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11.07.2022 | Original Article

Stochastic optimization of carbon nanotube reinforced concrete for enhanced structural performance

verfasst von: Ioannis Kalogeris, Stefanos Pyrialakos, Odysseas Kokkinos, Vissarion Papadopoulos

Erschienen in: Engineering with Computers | Ausgabe 4/2023

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Abstract

This paper presents a material optimization framework for identifying optimal material typologies to improve structural performance under the presence of uncertainties. Specifically, the focus in this work is on carbon nanotube (CNT)-reinforced concrete with the optimization problem consisting in finding the optimal CNT orientation in the host material so as to minimize the total deformation of structures made up from the composite. Regarding the material modeling, a two-level approach is considered to characterize the mechanical properties of the reinforced concrete. Specifically, cement mortar enhanced with carbon nanotubes is studied at a microscale level where a Drucker-Prager plasticity model is assumed to describe its inelastic behavior. Subsequently, the reinforced mortar along with the concrete’s larger aggregates is studied at a mesoscale level using continuum micromechanics. For the analysis of structural systems comprised of this composite material, an extension of the \(\hbox {FE}^{2}\) technique, termed \(\hbox {FE}^{3}\), is employed. To overcome the immense computational demands associated with \(\hbox {FE}^{3}\), efficient neural network-based surrogates are developed to approximate the nonlinear constitutive law of the composite. In this setting, the stochastic optimization problem equates to finding the optimal orientation of CNTs in the cement mortar, so as to achieve small structural deformations with low variability, under the presence of uncertainty in the loading conditions. To solve this problem, the Covariance Matrix Adaptation Evolution Strategy is chosen herein, and even though this approach requires a massive number of model runs, it is performed at a reasonable computational cost by virtue of the elaborated surrogate modeling scheme.

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Literatur
16.
Zurück zum Zitat Irshidat MR, Al-Saleh MH, Sanad SH (2015) Effect of nanoclay on expansive potential of cement mortar due to alkali-silica reaction. ACI Mater J 112:801–808 Irshidat MR, Al-Saleh MH, Sanad SH (2015) Effect of nanoclay on expansive potential of cement mortar due to alkali-silica reaction. ACI Mater J 112:801–808
22.
Zurück zum Zitat Ebbesen TW, Lezec HJ, Hiura H, Bennett JW, Ghaemi HF, Thio T (1996) Electrical conductivity of individual carbon nanotubes. Nature 382:54–56CrossRef Ebbesen TW, Lezec HJ, Hiura H, Bennett JW, Ghaemi HF, Thio T (1996) Electrical conductivity of individual carbon nanotubes. Nature 382:54–56CrossRef
28.
Zurück zum Zitat Parvin SA, Ahmed NA, Fattahi AM (2020) Numerical prediction of elastic properties for carbon nanotubes reinforced composites using a multi-scale method. Eng Comput pp 1–12 Parvin SA, Ahmed NA, Fattahi AM (2020) Numerical prediction of elastic properties for carbon nanotubes reinforced composites using a multi-scale method. Eng Comput pp 1–12
30.
Zurück zum Zitat Feyel F (2003) A multilevel finite element method (fe2) to describe the response of highly non-linear structures using generalized continua. Comput Methods Appl Mech Eng 192(28):3233–3244CrossRefMATH Feyel F (2003) A multilevel finite element method (fe2) to describe the response of highly non-linear structures using generalized continua. Comput Methods Appl Mech Eng 192(28):3233–3244CrossRefMATH
33.
Zurück zum Zitat Ganzerli S, Pantelides CP, Reaveley LD (2000) Performance-based design using structural optimization. Earthq Eng Struct Dyn 29(11):1677–1690CrossRef Ganzerli S, Pantelides CP, Reaveley LD (2000) Performance-based design using structural optimization. Earthq Eng Struct Dyn 29(11):1677–1690CrossRef
35.
Zurück zum Zitat Degertekin S, Tutar H, Lamberti L (2021) School-based optimization for performance-based optimum seismic design of steel frames. Eng Comput 37(4):3283–3297CrossRef Degertekin S, Tutar H, Lamberti L (2021) School-based optimization for performance-based optimum seismic design of steel frames. Eng Comput 37(4):3283–3297CrossRef
37.
Zurück zum Zitat Hansen N, Kern S (2004) Evaluating the cma evolution strategy on multimodal test functions. In: Yao X, Burke EK, Lozano JA, Smith J, Merelo-Guervós JJ, Bullinaria JA, Rowe JE, Tiňo P, Kabán A, Schwefel HP (eds) Parallel Problem Solving from Nature - PPSN VIII. Springer, Berlin, pp 282–291 Hansen N, Kern S (2004) Evaluating the cma evolution strategy on multimodal test functions. In: Yao X, Burke EK, Lozano JA, Smith J, Merelo-Guervós JJ, Bullinaria JA, Rowe JE, Tiňo P, Kabán A, Schwefel HP (eds) Parallel Problem Solving from Nature - PPSN VIII. Springer, Berlin, pp 282–291
39.
Zurück zum Zitat Ba Anh L, Yvonnet J, He Q (2015) Computational homogenization of nonlinear elastic materials using neural networks: neural networks-based computational homogenization. Int J Numer Methods Eng 104 Ba Anh L, Yvonnet J, He Q (2015) Computational homogenization of nonlinear elastic materials using neural networks: neural networks-based computational homogenization. Int J Numer Methods Eng 104
47.
Zurück zum Zitat Chen WH, Cheng HC, Liu YL (2010) Radial mechanical properties of single-walled carbon nanotubes using modified molecular structure mechanics. Comput Mater Sci 47(4):985–993CrossRef Chen WH, Cheng HC, Liu YL (2010) Radial mechanical properties of single-walled carbon nanotubes using modified molecular structure mechanics. Comput Mater Sci 47(4):985–993CrossRef
48.
Zurück zum Zitat Savvas D, Papadopoulos V, Papadrakakis M (2012) The effect of interfacial shear strength on damping behavior of carbon nanotube reinforced composites. Int J Solids Struct 49(26):3823–3837CrossRef Savvas D, Papadopoulos V, Papadrakakis M (2012) The effect of interfacial shear strength on damping behavior of carbon nanotube reinforced composites. Int J Solids Struct 49(26):3823–3837CrossRef
49.
Zurück zum Zitat Savvas D, Papadopoulos V (2014) Nonlinear multiscale homogenization of carbon nanotube reinforced composites with interfacial slippage. Int J Multiscale Comput Eng 12(4):271–289CrossRef Savvas D, Papadopoulos V (2014) Nonlinear multiscale homogenization of carbon nanotube reinforced composites with interfacial slippage. Int J Multiscale Comput Eng 12(4):271–289CrossRef
50.
Zurück zum Zitat Feenstra PH, De Borst R (1996) A composite plasticity model for concrete. Int J Solids Struct 33(5):707–730CrossRefMATH Feenstra PH, De Borst R (1996) A composite plasticity model for concrete. Int J Solids Struct 33(5):707–730CrossRefMATH
52.
Zurück zum Zitat Miehe C, Koch A (2002) Computational micro-to-macro transitions of discretized microstructures undergoing small strains. Arch Appl Mech 72:300–317CrossRefMATH Miehe C, Koch A (2002) Computational micro-to-macro transitions of discretized microstructures undergoing small strains. Arch Appl Mech 72:300–317CrossRefMATH
53.
Zurück zum Zitat Geers M, Kouznetsova V, Brekelmans W (2010) Multi-scale computational homogenization: trends and challenges. J Comput Appl Math 234(7):2175–2182CrossRefMATH Geers M, Kouznetsova V, Brekelmans W (2010) Multi-scale computational homogenization: trends and challenges. J Comput Appl Math 234(7):2175–2182CrossRefMATH
55.
Zurück zum Zitat Baydin AG, Pearlmutter BA, Radul AA, Siskind JM (2017) Automatic differentiation in machine learning: a survey. J Mach Learn Res 18(1):5595–5637MathSciNetMATH Baydin AG, Pearlmutter BA, Radul AA, Siskind JM (2017) Automatic differentiation in machine learning: a survey. J Mach Learn Res 18(1):5595–5637MathSciNetMATH
57.
Zurück zum Zitat Mckay MD, Beckman RJ, Conover WJ (2000) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 42(1):55–61CrossRefMATH Mckay MD, Beckman RJ, Conover WJ (2000) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 42(1):55–61CrossRefMATH
Metadaten
Titel
Stochastic optimization of carbon nanotube reinforced concrete for enhanced structural performance
verfasst von
Ioannis Kalogeris
Stefanos Pyrialakos
Odysseas Kokkinos
Vissarion Papadopoulos
Publikationsdatum
11.07.2022
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 4/2023
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-022-01693-8