On the least squares stochastic finite element analysis of the steel skeletal towers exposed to fire

• Autorzy: Kamiński M. M. , Strąkowski M. T.
• Języki publikacji: EN

Abstrakty

EN

The main issue in this paper is an application of the generalized stochastic perturbation technique to thermal stresses and deformations analysis for the spatial steel tower structure exposed to a fire. This approach is based on the given order Taylor expansion of all random parameters and state functions around their mean values as well as on the Least Squares Technique to determine the analytical functions in-between design parameters and structural responses. A distribution of the temperature in the model is considered for a simplicity as the set of constant values for all structural members. The temperature equivalent to the fire exposure in the analyzed structure is taken as the input Gaussian random variable, where basic material parameters are considered as temperature-dependent and this is the basis to calculate up to the fourth probabilistic moments and characteristics of the stresses and deformations. This study is an example of a hybrid usage of the FEM engineering system ROBOT and the computer algebra system MAPLE in stochastic analysis, where thermal stresses and strains may be straightforwardly used in fire reliability analysis of the civil engineering structures with both temperature-independent and dependent material characteristics.

Słowa kluczowe

EN

stochastic perturbation technique; fire simulation; stochastic finite element method; reliability analysis

PL

symulacja pożaru; metoda elementów skończonych; analiza niezawodności

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2013
• Tom: Vol. 13, no. 2
• Strony: 242--253
• Opis fizyczny: Bibliogr. 14 poz., rys., wykr.

Twórcy

autor

Kamiński M. M.

• Faculty of Civil Engineering, Architecture and Environmental Engineering, Technical University of Łódź, Poland

autor

Strąkowski M. T.

• Faculty of Civil Engineering, Architecture and Environmental Engineering, Technical University of Łódź, Poland

Bibliografia

• [1] D.L. Allaix, V.I. Carbone, An improvement of the response surface method, Structural Safety 33 (2) (2011) 165–172.
• [2] I. Babuska, R. Tempone, G.E. Zouraris, Solving elliptic boundary value problems with uncertain coefficients by the finite element method: the stochastic formulation, Computer Methods in Applied Mechanics and Engineering 12–16 (194) (2005) 1251–1294.
• [3] X. Chen, Y.K. Tung, Investigation of polynomial normal transform, Structural Safety 25 (4) (2003) 423–445.
• [4] M.M.S. Dwaikat, Experimental behavior of steel beam columns subjected to fire-induced thermal gradients, Journal of Constructional Steel Research 67 (1) (2011) 30–38.
• [5] H.P. Gavin, S.C. Yau, High-order limit state functions in the response surface method for structural reliability analysis, Structural Safety 30 (2) (2008) 162–179.
• [6] R.G. Ghanem, P.D. Spanos, Stochastic Finite Elements: A Spectral Approach, Springer-Verlag, New York, 1991.
• [7] M.A. Hadianfard, R. Razani, Effects of semi-rigid behavior of connections in the reliability of steel frames, Structural Safety 25 (2) (2011) 123–138.
• [8] M. Kamiński, P. Świta, Generalized stochastic finite element method in elastic stability problems, Computers & Structures 11–12 (89) (2011) 1241–1252.
• [9] A. Keese, H.G. Matthies, Hierarchical parallelisation for the solution of stochastic finite element equations, Computers & Structures 83 (14) (2005) 1033–1047.
• [10] M. Kleiber, T.D. Hien, The Stochastic Finite Element Method, Wiley, Chichester, 1992.
• [11] G. Stefanou, M. Papadrakakis, Stochastic finite element analysis of shells with combined random material and geometric properties, Computer Methods in Applied Mechanics and Engineering 1–2 (193) (2004) 139–160.
• [12] N. Tuśnio, Numerical Analysis of the Steel Structures strength Under Fire, Ph.D. Thesis, IFTR PAS, Warsaw, 2010.
• [13] E. Vanmarcke, Random Fields. Analysis and Synthesis, MIT Press, Boston, 1983.
• [14] J. Wolberg, Data Analysis Using the Method of Least Squares: Extracting the Most Information from Experiments, Springer, Berlin-Heidelberg, 2005.