System Reliability‐Based Topology Optimization of Structures under Stochastic Excitations SKIDMORE, OWINGS & MERRILL LLP Junho Chun, Junho Song, Glaucio H. Paulino Department of Civil and Environmental Engineering, University of Illinois at Urbana‐Champaign, U.S.A Research Objective • Find optimal bracing systems under stochastic excitation, particularly induced by earthquake ground motions. • Develop topology optimization framework Integrated with random vibration theory and structural reliability analysis. (courtesy of SOM) • Evaluate the system‐level failure probability accurately considering statistical dependence between failure modes, locations and time points. Discrete Representation Method Sequential Compounding Method (SCM) The discrete representation method discretizes a continuous stochastic process with a finite number of standard normal random variables. SCM can compute the probability of a large‐system reliability problem efficiently and accurately. vj Discretization of Random Process f (t ) (t ) vi si (t ) (t ) s(t ) v T i 1 αˆ (t0 ) v* (u0 , t0 ) Stochastic Response t n MPP n u (t ) vi si ( )hs (t τ)dτ vi ai (t ) a(t )T v 0 i 1 β(u0 ,t0 ) i 1 Instantaneous Failure Probability u0 a(t0 )T v 0 P E f P u0 a t0 v 0 P g (u ) 0 Geometric representation of instantaneous failure probability T | u (t ) |) P u (ti ) u0 i 1 n 10 =3 -2 EL : ‐ m 0 -3 100 200 300 400 ‐2 1 2 3 4 5 6 Time (seconds) 7 8 9 10 800 3 Normalized computational time 10 B 1 5 10 0.9 3 0.8 4 0.7 0.6 5 3 4 0.5 5 A 0.9 B 0.7 0.6 5 A B 0.5 5 0 10 400 600 800 1000 1200 Number of Elements 1400 1600 14 1 E C E5 1800 C 0 ‐0.2 10 0.9 C 0.8 0.7 5 ‐0.2 5 0.6 10 ‐0.4 8 ‐0.4 8 ‐0.6 6 ‐0.8 2 4 6 8 Adjoint method 0.5 5 D Sequential compounding procedure ‐1.2 10 ED ‐1 2 ‐1.2 C ‐0.8 4 ‐1 ‐0.6 2 4 6 8 10 Finite difference method h = 20 Convergence History 3 h = 15 10 8 6 4 2 0 20 40 60 80 100 120 140 20 40 60 80 No.iteration 100 120 140 0.2 Psys 0.1 0 0 h = 10 Dynamic Performance Ground acceleration 1000 LEVEL 02 EL : h m f(t) (m/s2) 0 ‐1000 0 h m 0.5 1 Initial system 1.5 2 2.5 3 Optimized system 3.5 4 2 0 0 10 20 30 (rad /s) 40 Kanai‐Tajimi PSD 50 60 GROUND EL : 0 m Design domain and loading configuration 0.02 1/L1 0.02 1/L1 Kanai-Tajimi PSD, () 0.5 5 1 2 10 g =0.5 6 4 0.8 5m 8 4 A 70 g =0.4 3 1 A 3 d 10 2 A 5 min Volume(ρ (d )) g =0.3 1 A 1000 12 The purpose of topology optimization is to identify the optimal distribution of materials in a given design domain subjected to tractions and boundary conditions while satisfying given design constraints.. 12 900 0 Lateral Load Resisting System Design t s.t P u (ti ) u0 P ( E sys : β1 ,...,β 70 ) Psys (=2.3%) i 1 0 ρ (d, x ) 1 x , ti [0, 3.5] u(t , ρ ) C(ρ )u (t , ρ ) K (ρ )u(t , ρ ) Mlf (t ) with M (ρ ) 5 E A E B E5 EL : 0 m Stochastic Topology Optimization Framework 700 FDM AJM 14 4 4 10 10 200 EL : ‐ m 0.7 4 EA E3 E4 E5 ‐1 6 GROUND 600 5 2 ‐4 0 500 10 LEVEL i 0.8 3 5 Exact Proposed method 12 LEVEL j 0.9 2 0.6 LEVEL k EL : ‐ m 1 2 3 Volume (m ) u0 =2 4 2 u(t) -1 Sensitivity Analysis The probability that a stochastic response exceeds a given threshold at least once for a given duration. It is often used to describe the reliability of a system subjected to stochastic excitations. 4 10 Performance of SCM The First Passage Probability P ( E sys ) P (u0 max 0t tn 1 # of components, N g (u ) u0 / a t0 a t0 / a t0 v β u0 , t0 αˆ (t0 ) v T E1 E2 E3 E4 E5 Correlation coefficient matrix 1 10 vi u0 u(t0 ) 0 Safe domain 0 =1 u0 u(t0 ) 0 Failure domain Probability of Cut Set System P(Esys) n 10 0 ‐0.02 Φ0=700 Φ0=30 Φ0=4 0 0 ‐0.02 1 2 Time (seconds) 3 0 1 2 Time (seconds) 3 Conclusion Acknowledgements • The sequential compounding method enables for an efficient and accurate computation of the failure probability of a large‐size system reliability problem and its parameter sensitivities. • The developed topology optimization framework under constraints on the first passage probability provides ways to find optimal bracing systems that can resist future realization of stochastic processes with a desired level of reliability. The authors gratefully acknowledge funding provided by the National Science Foundation (NSF) through project CMMI 1234243. We also acknowledge support from the Donald B. and Elizabeth M. Willett endowment at the University of Illinois at Urbana‐Champaign. Reference • J. Chun, J. Song and G. H. Paulino, Topology optimization of structures under stochastic excitations. Computer Methods in Applied Mechanics and Engineering, 2013. Submitted, under review. • W.‐H. Kang and J. Song, Evaluation of multivariate normal integrals for general systems by sequential compounding, Structural Safety, 32(1), 35‐41, 2010. • J. Song and A. Der Kiureghian, Joint first‐passage probability and reliability of systems under stochastic excitation, ASCE Journal of Engineering Mechanics, 132(1), 65‐77, 2006. • A. Der Kiureghian, The geometry of random vibrations and solutions by FORM and SORM. Probabilistic Engineering Mechanics, 15(1), 81–90, 2000.
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