Untitled

Yabe, Hiroshi; Ogasawara, Hideho

doi:10.1023/a:1018391917880

Cited by 8 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…process optimization, a nonzero solution is expected. The second order term was therefore approximated as m i=1 r i (x)G i A k by the Totally Structured Secant Method, proposed by Huschens [5,6], additionally the Huschens scaling scheme can be combined with the projected scaling scheme [7,8]. For more information on performance of the three different least-square formulations, see [9].…”

Section: Optimization Schemementioning

confidence: 99%

Advanced Gradient Based Optimization Techniques Applied on Sheet Metal Forming

Endelt¹,

Nielsen²

2005

AIP Conference Proceedings

View full text Add to dashboard Cite

The computational-costs for finite element simulations of general sheet metal forming processes are considerable, especially measured in time. In combination with optimization, the performance of the optimization algorithm is crucial for the overall performance of the system, i.e. the optimization algorithm should gain as much information about the system in each iteration as possible. Least-square formulation of the object function is widely applied for solution of inverse problems, due to the superior performance of this formulation. In this work focus will be on small problems which are defined as problems with less than 1000 design parameters; as the majority of real life optimization and inverse problems, represented in literature, can be characterized as small problems, typically with less than 20 design parameters. We will show that the least square formulation is well suited for two classes of inverse problems; identification of constitutive parameters and process optimization. The scalability and robustness of the approach are illustrated through a number of process optimizations and inverse material characterization problems; tube hydro forming, two step hydro forming, flexible aluminum tubes, inverse identification of material parameters.

show abstract

Section: Optimization Schemementioning

confidence: 99%

Advanced Gradient Based Optimization Techniques Applied on Sheet Metal Forming

Endelt¹,

Nielsen²

2005

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…process optimization, a nonzero solution is expected. The second order term was therefore approximated as m i=1 r i (x)G i A k by the Totally Structured Secant Method, proposed by Huschens [9,10], additional the Huschens scaling scheme can be combined with the projected scaling scheme [11,12]. For more informations on performance of the three different least-square formulations, see [13].…”

Section: Optimization Schemementioning

confidence: 99%

Analytic Differentiation of Barlat’s 2D Criteria for Inverse Modeling

Endelt¹,

Nielsen²,

Danckert³

2005

AIP Conference Proceedings

View full text Add to dashboard Cite

“…is satisfied, where ŷk = A k+1 s k + F k+1 F k y * k and y * k is given in Equation (13). Another version of the convergence proof by Huschens was given by Yabe and Ogasawara in [63], where they extend the result from a restricted convex class to a wider class of the structured Broyden's family.…”

mentioning

confidence: 94%

A brief survey of methods for solving nonlinear least-squares problems

Mohammad¹,

Waziri²,

Santos³

2019

Numerical Algebra, Control &Amp; Optimization

View full text Add to dashboard Cite

In this paper, we present a brief survey of methods for solving nonlinear least-squares problems. We pay specific attention to methods that take into account the special structure of the problems. Most of the methods discussed belong to the quasi-Newton family (i.e. the structured quasi-Newton methods (SQN)). Our survey comprises some of the traditional and modern developed methods for nonlinear least-squares problems. At the end, we suggest a few topics for further research.

show abstract

Untitled

Cited by 8 publications

References 14 publications

Advanced Gradient Based Optimization Techniques Applied on Sheet Metal Forming

Advanced Gradient Based Optimization Techniques Applied on Sheet Metal Forming

Analytic Differentiation of Barlat’s 2D Criteria for Inverse Modeling

A brief survey of methods for solving nonlinear least-squares problems

Contact Info

Product

Resources

About