Experimental and analytical studies on the prediction of forming limit diagrams

Ahmadi, Somayeh; Eivani, A.R.; Akbarzadeh, Abdolhamid

doi:10.1016/j.commatsci.2008.08.008

Cited by 40 publications

(33 citation statements)

References 9 publications

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“…The knowledge is presented by the interconnection weights, which are adjusted during the learning phase. There are several algorithms available among which the LevenbergMarquardt algorithm (trainlm) will have the fastest convergence [2]. In many cases, trainlm is able to obtain lower mean square errors than any of the other logrithms tested.…”

Section: Backpropagation (Bp) Networkmentioning

confidence: 98%

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Modelling the correlation between the geometrical features and the forming limit strains of perforated Al 8011 sheets using artificial neural network

Elangovan¹,

Narayanan²,

Narayanasamy³

2010

Int J Mater Form

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In the recent years, sheet metals are produced with perforations in various shapes and patterns to improve the appearance of sheet and to save weight of components. As in conventional metal sheets, it is important to form the perforated sheet metals also within their safe strain regions to avoid the forming failures like necking, fracture and wrinkling. The Forming Limit Diagram (FLD) is an appropriate tool to determine the forming limit strains. The limiting strains of perforated sheet metals mainly depend on the geometry of the perforations and forming variables. This leads to large increase in number of test to be conducted with various geometry and forming variables for determining the forming limit strain for perforated sheets. Aiming to reduce the number of experiments needed, in this work, an Artificial Neural Network (ANN) model has been developed for forming limit diagram of perforated Al 8011 sheets based on experimental results and correlated with the geometrical features of the perforated sheets. This model is a feed forward back propagation neural network (BPNN) with a set of geometrical variables as its inputs and the safe true strains as its output. This ANN model can be applied for prediction of FLD of perforated sheet having any geometry.

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Section: Backpropagation (Bp) Networkmentioning

confidence: 98%

“…These forming limit diagrams are being used by both manufacturers and users of the sheet metals. From the initiation of FLD concept, many numbers of works have been carried out in this field of FLD of sheet metals [1][2][3]. The important limitation of the FLD is that a FLD is applicable only for a particular sheet quality [4].…”

Section: Introductionmentioning

confidence: 99%

Modelling the correlation between the geometrical features and the forming limit strains of perforated Al 8011 sheets using artificial neural network

Elangovan¹,

Narayanan²,

Narayanasamy³

2010

Int J Mater Form

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“…Sendo assim, faz-se necessária uma análise dos efeitos destas variações de composição na estamapabilidade do material. Diversas são as formas de se analisar a estampabilidade de um material, uma forma muito usual é através da Curva de Limite de Conformação (CLC) que determina a capacidade máxima de deformação tolerada por um material quando sujeito ao processo de estampagem [6,7]. Este parâmetro ainda apresenta grande importância no projeto de peças estampadas através simulação computacional, pois a CLC é utilizada como critério de falha nos programas de simulações numéricas do processo de estampagem [7,8].Outro parâmetro bastante utilizado é a razão limite de estampagem (RLE), este parâmetro determina o limite da passagem de uma geratriz com diâmetro (D) para um corpo estampado com diâmetro (d), diâmetro do punção [9].…”

Section: Estampabilidade Dos Aços Inoxidáveisunclassified

Estudo Computacional Da Estampabilidade De Aço Inoxidável Através Da Simulação Numérica Do Ensaio De Cinco Punções

Carvalho¹,

Lora²,

Coelho³

2018

ABM Proceedings

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ResumoOs aços inoxidáveis possuem uma alta aplicabilidade nas indústrias de petróleo e gás, química e de papel e celulose, principalmente, devido à suas características de alta resistência à corrosão e alta resistência mecânica. Neste trabalho, estudos baseadas na técnica dos cinco punções foram realizados para avaliar as características de conformação do aço inoxidável UNS S32304. A metodologia baseia-se na caracterização mecânica do material para mensurar suas propriedades, como limite de escoamento e índice de anisotropia. Seguiu-se com uma análise teórica da estampabilidade do material através da simulação computacional do ensaio de cinco punções. Esta técnica analisa tipos de deformações desde o estiramento biaxial até o embutimento profundo. Esse trabalho apresenta uma análise computacional do comportamento desse material com relação à estampagem para os diversos punções. É apresentado o gráfico da Razão Limite de Estampagem teórica para o UNS S32304 em relação aos cinco punções utilizados e a influência do coeficiente de anisotropia normal nos resultados. Palavras-chave: Aço inoxidável; Ensaio de cinco punções; Conformação de chapas; Razão de estampagem. COMPUTATIONAL STUDY OF FORMABILITY OF STAINLESS STEEL THROUGH THE NUMERICAL SIMULATION OF FIVE PUNCH TEST AbstractThe stainless steel shows a high applicability in industries of oil and gas, chemical and cellulose and paper, mainly due to its high corrosion resistance and high strength characteristics. In this work, studies based on the five punch test were performed to evaluate the formability of the stainless steel UNS S32304. The method is based on the mechanical characterization of the material such as yield strength and anisotropy level. After measuring those properties, it was made a theoretical analysis of the formability of the material through a computer simulation based on the five punch test. This technique analyzes the types of resulting deformation from biaxial stretching to deep drawing. This paper presents a computational analysis of the material behavior in relation to the stamping for various punches. It is presented the analyses of the theoretical Limiting Drawing Ratio for UNS S32304 steel obtained by the five punches test and, in addition, discussed in terms of the influence of the normal anisotropy coefficient in the results.

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“…Actually, the formability of HSS can be measured by the FLD under different temperatures via experiments or theoretical models. Based on plastic instability theory, such as the M-K model[7], yield criterion[8] and hardening law[9], the theoretical prediction of FLD for HSS under evaluated temperature was achieved [10,11]. However, the practical FLD test for HSS under thermal circumstance is more convincing than the theoretical analysis in hot stamp simulation [12].…”

mentioning

confidence: 99%

Study on temperature distribution of HSS in hot FLD test

Yuan

et al. 2015

Applied Thermal Engineering

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Experimental and analytical studies on the prediction of forming limit diagrams

Cited by 40 publications

References 9 publications

Modelling the correlation between the geometrical features and the forming limit strains of perforated Al 8011 sheets using artificial neural network

Modelling the correlation between the geometrical features and the forming limit strains of perforated Al 8011 sheets using artificial neural network

Estudo Computacional Da Estampabilidade De Aço Inoxidável Através Da Simulação Numérica Do Ensaio De Cinco Punções

Study on temperature distribution of HSS in hot FLD test

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