite structures under multiple load cases using a discrete approach based on lamination parameters. Int. J. Numer. Methods Eng. 104(9), 827–843, International Journal for Numerical method in Engineering, Wiley (2015). https://doi.org/10.1002/nme.494110.1002/nme.4941 ↗
10. Fontecha Dulcey, G., Fischer, X., Joyot, P.: An experiment-based method for parameter identification of a reduced multiscale parametric viscoelastic model of a laminated composite beam. Multiscale Multidiscip. Model. Exp. Des. (2018a). https://doi.org/10.1007/s41939-018-0018-810.1007/s41939-018-0018-8 ↗
11. Fontecha Dulcey, G., Fischer, X., Joyot, P., Fadel G.: Support for decision making in Design of Composite Laminated Structures; part 2: reduced parametric model-based optimization. Springer Nature (2018b)10.1007/s10443-018-9741-x ↗
12. Galiotis C.P.: Interfacial damage modelling of composites, pp. 33–64, A. in Multi-Scale Modelling of Composite Material Systems 1st Edition, Soutis C., Beaumont P W R Eds., Woodhead Publishing ISBN: 9781855739369, (2005)
13. Ghiasi, H., Pasinin, D., Lessard, L.: Optimum stacking sequence design of composite materials part I: constant stiffness design. Compos. Struct. 90(1), 1–11, Elsevier (2009). https://doi.org/10.1016/j.compstruct.2009.01.00610.1016/j.compstruct.2009.01.006 ↗
14. Hosseini Kordkheili, S.A., Toozandehjani, H., Soltani, Z.: A progressive multi-scale fatigue model for life prediction of laminated composites. J. Compos. Mater. 51(20), 2949–2960, Sage (2017). https://doi.org/10.1177/002199831770961010.1177/0021998317709610 ↗
15. Jeong Sik, K., Arronche, L., Farrugia, A., Muliana, A., La Saponara, V.: Multi-scale modeling of time-dependent response of smart sandwich constructions. Compos. Struct. 93(9), 2196–2207, Elsevier (2011). https://doi.org/10.1016/j.compstruct.2011.03.006201110.1016/j.compstruct.2011.03.006 ↗
16. Kwon, Y.W., Allen, D.H., Talreja, R.: Multiscale Modeling and Simulation of Composite Materials and Structures. Springer, New York (2008)10.1007/978-0-387-68556-4 ↗
17. Ladevèze, P.: Multiscale modelling and computational strategies for composites. Int. J. Num. Method Eng. 60(1), 233–253, Wiley (2004). https://doi.org/10.1002/nme.96010.1002/nme.960 ↗
18. Macquart, T., Maes, V., Bordogna, M.T., Pirrera, A., Weaver, P.M.: Optimisation of composite structures – enforcing the feasibility of lamination parameter constraints with computationally-efficient maps. Compos. Struct. 192, 605–615 (2018). https://doi.org/10.1016/j.compstruct.2018.03.04910.1016/j.compstruct.2018.03.049 ↗
19. Llorca, J.L., Gonzalez, C., Molina-Aldareguia, J., Lopes, C.S.: Multiscale modeling of composites: toward virtual testing and beyond. J. Min. Metals Mater. Soc. 65(2), 1–11 (2012). https://doi.org/10.1007/s11837-012-0509-810.1007/s11837-012-0509-8 ↗
20. Masoumi, S., Salehi, M., Akhlaghi, M.: Nonlinear viscoelastic analysis of laminated composite plates – a multi scale approach, Int. J. Recent Adv. Mech. Eng. (IJMECH) 2 (2), (2013)
21. McCartney, L.N: Multi-scale predictive modelling of cracking in laminate composites, pp. 65–98, A. in Multi-Scale Modelling of Composite Material Systems 1st Edition, Soutis C., Beaumont P W R Eds., Woodhead Publishing. ISBN: 9781855739369, (2005)
22. Mitsunori, M., Sugiyamat, Y.: Optimum design of laminated composite plates using lamination parameters. AIAA J. 31(5), 921–922 (1993). https://doi.org/10.2514/3.4903310.2514/3.49033 ↗
23. Monte, S.M.C., Infante, V., Madeira, J.F.A., Moleiro, F.: Optimization of fibers orientation in a composite specimen. Mech. Adv. Mater. Struct. 24(5), 410–416, Talyor and Francis (2017). https://doi.org/10.1080/15376494.2016.119109910.1080/15376494.2016.1191099 ↗
24. Prulière, E., Chinesta, F., Ammar, A.: On the deterministic solution of multidimensional parametric models using the proper generalized decomposition. Math. Comput. Simul. 81, 791–810 (2010). https://doi.org/10.1016/j.matcom.2010.07.01510.1016/j.matcom.2010.07.015 ↗
25. Ranaivomiarana N., Irisarri F.X., Bettebghor D., Desmorat B., Concurrent optimization of material spatial distribution and material anisotropy repartition for two-dimensional structures. Continuum Mech. Thermodynam. 1–14, , Springer, (2018). doi: https://doi.org/10.1007/s00161-018-0661-710.1007/s00161-018-0661-7 ↗
26. Reddy, J.N. (ed.): Mechanics of composite materials. Springer Netherlands, Dordrecht (1994)
27. Sonmez, F.O.: Optimum design of composite structures: a literature survey (1969–2009). J. Reinforced Plastics Compos. 36(1), 3–39 (2017, Sage Journals). https://doi.org/10.1177/073168441666826210.1177/0731684416668262 ↗
28. Soutis, C., Beaumont, P.W.R.: Multi-scale modelling of composite material systems 1st Edition, Woodhead Publishing. ISBN: 9781855739369, (2005a)10.1533/9781845690847 ↗
29. Soutis C., Beaumont P.W.R.: Multi-scale modelling of composite material systems: the art of predictive damage modelling, Woodhead, (2005b)10.1201/9781439823736 ↗
30. Wang C.H.: Progressive multi-scale modelling of composite laminates, pp. 259–277, A. in Multi-Scale Modelling of Composite Material Systems 1st Edition, Soutis C., Beaumont P W R Eds., Woodhead Publishing, , ISBN: 9781855739369, (2005)
31. Xinxing, T.X.: Wenjie Ge, Yonghong Zha, optimal fiber orientation and topology design for compliant mechanisms with fiber-reinforced composites. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 231(12), 2302–2312 (2017). https://doi.org/10.1177/095440621663178310.1177/0954406216631783 ↗
32. Zhao, J., Xueling, F., Sun, Q.: Stacking sequence optimization of composite laminates for maximum buckling load using permutation search Algorithm. Compos. Struct. 121, 225–236, Elsevier (2015). https://doi.org/10.1016/j.compstruct.2014.10.03110.1016/j.compstruct.2014.10.031 ↗