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On spectral representation method and Karhunen–Loève expansion in modelling construction material properties

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Randomness in construction material properties (e.g. Young's modulus) can be simulated by stationary random processes or random fields. To check the stationarity of commonly used techniques, three random process generation methods were considered: Xn(t), Yn(t), and Zn(t). Methods Xn(t) and Yn(t) are based on a truncation of the spectral representation method with the first n terms. Xn(t) has random amplitudes while Yn(t) has random harmonics phases. Method Zn(t) is based on the Karhunen–Loève expansion with the first n terms as well. The effects of the truncation technique on the mean-square error, covariance function, and scale of fluctuation were examined in this study; these three methods were shown to have biased estimations of variance with finite n. Modified forms for those methods were proposed to ensure the truncated processes were still zero-mean, unit-variance, and had a controllable scale of fluctuation; in particular, the modified form of Karhunen–Loève expansion was shown to be stationary in variance. As a result, the modified forms for those three methods are advantageous in simulating statistically homogenous material properties. The effectiveness of the modified forms was demonstrated by a numerical example.
Rocznik
Strony
768--783
Opis fizyczny
Bibliogr. 39 poz., rys., tab., wykr.
Twórcy
autor
  • School of Civil Engineering & Mechanics, Huazhong University of Science & Technology, 1037 Luoyu Rd, Wuhan 430074, PR China
autor
  • School of Civil Engineering & Mechanics, Huazhong University of Science & Technology, 1037 Luoyu Rd, Wuhan 430074, PR China
autor
  • State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 299 Ba Yi Road, Wuhan 430072, PR China
  • Department of Civil & Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore
autor
  • dMOE Key Laboratory of Geotechnical and Underground Engineering, Tongji University, 1239 Siping Rd, Shanghai 200092, PR China
  • Department of Civil & Environmental Engineering, University of Maryland, 4298 Campus Dr., College Park, MD 20742, United States
Bibliografia
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  • [8] Y. Liu, M.D. Shields, A direct simulation method and lower-bound estimation for a class of gamma random fields with applications in modelling material properties, Probab. Eng. Mech. 47 (2017) 16–25.
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  • [33] H.W. Huang, L. Xiao, D.M. Zhang, J. Zhang, Influence of spatial variability of soil Young's modulus on tunnel convergence in soft soils, Eng. Geol. 228 (2017) 357–370.
  • [34] Y. Liu, S.T. Quek, F.H. Lee, Translation random field with marginal beta distribution in modelling material properties, Struct. Saf. 61 (2016) 57–66.
  • [35] A.T.C. Goh, Y.M. Zhang, R.H. Zhang, W.G. Zhang, Y. Xiao, Evaluating stability of underground entry-type excavations using multivariate adaptive regression splines and logistic regression, Tunn. Undergr. Space Technol. 70 (2017) 148–154.
  • [36] Y. Liu, Y. Jiang, H. Xiao, F.H. Lee, Determination of representative strength of deep cement–mixed clay from core strength data, Géotechnique 67 (4) (2017) 350–364.
  • [37] W.G. Zhang, A.T.C. Goh, Multivariate adaptive regression splines and neural network models for prediction of pile drivability, Geosci. Front. 7 (2016) 45–52.
  • [38] A. Der-Kiureghian, J.B. Ke, The stochastic finite element method in structural reliability, Probab. Eng. Mech. 3 (1988) 83–91.
  • [39] JCSS – Joint Committee of Structural Safety, Probabilistic Model Code – Part 1: Basis of Design (JCSS-OSTL/DIA/VROU- 10-11-2000), 2001.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-476af82c-c863-4e0c-868d-a2db07c52ea2
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