“Seen Is Solution” a CAD/CAE integrated parallel reanalysis design system

Wang, Hu; Zeng, Yifan; Li, Enying; Huang, Guangxin; Gao, Guoping; Li, Guangyao

doi:10.1016/j.cma.2015.10.022

Cited by 47 publications

(10 citation statements)

References 43 publications

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“…Second, the purpose of this study is to enhance the abilities of the CAD/CAE integrated system and apply it to closed‐loop optimization. Recently, Wang et al developed a rapid CAD/CAE integrated design‐analysis system called “seen is solution” for complex design problems. Subsequently, Huang et al constructed a closed‐loop optimization framework based on reanalysis and subdivision.…”

Section: Introductionmentioning

confidence: 99%

An efficient auxiliary projection‐based multigrid isogeometric reanalysis method and its application in an optimization framework

Liu

et al. 2020

Numerical Meth Engineering

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Summary An efficient optimization framework is developed in this study by integrating auxiliary projection‐based multigrid isogeometric reanalysis (MG‐IGR) and metaheuristic searching techniques. It is well known that the inherent characteristics of isogeometric analysis (IGA) are superior in shape optimization problems. Inheriting the characteristics of IGA, an auxiliary projection‐based MG reanalysis (MGR) is proposed to construct mapping between the mesh before modification and after modification during the optimization process. Subsequently, MG‐IGR is utilized to reanalyze the modified design efficiently by reusing the initial evaluated results. Moreover, the proposed MG‐IGR also eliminates the restriction of mesh consistency. In this framework, the structure can be designed directly through parameterized control of the non‐uniform rational B‐spline (NURBS) model, and the MG‐IGR fast solver enables any metaheuristic algorithm to perform the optimization procedure. Moreover, the accuracy of the simulation can be guaranteed by the NURBS model and the convergence criterion of the MG. Finally, two geometric optimization examples are presented to validate the performance of the developed framework.

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Section: Introductionmentioning

confidence: 99%

An efficient auxiliary projection‐based multigrid isogeometric reanalysis method and its application in an optimization framework

Liu

et al. 2020

Numerical Meth Engineering

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“…Thus, considering the accuracy, the proposed exact reanalysis embedded in the iterative reanalysis approximation (IRA), is more appropriate for the MMC-based topology optimization. As a kind of DM, the exact reanalysis stems from Independent Coefficients 31,32 and Sherman-Morrison-Woodbury formula. 33,34 However, most of the existing reanalysis methods do not work without the direct factorization of the initial matrix.…”

Section: Introductionmentioning

confidence: 99%

Iterative reanalysis approximation‐assisted moving morphable component‐based topology optimization method

Guo

Wang

2020

Numerical Meth Engineering

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An Iterative Reanalysis Approximation-(IRA) assisted Moving Morphable Components-(MMCs) based topology optimization is developed (IRA-MMC) in this study. Compared with other classical topology optimization methods, Finite Element-based solver is replaced with the suggested IRA. In this way, the expensive computational cost can be significantly saved by several nested iterations. In the suggested algorithm, a hybrid optimizer based on Method of Moving Asymptotes approach and Globally Convergent version of Method of Moving Asymptotes is suggested to improve convergence ratio and avoid local optimum. Finally, the proposed approach is evaluated by some classical benchmark problems in topology optimization. The results show significant time saving without compromising accuracy.

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“…ES-FEM has its advantage that it is insensitive to the mesh distortion, moreover, it just uses the triangle elements to get highly accurate solutions without costing extra time, which is much more efficient than traditionally stochastic FEM. Recently, ES-FEM has been applied into laminated plates by Cui [35] and CAD/CAE integrated system by Wang et.al [36]. It has been gradually proven an accurate and reliable tool.…”

Section: Introductionmentioning

confidence: 99%

The performance prediction and optimization of the fiber-reinforced composite structure with uncertain parameters

Cui

Liang

et al. 2017

Composite Structures

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The fiber-reinforced composites display the random fiber orientations and uncertain material parameters because of the manufacturing error and scattering feature. For this problem, the uncertain prediction and optimization based on the transformed perturbation stochastic method, the edged-based smoothing technique and the optimization theory is presented. In this method, the non-Gaussian probability density functions and the cumulative distribution functions of multi-variables for stochastic static responses of fiber-reinforced composite structure are explicitly exhibited as the prediction result compared with the Monte Carlo solution. Unlike the direct MCs, it only needs an iteration as the FEM and has the potential in the complex construction. In order to improve the efficiency and capability to resist the mesh distortion compared with the traditional stochastic FEM, the edged-based smoothing technique is introduced into the present framework. Furthermore, the stable performance feature of the fiber-reinforced composite in the uncertain working condition is presented. Consequently, objectives of the structural stability and insensitivity criteria based on the second-order perturbation expansion are proposed, and overall uncertain conditions coupled by uncertain fiber orientation, external load, material parameters and geometry sizes are analyzed and optimized within this framework, respectively.

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“Seen Is Solution” a CAD/CAE integrated parallel reanalysis design system

Cited by 47 publications

References 43 publications

An efficient auxiliary projection‐based multigrid isogeometric reanalysis method and its application in an optimization framework

An efficient auxiliary projection‐based multigrid isogeometric reanalysis method and its application in an optimization framework

Iterative reanalysis approximation‐assisted moving morphable component‐based topology optimization method

The performance prediction and optimization of the fiber-reinforced composite structure with uncertain parameters

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