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High dimensional model representation for reliability analyses of complex rock–soil slope stability

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The high-dimensional model representation (HDMR) and its modifications, the fractional HDMR (FHDMR) and hybrid HDMR (HHDMR), are new tools for calculating reliability indexes in stability analyses when several variables with large uncertainties are used to describe rock and soil behaviours. Plain HDMR utilises an inverse reliability analysis for the study of unknown design parameters associated with target reliability index values. This approach uses implicit response functions, named limit state functions, according to the response surface method (RSM). In this study, both the FHDMR and HHDMR are applied to the reliability index calculation of safety factors related to the stability analyses of sliding failure mechanisms in complex formations. These two methods improve the computational efficiency of the RSM in reliability index calculations compared to the HDMR. A case study of Carpathian Flysch rock–soil slopes is presented, and the efficiency of the reliability index calculation is estimated by comparing results with ones from neural network application.
Rocznik
Strony
954--963
Opis fizyczny
Bibliogr. 29 poz., rys., tab., wykr.
Twórcy
autor
  • University ‘‘G. d'Annunzio’’ of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti Scalo (CH), Italy
autor
  • Wrocław University of Science and Technology, Wyb. St. Wyspiańskiego 27, 50-370 Wrocław, Poland
autor
  • Wrocław University of Science and Technology, Wyb. St. Wyspiańskiego 27, 50-370 Wrocław, Poland
Bibliografia
  • [1] J. Bauer, W. Puła, Reliability with respects to settlement limit-states of shallow foundation on linearly-deformable subsoil, Computers and Geotechnics 25 (3–4) (2000) 281–308.
  • [2] D.Q. Li, D. Zheng, Z.J. Cao, X.S. Tang, K.K. Phoon, Response surface methods for slope reliability analysis: review and comparison, Engineering Geology 203 (2016) 3–14. , http://dx. doi.org/10.1016/j.enggeo.2015.09.003.
  • [3] R. Chowdhury, B. Rao, A. Prasad, High Dimensional model representation for piece-wise continuous function approximation, Communications in Numerical Methods in Engineerings 24 (12) (2008) 1587–1609.
  • [4] R. Chowdhury, B. Rao, Hybrid high dimensional model representation for reliability analysis, Computer Methods in Applied Mechanics and Engineering 198 (2009) 753–765.
  • [5] R. Chowdhury, B. Rao, Assessment of high dimensional model representation techniques for reliability analysis, Probabilistic Engineering Mechanics 24 (1) (2009) 100–115.
  • [6] R. Chowdhury, B. Rao, Probabilistic stability assessment of slopes using high dimensional model representation, Computers and Geotechnics 37 (7–8) (2010) 876–884.
  • [7] B. Rao, R. Chowdhury, Enhanced high dimensional model representation for reliability analysis, International Journal for Numerical Methods in Engineering 77 (5) (2009) 719–750.
  • [8] H. Rabitz, Ö. Aliş, General foundations of high dimensional model representations, Journal of Mathematical Chemistry 25 (2–3) (1999) 197–233.
  • [9] L. Genyuan, W. Sheng-Wei, H. Rabitz, High Dimensional Model Representations (HDMR): Concepts and Applications, Department of Chemistry, Princeton University, 2000.
  • [10] I.M. Sobol, Theorems and examples on high dimensional model representation, Reliability Engineering and System Safety 79 (2) (2003) 187–193.
  • [11] D. Mukherjee, B. Rao, A. Prasad, Cut-HDMR based fully equivalent operational model for analysis of unreinforced masonry structure, Sadhana 37 (5) (2012) 609–628.
  • [12] J. Bauer, J. Kozubal, W. Puła, M. Wyjadłowski, Application of HDMR method to reliability assessment of a single pile subjected to lateral load, Studia Geotechnica and Mechanica 3 (2012) 37–52.
  • [13] M.A. Tunga, M. Demiralp, A factorized high dimensional model representation on the nodes of a finite hyperprismatic regular grid, Applied Mathematics and Computation 164 (3) (2005) 865–883.
  • [14] M.A. Tunga, M. Demiralp, Hybrid high dimensional model representation (HHDMR) on the partitioned data, Journal of Computational and Applied Mathematics 185 (1) (2006) 107– 132.
  • [15] S. Romeo, D.S. Kieffer, L. Di Matteo, Reliability of GBInSAR monitoring in Ingelsberg Landslide Area (Bad Hofgastein, Austria), in: T. Scweckendiek, A.F. van Tol, D. Pereboom, M. Th. van Staveren, P.M.C.B.M. Cools (Eds.), Proceedings in Geotechnical Safety and Risk, IOS Press, 2015 785–788.
  • [16] Z. Arbanas, Landslides caused by highway construction near Rijeka, Croatia, in: Proceeding of the 4th International Workshop on Landslides, 23–25 November, Naples, Italy, 2015.
  • [17] Z. Bednarczyk, Landslide geohazard monitoring, early warning and stabilization control methods, Studia Geotechnica et Mechanica 36 (1) (2014) 3–13.
  • [18] S. Dzulynski, M. Ksiazkiewicz, P. Kuenen, Turbidites in flysch of the polish carpathian mountains, Bulletin of the Geological Society of America 70 (8) (1959) 1089–1118.
  • [19] B.D. Collins, R.L. Baum, T. Mrozek, P. Nescieruk, Z. Perski, W. Rączkowski, M. Graniczny, Evaluation of Landslide Monitoring in the Polish Carpathians, Open File Report 2011-1001, 2011.
  • [20] M. Broniatowska, J. Gaszyński, Strength tests of the Carpathian flysch rocks in the region of the constructed water reservoir Świnna Poręba, ZSMG XXIX (English abstract) (2006).
  • [21] J. Atkinson, P. Bransby, The Mechanics of Soils, An Introduction to Critical state Soil Mechanics, McGraw-Hill, 1978.
  • [22] W. Derski, R. Izbicki, I. Kisiel, Z. Mróz, Rock and Soil Mechanics, Elsevier, 1989.
  • [23] D.W. Marquardt, An algorithm for least-squares estimation of nonlinear parameters related databases, Journal of the Society for Industrial and Applied Mathematics 11 (2) (1962) 431–441.
  • [24] O. Ditlevsen, H.O. Madsen, Structural Reliability Methods, John Wiley & Sons, Chichester, 1996.
  • [25] ISO 2394:2015, General principles on reliability of structures. International Standard.
  • [26] L.A. Faravelli, A response surface approach for reliability analysis, Journal of the Engineering Mechanics Division, ASCE 115 (12) (1989) 2763–2781.
  • [27] S. Engelund, R. Rackwitz, Experiences with experimental design schemes for failure surface estimation and reliability, in: Proc. 6th Speciality Conf. Probabilistic Mechanics and Structural and Geotechnical Reliability, Denver, (1992) 252–255.
  • [28] G.P. Box, N.R. Draper, Empirical Model Building and Response Surface, J. Wiley & Sons, New York, 1996.
  • [29] J. Bauer, W. Puła, Neural network supported response surface method with respect to reliability computations in geotechnics, Studia Geotechnica et Mechanica 22 (3–4) (2000) 103–115.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-63207060-afd4-4924-a088-226bd87f690f
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