Applying the spectral stochastic finite element method in multiple-random field RC structures

Abbas Yazdani1
1University of Sistan and Baluchestan

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Der Kiureghian A, Haukaas T, Fujimura K. Structural reliability software at the University of California, Berkeley. Structural Safety, 2006, 28(1–2): 44–67

Der Kiureghian A. Analysis of structural reliability under parameter uncertainties. Probabilistic Engineering Mechanics, 2008, 23(4): 351–358

Depina I, Le T M H, Fenton G, Eiksund G. Reliability analysis with metamodel line sampling. Structural Safety, 2016, 60: 1–15

Sakata S, Okuda K, Ikeda K. Stochastic analysis of laminated composite plate considering stochastic homogenization problem. Frontiers of Structural and Civil Engineering, 2015, 9(2): 141–153

Soltani N, Alembagheri M, Khaneghahi M H. Risk-based probabilistic thermal-stress analysis of concrete arch dams. Frontiers of Structural and Civil Engineering, 2019, 13(5): 1007–1019

Ghavidel A, Rashki M, Ghohani Arab H, Azhdary Moghaddam M. Reliability mesh convergence analysis by introducing expanded control variates. Frontiers of Structural and Civil Engineering, 2020, 14(4): 1012–1023

Rashki M, Ghavidel A, Ghohani Arab H, Mousavi S R. Low-cost finite element method-based reliability analysis using adjusted control variate technique. Structural Safety, 2018, 75: 133–142

Song K, Zhang Y, Zhuang X, Yu X, Song B. Reliability-based design optimization using adaptive surrogate model and importance sampling-based modified SORA method. Engineering with Computers, 2021, 37(2): 1295–1314

Papaioannou I, Straub D. Combination line sampling for structural reliability analysis. Structural Safety, 2021, 88: 102025

Papadopoulos V, Giovanis D G. Stochastic Finite Element Methods: An Introduction. Cham: Springer, 2018: 47–70

Ghanem R G, Spanos P D. Stochastic Finite Elements: A Spectral Approach. New York: Springer, 1991: 101–119

Bae H R, Forster E E. Improved Neumann expansion method for stochastic finite element analysis. Journal of Aircraft, 2017, 54(3): 967–979

Sofi A, Romeo E. A unified response surface framework for the interval and stochastic finite element analysis of structures with uncertain parameters. Probabilistic Engineering Mechanics, 2018, 54: 25–36

Wu F, Yao L Y, Hu M, He Z C. A stochastic perturbation edge-based smoothed finite element method for the analysis of uncertain structural-acoustics problems with random variables. Engineering Analysis with Boundary Elements, 2017, 80: 116–126

Papadopoulos V, Kalogeris I, Giovanis D G. A spectral stochastic formulation for nonlinear framed structures. Probabilistic Engineering Mechanics, 2019, 55: 90–101

Chen N Z, Soares C G. Spectral stochastic finite element analysis for laminated composite plates. Computer Methods in Applied Mechanics and Engineering, 2008, 197(51–52): 4830–4839

Stefanou G, Papadrakakis M. Stochastic finite element analysis of shells with combined random material and geometric properties. Computer Methods in Applied Mechanics and Engineering, 2004, 193(1–2): 139–160

Kandler G, Füssl J, Eberhardsteiner J. Stochastic finite element approaches for wood-based products: theoretical framework and review of methods. Wood Science and Technology, 2015, 49(5): 1055–1097

Li K, Wu D, Gao W. Spectral stochastic isogeometric analysis for static response of FGM plate with material uncertainty. Thin-walled Structures, 2018, 132: 504–521

Zhou X Y, Gosling P D, Ullah Z, Kaczmarczyk L, Pearce C J. Stochastic multi-scale finite element based reliability analysis for laminated composite structures. Applied Mathematical Modelling, 2017, 45: 457–473

Sudret B, Der Kiureghian A. Stochastic Finite Element Methods and Reliability: A State-of-the-Art Report. Berkeley, CA: University of California, 2000

Yazdani A, Arab H G, Rashki M. Simplified spectral stochastic finite element formulations for uncertainty quantification of engineering structures. Structures, 2020, 28: 1924–1945

Schietzold F N, Schmidt A, Dannert M M, Fau A, Fleury R M, Graf W, Kaliske M, Könke C, Lahmer T, Nackenhorst U. Development of fuzzy probability based random fields for the numerical structural design. GAMM-Mitteilungen, 2019, 42(1): e201900004

Schmidt A, Henning C, Herbrandt S, Könke C, Ickstadt K, Ricken T, Lahmer T. Numerical studies of earth structure assessment via the theory of porous media using fuzzy probability based random field material descriptions. GAMM-Mitteilungen, 2019, 42(1): e201900007

Zakian P, Khaji N. A stochastic spectral finite element method for wave propagation analyses with medium uncertainties. Applied Mathematical Modelling, 2018, 63: 84–108

Wiener N. The homogeneous chaos. American Journal of Mathematics, 1938, 60(4): 897–936

Chandrupatla T R, Belegundu A D. Introduction to Finite Elements in Engineering. Upper Saddle River, NJ: Prentice Hall, 2002

Nariman N A, Hamdia K, Ramadan A M, Sadaghian H. Optimum design of flexural strength and stiffness for reinforced concrete beams using machine learning. Applied Sciences, 2021, 11(18): 8762

Timoshenko S P, Woinowsky-Krieger S. Theory of Plates and Shells. New York: McGraw-hill, 1959

Vu-Bac N, Duong T X, Lahmer T, Zhuang X, Sauer R A, Park H S, Rabczuk T. A NURBS-based inverse analysis for reconstruction of nonlinear deformations of thin shell structures. Computer Methods in Applied Mechanics and Engineering, 2018, 331: 427–455

Vu-Bac N, Duong T X, Lahmer T, Areias P, Sauer R A, Park H S, Rabczuk T. A NURBS-based inverse analysis of thermal expansion induced morphing of thin shells. Computer Methods in Applied Mechanics and Engineering, 2019, 350: 480–510

ACI 318-08. Building Code Requirements for Structural Concrete and Commentary. Farmington Hills: American Concrete Institute, 2008

Vu-Bac N, Silani M, Lahmer T, Zhuang X, Rabczuk T. A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites. Computational Materials Science, 2015, 96: 520–535

Vu-Bac N, Lahmer T, Zhuang X, Nguyen-Thoi T, Rabczuk T. A software framework for probabilistic sensitivity analysis for computationally expensive models. Advances in Engineering Software, 2016, 100: 19–31

Vu-Bac N, Zhuang X, Rabczuk T. Uncertainty quantification for mechanical properties of polyethylene based on fully atomistic model. Materials, 2019, 12(21): 3613

Liu B, Vu-Bac N, Zhuang X, Rabczuk T. Stochastic multiscale modeling of heat conductivity of polymeric clay nanocomposites. Mechanics of Materials, 2020, 142: 103280

Liu B, Vu-Bac N, Rabczuk T. A stochastic multiscale method for the prediction of the thermal conductivity of polymer nanocomposites through hybrid machine learning algorithms. Composite Structures, 2021, 273: 114269

Frangopol D M. Probability concepts in engineering: Emphasis on applications to civil and environmental engineering. Structure and Infrastructure Engineering, 2008, 4(5): 413–414