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Computer analysis of dynamic reliability of some concrete beam structure exhibiting random damping

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An efficiency of the generalized tenth order stochastic perturbation technique in determination of the basic probabilistic characteristics of up to the fourth order of dynamic response of Euler-Bernoulli beams with Gaussian uncertain damping is verified in this work. This is done on civil engineering application of a two-bay reinforced concrete beam using the Stochastic Finite Element Method implementation and its contrast with traditional Monte-Carlo simulation based Finite Element Method study and also with the semi-analytical probabilistic approach. The special purpose numerical implementation of the entire Stochastic perturbation-based Finite Element Method has been entirely programmed in computer algebra system MAPLE 2019 using Runge-Kutta-Fehlberg method. Further usage of the proposed technique to analyze stochastic reliability of the given structure subjected to dynamic oscillatory excitation is also included and discussed here because of a complete lack of the additional detailed demands in the current European designing codes.
Rocznik
Strony
45--64
Opis fizyczny
Bibliogr. 23 poz., rys., tab., wykr.
Twórcy
autor
  • Department of Structural Mechanics, Łódź University of Technology Al. Politechniki 6, 90-924 Łódź, POLAND
autor
  • Department of Structural Mechanics, Łódź University of Technology Al. Politechniki 6, 90-924 Łódź, POLAND
Bibliografia
  • [1] Mayers A. (2009): Vibration acceptance criteria.– Australian Bulk Handling Review: issue March/April.
  • [2] DIN 4150 1-3:2001: Vibrations in buildings.
  • [3] AS 2670.1-201 Australian Standards: Evaluation of human exposure to whole-body vibration, Part 1: General requirements.
  • [4] Cornell C.A. (1968): Engineering seismic risk analysis.– Bulletin of Seismological Society of America, vol.58, No.5, pp.1583-1606.
  • [5] Madsen H.O., Krenk S. and Lind N.C. (1986): Methods of Structural Safety.– Prentice Hall, Englewood Cliffs.
  • [6] Melchers R.E. and Beck A.T. (2018): Structural Reliability Analysis and Prediction.– John Wiley & Sons, Hoboken, NJ, p.497.
  • [7] Valdebenito M.A., Jensen H.A., Schuëller G.I. and Caro F.E. (2012): Reliability sensitivity estimation of linear systems under stochastic excitation.– Computers and Structures, vol.92-93, pp.257-268.
  • [8] Soize C. (2013): Stochastic modelling of uncertainties in computational structural dynamics – Recent theoretical advances.– J. of Sound and Vibration, vol.332, No.10, pp.2379-2395.
  • [9] Roberts J.B. and Spanos P.D. (1990): Random vibration and statistical linearization.– Chichester, Wiley.
  • [10] Muscolino G., Ricciardi G. and Vasta M. (1997): Stationary and non-stationary probability density function of non-linear oscillators.– Int. J. of Non-Linear Mechanics, vol.32, No.6, pp.1051-1064.
  • [11] Roberts J.B. and Spanos P.D. (1986): Stochastic averaging: an approximation method of solving random vibration problems.– Int. J. Non-Linear Mechanics, vol.21, No.2, pp.111-134.
  • [12] Sobczyk K, Wędrychowicz S. and Spencer B.F. (1996): Dynamics of structural systems with spatial randomness.–Int. J. of Solids and Structures, vol.33, No.11, pp.1651-1669.
  • [13] Goller B., Pradlwarter H.J. and Schuëller G.I. (2013): Reliability assessment in structural dynamics.– Journal of Sound & Vibration, vol.332, pp.2488-2499.
  • [14] Kamiński M. (2013): The Stochastic Perturbation Method for Computational Mechanics.– Chichester, Wiley.
  • [15] Kamiński M. and Corigliano A. (2015): Numerical solution of the Duffing equation with random coefficients.– Meccanica, vol.50, pp.1841-1853.
  • [16] Hughes T.J.R. (2000): The Finite Element Method – Linear Static and Dynamic Finite Element Analysis.– New York, Dover Publications, Inc.
  • [17] Hutton D.V. (2004): Fundamentals of Finite Element Analysis.– McGraw-Hill.
  • [18] Han S.H., Benaroya H. and Wei T. (1999): Dynamics of transversely vibrating beams using four engineering theories.– Journal of Sound and Vibration, vol.225, No.5, pp.935-988.
  • [19] Liao S., Zhang Y. and Chen D. (2019) Runge-Kutta Finite Element Method based on the characteristic for the incompressible Navier-Stokes equations.– Advanced Applied Mathematics & Mechanics, vol.11, pp.1415-1435.
  • [20] Botasso C.L. (1997): A new look at finite elements in time: a variational interpretation of Runge-Kutta methods.–Applied Numerical Mathematics vol.25, pp.355-368.
  • [21] Eurocode 0 (2005): Basis of structural design. EN 1990:2002/A1.– European Committee for Standardization, Brussels.
  • [22] Pradlwarter H.J. and Schuëller GI. (2010): Uncertain linear systems in dynamics: Efficient stochastic reliability assessment.– Computers and Structures, vol.88, pp.74-86.
  • [23] Kamiński M. (2015): On the dual iterative stochastic perturbation-based finite element method in solid mechanics with Gaussian uncertainties.– International Journal for Numerical Methods in Engineering, vol.104, No.11, pp.1038-1060.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-08e340f4-9d54-4386-9fbb-3cc4d1b79bf5
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