Modified linear estimation method for generating multi-dimensional multi-variate Gaussian field in modelling material properties |
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Affiliation: | 1. Department of Civil & Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore;2. Institute for Risk & Uncertainty, University of Liverpool, Brodie Tower, Brownlow Street, Liverpool L69 3GQ, UK;1. Ruhr-Universität Bochum, Faculty of Civil and Environmental Engineering, Chair of Computing in Engineering, 150, Universitätsstr., 44780 Bochum, Germany;2. Ruhr-Universität Bochum, Faculty of Civil and Environmental Engineering, Chair for Foundation Engineering, Soil and Rock Mechanics, 150, Universitätsstr., 44780 Bochum, Germany;1. Cyprus University of Technology, Limassol, Cyprus;2. Colorado School of Mines, Golden, CO, USA;3. University of Newcastle, NSW, Australia;2. School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei, China;3. Antea Group, 92160 Antony, France;1. Department of Civil and Environmental Engineering, National University of Singapore, 1 Engineering Dr. 2, Singapore 117576, Singapore;2. College of Civil Engineering and Architecture, Hainan University, Haikou, Hainan 570228, China;3. Golder Associates (HK) Limited, Hong Kong;1. School of Civil Engineering & Mechanics, Huazhong University of Science & Technology, 1037 Luoyu Rd, Wuhan 430074, PR China;2. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 299 Ba Yi Road, Wuhan 430072, PR China;3. Department of Civil & Environmental Engineering, National University of Singapore, 1 Engineering Drive 2, Singapore 117576, Singapore;4. MOE Key Laboratory of Geotechnical and Underground Engineering, Tongji University, 1239 Siping Rd, Shanghai 200092, PR China;5. Department of Civil & Environmental Engineering, University of Maryland, 4298 Campus Dr., College Park, MD 20742, United States |
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Abstract: | Although a number of methods have been developed to generate random fields, it remains a challenge to efficiently generate a large, multi-dimensional, multi-variate property field. For such problems, the widely used spectral representation method tends to require relatively longer computing time. In this paper, a modified linear estimation method is proposed, which involves mapping the linearly estimated field through a series of randomized translations and rotations from one realization to the next. These randomized translations and rotations enable the simulated property field to be stationary. The autocorrelation function of the simulated fields can be approximately described by a squared exponential function. The algorithms of the proposed method in both the rectangular and cylindrical polar coordinate systems are demonstrated and the results validated by Monte-Carlo simulations. Comparisons between the proposed method and spectral representation method show that the results from both methods are in good agreement, as long as the cut-off wave numbers of the spectral representation method are sufficiently large. However, the proposed method requires much less computational time than the spectral representation method. This makes it potentially useful for generating large multi-dimensional fields in random finite element analysis. Applications of the proposed method are exemplified in both rectangular and cylindrical polar coordinate systems. |
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Keywords: | Random field Material property Autocorrelation function Random finite element analysis |
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