Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Chaparro, Bruno M.; Thuillier, Sandrine; Menezes, L.F.; Manach, Pierre‐Yves; Fernandes, J.V.

doi:10.1016/j.commatsci.2008.03.028

Cited by 192 publications

(115 citation statements)

References 34 publications

Supporting

Mentioning

102

Contrasting

Order By: Relevance

“…A multi-set of nonlinear equations was established and then, the obtained equations were solved to determine the required parameters using an iterative technique such as Newton-Raphson approach. In other studies (Chaparro et al, 2008;Mahmoudi et al, 2011), genetic algorithm (GA) was used to minimize the difference between the numerical predictions and the experimental results when calibrating the NLKH models. However, FEMU has a drawback that it is time-consuming due to the iterative nature of the FE model updating process.…”

Section: Introductionmentioning

confidence: 99%

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

Barlat

Kim

et al. 2016

International Journal of Solids and Structures

View full text Add to dashboard Cite

In this work, the nonlinear kinematic hardening combined with Voce isotropic hardening was selected to characterize the material behavior of advanced high strength steel sheet samples subjected to a few reverse loading cycles. Multi-components of backstress were considered for the combined nonlinear kinematical hardening model, namely, one, two, and three backstress components. To calibrate the model, an inverse problem solution tool, so-called virtual fields method, which takes full advantage of full-field deformation measurement, was applied to identify the material constitutive parameters. First, finite element simulations of forward-reverse simple shear were performed to validate the proposed identification method. The influence of strain noise on the identification accuracy was also evaluated. Then, the proposed method was applied to three kinds of sheet metals (DP600, TRIP780 and TWIP980) tested under two cycles of forward-reverse simple shear for parameter identification. The identification results obtained with different number of backstress components were critically discussed.

show abstract

Section: Introductionmentioning

confidence: 99%

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

Barlat

Kim

et al. 2016

International Journal of Solids and Structures

View full text Add to dashboard Cite

show abstract

“…The fifth case only considers torsion. The optimal position of the mechanical components on the external fixator is obtained from a real-coded genetic algorithm [32], in which the objective function is the minimization of the norm of the resulting displacement in the fracture focus according to where u x , u y and u z represents the displacement in the x, y and z directions, respectively. The considered settings and genetic operators used within the genetic algorithm are presented in table 2.…”

Section: Optimization Proceduresmentioning

confidence: 99%

External fixator configurations in tibia fractures: 1D optimization and 3D analysis comparison

Roseiro¹,

Neto

Amaro

et al. 2014

Computer Methods and Programs in Biomedicine

View full text Add to dashboard Cite

show abstract

“…The optimization problem expressed by equation (9) is solved using a genetic algorithm, specially recommended for the solution of curve fitting problems [22].…”

Section: Wind Turbine Blade Optimizationmentioning

confidence: 99%

Design blades of a wind turbine using flexible multibody modelling

Neto¹,

Yu²,

Ambrósio³

et al. 2009

REPQJ

View full text Add to dashboard Cite

Abstract.A methodology for the application of structural optimization to find the optimal layouts of composite blades, based on a multibody model of a wind turbine, is presented. VABS (Variational Asymptotic Beam Section) is used to compute the sectional constants for a generalized Timoshenko beam model. The gravity and inertia effects are taken into account as well as the aerodynamic force, which are calculated by the aerodynamic coefficients and transferred to the corresponding finite element nodes. The minimum lateral moment component at the blade root is found by using an optimization methodology that finds the optimal values for the fiber orientation of the composite spar of the blade. The computational efficiency and robustness of the optimal process relies on the accurate evaluation of the system sensitivities. In this work a general formulation for the computation of the first order analytical sensitivities based on the direct method is used. The direct method for sensitivity calculation is obtained by differentiating the equations defining the response of the structure with respect to the design variables. The equations of motion and sensitivities of the flexible multibody system are solved simultaneously and therefore the accelerations and velocities of the system and the sensitivities of the accelerations and of the velocities are integrated in time using a multi-step multi-order integration algorithm.

show abstract

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Cited by 192 publications

References 34 publications

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

External fixator configurations in tibia fractures: 1D optimization and 3D analysis comparison

Design blades of a wind turbine using flexible multibody modelling

Contact Info

Product

Resources

About