Journal ArticleDOI
Parameter identification of an elasto-plastic behaviour using artificial neural networks–genetic algorithm method
TLDR
In this paper, a hybrid identification method based on finite elements, neural network computations and GA of an elasto-plastic behaviour model was proposed to identify the Karafillis and Boyce criterion and the Voce parameters model.About:
This article is published in Materials & Design.The article was published on 2011-01-01. It has received 59 citations till now. The article focuses on the topics: Finite element method.read more
Citations
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The Use of genetic algorithm and neural network to predict rate-dependent tensile flow behaviour of AA5182-O sheets
TL;DR: In this article, the tensile flow behavior of AA5182-O sheet was experimentally obtained in different material directions (RD, DD, and TD) at strain rates ranging from 0.001 to 1000 s − 1 and predicted by means of both phenomenological models and neural networks (NNs).
Journal ArticleDOI
Experimental characterization and inverse constitutive parameters identification of tubular materials for tube hydroforming process
TL;DR: In this article, a self-designed bulge forming machine is manufactured to perform tubular bulge tests and tensile tests are carried out on specimens cut from the tube to measure the Lankford anisotropy coefficients.
Journal ArticleDOI
Neural networks optimization through genetic algorithm searches: A review
Haruna Chiroma,Ahmad Shukri Mohd Noor,Sameem Abdulkareem,Adamu Abubakar,Arief Hermawan,Hongwu Qin,Mukhtar Fatihu Hamza,Tutut Herawan +7 more
TL;DR: This study may provide a proper guide for novice as well as expert researchers in the design of evolutionary neural networks helping them choose suitable values of genetic algorithm operators for applications in a specific problem domain.
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A study on optimal design of process parameters in single point incremental forming of sheet metal by combining Box–Behnken design of experiments, response surface methods and genetic algorithms
TL;DR: In this paper, a numerical model of single point incremental forming of aluminum truncated cone geometries is developed by means of Finite Element simulation code ABAQUS and validated experimentally.
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On calibration of orthotropic elastic-plastic constitutive models for paper foils by biaxial tests and inverse analyses
TL;DR: In this article, two procedures are developed for the identification of the parameters contained in an orthotropic elastic-plastic-hardening model for free standing foils, particularly of paper and paperboard.
References
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Journal ArticleDOI
Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms
TL;DR: In this paper, a hybrid algorithm was proposed to improve the performance of the gradient-based algorithm, which is strongly dependent on the initial set of results, in order to analyse the effectiveness of this optimization procedure, numerical and experimental results for an EN AW-5754 aluminium alloy are compared.
Journal ArticleDOI
Identification of Mechanical Material Behavior Through Inverse Modeling and DIC
TL;DR: Inverse methods offer a powerful tool for the identification of the elasto-plastic material parameters as mentioned in this paper, which can deal with heterogeneous deformation fields, and are able to deal with the fact that the unknown material parameters in the FE model are iteratively tuned so as to match the experimentally measured and numerically computed strain fields as closely as possible.
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Multi-objective stacking sequence optimization of laminated cylindrical panels using a genetic algorithm and neural networks
M. Abouhamze,Mahmoud Shakeri +1 more
TL;DR: In this paper, a multi-objective optimization strategy for optimal stacking sequence of laminated cylindrical panels is presented, with respect to the first natural frequency and critical buckling load, using the weighted summation method.
Journal ArticleDOI
Elasto-plastic material parameter identification by inverse methods: Calculation of the sensitivity matrix
TL;DR: Inverse methods offer a powerful tool for the identification of elasto-plastic material properties of metals as discussed by the authors, where the basic principle of the inverse method is to compare an experimentally measured strain field with a strain field computed by a finite element (FE) model.