Optimization strategies for non-linear material parameters identification in metal forming problems

de-Carvalho, R.; Valente, R. A. F.; Andrade‐Campos, A.

doi:10.1016/j.compstruc.2010.10.002

Cited by 36 publications

(27 citation statements)

References 21 publications

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“…This constitutive model leads to feasible stress-strain results only when σ 0 < σ ∞ . Therefore during the formulation of the minimization problem this constraint must be taken into account [3].…”

Section: Non-linear Elastoplastic Harden-ing Modelmentioning

confidence: 99%

“…The first constitutive model here studied is an elastoplastic model with non-linear hardening for stainless steel AISI 304 [3]. Experimental tests were carried out in proportional loading for uniaxial tension.…”

Section: Non-linear Elastoplastic Harden-ing Modelmentioning

confidence: 99%

“…The aim of these problems, for instance, is to estimate material parameters for constitutive models. This inverse problem is solved with the aid of optimization algorithms [3]. In this work, the use of single-point or metal forming FE analysis for the evaluation of the objective function in the identification process is analysed.…”

Section: Introductionmentioning

confidence: 99%

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On the Objective Function Evaluation in Parameter Identification of Material Constitutive Models - Single-point or FE Analysis

2010

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This work deals with the identification of constitutive parameters by inverse methodology. Two different approaches are presented and analysed: the single-point and FE analysis. The use of these two different methodologies for the evaluation of objective functions in the identification process is still an open question and the interest in this field has been increasing among the metal forming community. To discuss this issue, two different constitutive models suitable for metals were used, i.e. an elastoplastic hardening model and an elastoplastic model with isotropic and kinematic hardening. The determined material parameters for the two models, the respective objective function values and the CPU time required to perform the simulations are presented and discussed.

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Section: Non-linear Elastoplastic Harden-ing Modelmentioning

confidence: 99%

Section: Non-linear Elastoplastic Harden-ing Modelmentioning

confidence: 99%

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On the Objective Function Evaluation in Parameter Identification of Material Constitutive Models - Single-point or FE Analysis

2010

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“…given the desired shape, what tool geometry and material properties should be used? The first step is estimation of material properties, as shown in [29,30]. If tool geometry is expressed parametrically, optimization methods can be developed for automated parameter identification [31], [32].…”

Section: Incremental Sheet Forming (Isf)mentioning

confidence: 99%

Human-Robot Collaboration for Creative and Integrated Design and Fabrication Processes

Sharif¹,

Gentry²,

Sweet³

2016

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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This paper proposes a new framework for digital design to fabrication workflow to create an effective collaboration process between human designers and industrial robots, in order to redefine the relationship between design and production. This framework aims at redefining the current one-directional workflow of design to robotic fabrication that is imposed by the current robot programming and control systems, originally developed for engineering product industries. Our proposed system employs machine perception, adaptive control, and design libraries to adapt fabrication processes in real time, in parallel with human perception, learning, and guidance, to act as a catalyst of innovation for design practices, accelerating the design and production of novel building and industrial components.

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“…The inverse problem is generally solved through the use of an optimization approach, in which a discrepancy function between the computed output variables (given a trial set of input parameters) and the measured entities is minimised. While calibration methods with dynamic tests and inverse analysis techniques (dynamic inverse analysis) are now well-established for determining constitutive elastic parameters of existing structures [13], [14], [15], the use of static tests may represent a more suitable and cheaper strategy when nonlinear material parameters are to be sought [16]. However, the results obtained by applying inverse analysis with experimental static tests (static inverse analysis) may be less accurate, mainly because of the limited amount of information that static tests can supply [17].…”

Section: Introductionmentioning

confidence: 99%

An inverse analysis procedure for material parameter identification of mortar joints in unreinforced masonry

Chisari

Macorini

Amadio

et al. 2015

Computers & Structures

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Optimization strategies for non-linear material parameters identification in metal forming problems

Cited by 36 publications

References 21 publications

On the Objective Function Evaluation in Parameter Identification of Material Constitutive Models - Single-point or FE Analysis

On the Objective Function Evaluation in Parameter Identification of Material Constitutive Models - Single-point or FE Analysis

Human-Robot Collaboration for Creative and Integrated Design and Fabrication Processes

An inverse analysis procedure for material parameter identification of mortar joints in unreinforced masonry

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