Solution to Shape Optimization Problem Considering Material Non-linearity.

Ihara, Hisashi; Azegami, Hideyuki; Shimoda, Masatoshi; Watanabe, Katsuhiko

doi:10.1299/kikaia.66.1111

Cited by 6 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equation 5describes the regression model of the present system, which includes the interaction term [8]: (5) where is the predicted response…”

Section: Analysis Of Variance (Anova)mentioning

confidence: 99%

“…The studies on optimization of elastic and elasto-plastic structures have been extensively investigated during the past 30 years, and a number of useful algorithms and methodologies are developed(e.g. [4] [5]). As a practical and effective optimum design methodology for nonlinear problem, the response surface methodology (RSM) combined with the design of experiment (DOE) technique is currently applied to nonlinear design optimization problems, such as optimization problems of crushing energy absorbing of the automobile body and boxtype column structures [6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-Objective Design Optimization of the Low-Yield Steel Shear Panel Damper

Liu¹,

Shimoda²

2014

Proceedings of 10th World Congress on Computational Mechanics

View full text Add to dashboard Cite

This paper presents a shape optimization methodology for the design of the lowyield steel shear panel damper without stiffeners. The optimization was carried out as a multiobjective optimization problem to maximize the total absorbing energy and minimize the max. accumulated equivalent plastic strain of the shear panel damper under cyclic loading. With application of the optimization methodology of the response surface methodology combined with the design of experiment technique, firstly, finite element analysis with isotropic/kinematic hardening model was used to simulate the cyclic elasto-plastic behavior instead of experimental approach, and reliability of the numerical solutions was confirmed by comparing to previous experimental results. Then, based on the numerical analysis, the shape parameters effects and their interactions were investigated and second order polynomials were fitted to obtain the regression equations of the total absorbing energy and the max. accumulated equivalent plastic strain. Finally, the regression equations were applied to constitute the multi-objective functional by using the weighed sum method, and maximization problem of the formulated multi-objective functional was solved.

show abstract

“…Equation 5describes the regression model of the present system, which includes the interaction term [8]: (5) where is the predicted response…”

Section: Analysis Of Variance (Anova)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Objective Design Optimization of the Low-Yield Steel Shear Panel Damper

Liu¹,

Shimoda²

2014

Proceedings of 10th World Congress on Computational Mechanics

View full text Add to dashboard Cite

show abstract

“…This paper is devoted to presenting a concrete solution to the geometrical domain identification problems previously treated by the author's research group [6][7][8][9][10][11][12][13][14][15][16][17][18] while keeping the mathematical background.…”

Section: Introductionmentioning

confidence: 99%

Solution to boundary shape identification problems in elliptic boundary value problems using shape derivatives

Azegami

2000

Inverse Problems in Engineering Mechanics II

Self Cite

View full text Add to dashboard Cite

This paper concerns the problem identifying geometrical boundary shapes of domains in which elliptic boundary value problems are defined. Such identification problems can be formulated as minimization problems of squared error integrals between the actual solutions of the elliptic boundary value problems and their reference data with respect to perturbation of the uncertain boundary. Mathematicians have presented fundamental theories concerning the shape derivatives of functionals with respect to domain perturbation and the gradient method in Hilbert space. Based on these theories, this paper presents a concrete solution to geometrical domain identification problems. It briefly describes the derivation of the shape gradient functions for two types of shape identification problems with respect to a boundary value on a subboundary and with respect to the gradient in the subdomain and defines the gradient method in Hilbert space. Using the shape gradient functions thus derived and the concept of the gradient method in Hilbert space, a concrete solution to geometrical boundary identification problems is presented. This solution coincides with the traction method proposed previously by the author's research group.

show abstract

Shape Optimization Problems of Domain Variation Type

Azegami

2020

Shape Optimization Problems

View full text Add to dashboard Cite

Solution to Shape Optimization Problem Considering Material Non-linearity.

Cited by 6 publications

References 0 publications

Multi-Objective Design Optimization of the Low-Yield Steel Shear Panel Damper

Multi-Objective Design Optimization of the Low-Yield Steel Shear Panel Damper

Solution to boundary shape identification problems in elliptic boundary value problems using shape derivatives

Shape Optimization Problems of Domain Variation Type

Contact Info

Product

Resources

About