TY - JOUR
T1 - Structural topology optimization under constraints on instantaneous failure probability
AU - Chun, Junho
AU - Song, Junho
AU - Paulino, Glaucio H.
N1 - Funding Information:
The authors gratefully acknowledge funding provided by the National Science Foundation (NSF) through project CMMI 1234243. We also acknowledge support from the Raymond Allen Jones Chair at the Georgia Institute of Technology. The second author also acknowledges the support from the Integrated Research Institute of Construction and Environmental Engineering at Seoul National University, and the National Research Foundation of Korea (NRF) Grant (No. 2015R1A5A7037372), funded by the Korean Government (MSIP). Any opinion, finding, conclusions or recommendations expressed here are those of the authors and do not necessarily reflect the views of the sponsors.
Publisher Copyright:
© 2015, Springer-Verlag Berlin Heidelberg.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - Accurate prediction of stochastic responses of a structure caused by natural hazards or operations of non-structural components is crucial to achieve an effective design. In this regard, it is of great significance to incorporate the impact of uncertainty into topology optimization of structures under constraints on their stochastic responses. Despite recent technological advances, the theoretical framework remains inadequate to overcome computational challenges of incorporating stochastic responses to topology optimization. Thus, this paper presents a theoretical framework that integrates random vibration theories with topology optimization using a discrete representation of stochastic excitations. This paper also discusses the development of parameter sensitivity of dynamic responses in order to enable the use of efficient gradient-based optimization algorithms. The proposed topology optimization framework and sensitivity method enable efficient topology optimization of structures under stochastic excitations, which is successfully demonstrated by numerical examples of structures under stochastic ground motion excitations.
AB - Accurate prediction of stochastic responses of a structure caused by natural hazards or operations of non-structural components is crucial to achieve an effective design. In this regard, it is of great significance to incorporate the impact of uncertainty into topology optimization of structures under constraints on their stochastic responses. Despite recent technological advances, the theoretical framework remains inadequate to overcome computational challenges of incorporating stochastic responses to topology optimization. Thus, this paper presents a theoretical framework that integrates random vibration theories with topology optimization using a discrete representation of stochastic excitations. This paper also discusses the development of parameter sensitivity of dynamic responses in order to enable the use of efficient gradient-based optimization algorithms. The proposed topology optimization framework and sensitivity method enable efficient topology optimization of structures under stochastic excitations, which is successfully demonstrated by numerical examples of structures under stochastic ground motion excitations.
KW - Discrete representation
KW - Parameter sensitivity
KW - Reliability based design optimization
KW - Stochastic excitation
KW - Topology optimization
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U2 - 10.1007/s00158-015-1296-y
DO - 10.1007/s00158-015-1296-y
M3 - Article
AN - SCOPUS:84947729614
SN - 1615-147X
VL - 53
SP - 773
EP - 799
JO - Structural Optimization
JF - Structural Optimization
IS - 4
ER -