2006
DOI: 10.1007/s00158-005-0575-4
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A review of optimization of structures subjected to transient loads

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Cited by 183 publications
(70 citation statements)
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“…Since special treatments are required, the technology is rarely applied to large-scale structures. (8) Instead, static response optimization is carried out. Therefore, static loads, which approximate dynamic loads, have been used in structural optimization of the joined-wing.…”
Section: Gallman Andmentioning
confidence: 99%
See 1 more Smart Citation
“…Since special treatments are required, the technology is rarely applied to large-scale structures. (8) Instead, static response optimization is carried out. Therefore, static loads, which approximate dynamic loads, have been used in structural optimization of the joined-wing.…”
Section: Gallman Andmentioning
confidence: 99%
“…The loads are utilized as multiple loading conditions in structural optimization. (8)(9)(10)(11)(12)(13)(14)(15)(16) Size optimization is performed to reduce the structural mass while design conditions are satisfied. Existing static loading conditions are utilized.…”
Section: Gallman Andmentioning
confidence: 99%
“…One has to remember that contrary to static optimization, dealing with optimal design of structures subjected to dynamic loading, one needs to either solve transient response of the structures under consideration or transform dynamic loading into equivalent quasi-static ones [29]. Fortunately, it turns out that the appropriate formulation of optimal design of dynamically loaded structures i.e.…”
Section: Introductionmentioning
confidence: 99%
“…However, many algorithms have been developed to calculate dynamic response first derivatives with respect to design variables (also called sensitivity analysis [5][6][7][8][9][10][11][12]). Today, the gradient-based algorithms are the mainstream pattern [13] to solve the optimization problem of structures subjected to transient loads. Much research [14][15][16][17] has been done to solve the structural dynamic response optimization problem with the gradient-based algorithms.…”
Section: Introductionmentioning
confidence: 99%