Combined approximations – a general reanalysis approach for structural optimization

By Uri Kirsch. 2000

119 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/af003707c8ecdd187a19243d7e14c6480ab5949f

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In Civil and Structural Engineering

In Statistics and Probability

Citations in the corpus

Efficient generation of large-scale pareto-optimal topologies (2013, methodology): “In [13], the authors exploit approximate reanalysis, based on the combined approximation (CA) method [14] as an acceleration technique.”
An adaptive reanalysis method for genetic algorithm with application to fast truss optimization (2010, methodology): “The reduced basis method considered in this article is based on the Kirsch’s CA method [18].”
Structural reanalysis for topological modifications – a unified approach (2001, methodology): “The method has been used in previous studies for various problems and different types of design variables (Kirsch 1993b, 1999, 2000; Kirsch and Liu 1995, 1997).”
Reanalysis and sensitivity reanalysis by combined approximations (2009, methodology): “have been reviewed in previous studies ( Kirsch 2000, 2002, 2003a, b), and detailed discussions on particular aspects of various problems are presented in a recent text (Kirsch 2008).”
A unified reanalysis approach for structural analysis, design, and optimization (2003, methodology): “The main advantages of the CA approach, which have been studied in terms of several criteria, can be summarized as follows ( Kirsch 2000; 2002a; 2003a ):”
Sensitivity reanalysis of static displacement using Taylor series expansion and combined approximate method (2015, methodology): “…for Automobile Parts, (Chongqing University of Technology), Ministry of Education, Chongqing, People’s Republic of China nonlinear reanalysis (Kirsch 2000; Kirsch and Bogomolni 2007), vibration reanalysis (Chen and Yang 2000), dynamic reanalysis (Kirsch et al. 2006), sensitivity reanalysis…”
Fast structural optimization with frequency constraints by genetic algorithm using adaptive eigenvalue reanalysis methods (2011, background): “So this approach is also effective for the large changes of structural equation (Chen and Yang 2000; Kirsch 2000; Kirsch et al. 2006).”