2012
DOI: 10.1007/s00707-011-0610-z
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Optimisation of material composition of functionally graded materials based on multiscale thermoelastic analysis

Abstract: This paper presents a method for optimisation of the material composition of functionally graded materials (FGMs) for thermal stress relaxation. This method consists of a multiscale thermoelastic analysis and a genetic algorithm. In the presented method, location-dependent unit cells representing the microstructures of two-phase FGMs are created using morphology description functions, and the homogenised material properties and microscale thermal stresses are computed using the asymptotic expansion homogenisat… Show more

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Cited by 24 publications
(5 citation statements)
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“…The results of using optimized FGM were compared with the use of standard Co-Cr alloy in a femoral component to demonstrate relative performance. Optimization of material composition of FGMs based on multiscale analysis method that can efficiently predict the microscopic stress state (namely, the asymptotic expansion homogenization (AEH) method) was conducted by Chiba and Sugano [82]. They optimized the material composition of an infinite FG plate made of Ti and ZrO 2 in only one direction using a genetic algorithm.…”
Section: -2015mentioning
confidence: 99%
“…The results of using optimized FGM were compared with the use of standard Co-Cr alloy in a femoral component to demonstrate relative performance. Optimization of material composition of FGMs based on multiscale analysis method that can efficiently predict the microscopic stress state (namely, the asymptotic expansion homogenization (AEH) method) was conducted by Chiba and Sugano [82]. They optimized the material composition of an infinite FG plate made of Ti and ZrO 2 in only one direction using a genetic algorithm.…”
Section: -2015mentioning
confidence: 99%
“…The genetic algorithm starts a search from a series of points, and for performing the search procedure, it does not require to the Jacobian of functions [21]. Many researchers for optimizing their work have used the genetic algorithm [22][23][24][25]. The terminology used for genetic algorithm is given in Table 1.…”
Section: Application Of Ga For Optimal Location Of Piezoelectric Devicesmentioning
confidence: 99%
“…Obok mechanizmu dziedziczenia cech i umierania słabszych osobników istnieje mechanizm mutacji. Algorytmy genetyczne to jedna z popularniejszych obecnie metod optymalizacji [2,10]. Charakterystykę optymalizacyjnego algorytmu genetycznego przedstawiono w tabeli 1.…”
Section: Optymalizacja Lokalizacji I Orientacji Elementówunclassified