A gradient based algorithm to solve inverse plane bimodular problems of identification

Ran, Chunjiang; Yang, Haitian; Zhang, Guoqing

doi:10.1016/j.jcp.2017.11.005

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…The other advantage is that this paper's method provides a new approach for the uncertain damage analysis of soft biological tissues based on the surrogate model. Although the Monte Carlo method is an accurate and robust method for uncertainty analysis, the huge computational cost is a key challenge for its application to damage analyses since the nonlinear problem has to be repeatedly solved by the FEM 48,49 . Due to the huge computational cost, the Monte Carlo method is commonly introduced as a referenced approach, but it is rarely used in the practical engineering.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity analysis of non‐local damage in soft biological tissues

Zuo

Avril

Ran

et al. 2020

Numer Methods Biomed Eng

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Computational modeling can provide insight into understanding the damage mechanisms of soft biological tissues. Our gradient‐enhanced damage model presented in a previous publication has shown advantages in considering the internal length scales and in satisfying mesh independence for simulating damage, growth and remodeling processes. Performing sensitivity analyses for this model is an essential step towards applications involving uncertain patient‐specific data. In this paper, a numerical analysis approach is developed. For that we integrate two existing methods, that is, the gradient‐enhanced damage model and the surrogate model‐based probability analysis. To increase the computational efficiency of the Monte Carlo method in uncertainty propagation for the nonlinear hyperelastic damage analysis, the surrogate model based on Legendre polynomial series is employed to replace the direct FEM solutions, and the sparse grid collocation method (SGCM) is adopted for setting the collocation points to further reduce the computational cost in training the surrogate model. The effectiveness of the proposed approach is illustrated by two numerical examples, including an application of artery dilatation mimicking to the clinical problem of balloon angioplasty.

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Section: Discussionmentioning

confidence: 99%

Sensitivity analysis of non‐local damage in soft biological tissues

Zuo

Avril

Ran

et al. 2020

Numer Methods Biomed Eng

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“…, 2021). Ran et al. (2018) proposed a gradient based algorithm to calculate inverse plane bimodular problems for constitutive parameters, including tensile/compressive moduli and tensile/compressive Poisson ratios.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, they also used the method to simultaneously identify the interface and spatial field properties through the inversion of hydraulic head and discharge rate data obtained from a steady seepage flow experiment on a domain containing a predefined piping zone (Koch et al, 2021). Ran et al (2018) proposed a gradient based algorithm to calculate inverse plane bimodular problems for constitutive parameters, including tensile/compressive moduli and tensile/compressive Poisson ratios. Qasmi et al used the inverse analysis coupled with a finite element method of the nanoindentation test, to determine the viscoelastic mechanical properties of polypropylene modified by He þ particles implantation and by electrons irradiation (Qasmi et al, 2004), and study the influence of the residual stress on the determination of the Young's modulus of W thin film deposit on SiO2/Si substrate (Qasmi et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous identification of multi-parameter for power hardening elastoplastic problems in three-dimensional geometries

Zhang

Mei

Bai

et al. 2022

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PurposeThe purpose of this study is to simultaneously determine the constitutive parameters and boundary conditions by solving inverse mechanical problems of power hardening elastoplastic materials in three-dimensional geometries.Design/methodology/approachThe power hardening elastoplastic problem is solved by the complex variable finite element method in software ABAQUS, based on a three-dimensional complex stress element using user-defined element subroutine. The complex-variable-differentiation method is introduced and used to accurately calculate the sensitivity coefficients in the multiple parameters identification method, and the Levenberg–Marquardt algorithm is applied to carry out the inversion.FindingsNumerical results indicate that the complex variable finite element method has good performance for solving elastoplastic problems of three-dimensional geometries. The inversion method is effective and accurate for simultaneously identifying multi-parameters of power hardening elastoplastic problems in three-dimensional geometries, which could be employed for solving inverse elastoplastic problems in engineering applications.Originality/valueThe constitutive parameters and boundary conditions are simultaneously identified for power hardening elastoplastic problems in three-dimensional geometries, which is much challenging in practical applications. The numerical results show that the inversion method has high accuracy, good stability, and fast convergence speed.

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Sensitivity analysis-based full-scale bounds estimation for 2-D interval bi-modular problems

Ran

Yang

2021

Arch Appl Mech

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A gradient based algorithm to solve inverse plane bimodular problems of identification

Cited by 8 publications

References 10 publications

Sensitivity analysis of non‐local damage in soft biological tissues

Sensitivity analysis of non‐local damage in soft biological tissues

Simultaneous identification of multi-parameter for power hardening elastoplastic problems in three-dimensional geometries

Sensitivity analysis-based full-scale bounds estimation for 2-D interval bi-modular problems

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