Determination of stress–strain relationship of tubular material with hydraulic bulge test

Yang, Lianfa; Guo, Cheng

doi:10.1016/j.tws.2007.08.017

Cited by 53 publications

(18 citation statements)

References 10 publications

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“…Hence, a tube bulge test is usually accepted as the most appropriate experiment for measuring material behaviour for tube hydroforming simulations , e.g. see (Zribi et al, 2013, Koç et al, 2001, Nemat-Alla, 2003, Strano and Altan, 2004, Hwang et al, 2007, Bortot et al, 2008, Lianfa and Cheng, 2008, Xu et al, 2008, Hwang and Wang, 2009, Saboori et al, 2014.…”

Section: Characterizing the Stress-strain Behaviour In Multi-axial Stmentioning

confidence: 99%

“…Their method requires measuring the instantaneous thickness, the longitudinal and circumferential radii of curvatures and the internal pressure. (Lianfa and Cheng, 2008) established an analytical formulation based on the plastic membrane theory and force equilibrium equations to obtain the stress-strain relationship from the curvature of the bulged area and the applied pressure. (Xu et al, 2008) introduced an adaptive inverse finite element method to determine the material hardening coefficient and the hardening exponent, two material parameters for the assumed material model.…”

Section: Characterizing the Stress-strain Behaviour In Multi-axial Stmentioning

confidence: 99%

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Flow stress identification of tubular materials using the progressive inverse identification method

Asaadi

Heyns

2016

Engineering Computations

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Purpose-Propose a progressive inverse identification algorithm to characterize flow stress of tubular materials from the material response, independent of choosing an a priori hardening constitutive model. Design/methodology/approach-In contrast to the conventional forward flow stress identification methods, the flow stress is characterized by a multi-linear curve rather than a limited number of hardening model parameters. The proposed algorithm optimizes the slopes and lengths of the curve increments simultaneously. The objective of the optimization is that the finite element simulation response of the test estimates the material response within a predefined accuracy. Findings-We employ the algorithm to identify flow stress of a 304 stainless steel tube in a tube bulge test as an example to illustrate application of the algorithm. Comparing response of the finite element simulation using the obtained flow stress with the material response shows that the method can accurately determine the flow stress of the tube. Practical implications-The obtained flow stress can be employed for more accurate finite element simulation of the metal forming processes as the material behaviour can be characterized in a similar state of stress as the target metal forming process. Moreover, since there is no need for a priori choosing the hardening model, there is no risk for choosing an improper hardening model, which in turn facilitates solving the inverse problem. Originality/value-The proposed algorithm is more efficient than the conventional inverse flow stress identification methods. In the latter, each attempt to select a more accurate hardening model, if it is available, result in constructing an entirely new inverse problem. However, this problem is avoided in the proposed algorithm.

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Section: Characterizing the Stress-strain Behaviour In Multi-axial Stmentioning

confidence: 99%

Section: Characterizing the Stress-strain Behaviour In Multi-axial Stmentioning

confidence: 99%

Flow stress identification of tubular materials using the progressive inverse identification method

Asaadi

Heyns

2016

Engineering Computations

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“…More details and insights into this well-known method for determining flow stress curve from free tube bulge test are given in Refs. [8,20,21].…”

Section: Determination Of Biaxial Stressesmentioning

confidence: 99%

“…Valesco et al, [19] proposed an analytical approach for tube bulging tests based on geometric observations, assuming a circular profile of the bulged zone and ignoring the fillet radius of the tube guiding dies. Lianfa et al, [20] Saboori et al, [8] and Liu et al, [21] have determined the flow stress curves for a diversity of tubular materials, using approaches based on the evaluation of the meridian radius of curvature by means of curve-fitting least squares methods. It is worth noting that the aforementioned methods assume material's isotropy, disregarding the studied tubular materials' anisotropy.…”

Section: Introductionmentioning

confidence: 99%

Mechanical characterization and constitutive parameter identification of anisotropic tubular materials for hydroforming applications

Khalfallah

Oliveira

Alves

et al. 2015

International Journal of Mechanical Sciences

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This paper aims to identify the constitutive parameters of anisotropic tubular materials and to verify the accuracy of models' prediction. The identification of the constitutive parameters is based on information obtained from tensile tests, performed on samples cut from the tubes, and from the free tubular bulge test, using a home-developed bulge forming machine. Two tubular materials exhibiting different anisotropic behaviour and work hardening characteristics are investigated: a mild steel S235 seamed tube and an aluminium alloy AA6063 extruded tube. It is shown that advanced phenomenological yield functions, including a large number of anisotropy parameters, can accurately describe the plastic flow of highly anisotropic tubular materials during the tube hydroforming process.However, parameter identification procedure of advanced yield criteria requires a high number of experimental tests. Thus, in order to enable the parameter identification of these yield criteria when using a reduced set of experimental results, the present study develops a method that combines tensile tests with: i) a free bulge test, which is used to characterize the biaxial stress state experienced by the tube during the bulge testing, and ii) some generated artificial input data. Finally, the proposed method shows an excellent agreement between numerical predictions and experimental results.

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“…To get material data from these tests, it is necessary to develop specific model and no standard is defined at the present time [5]. So several authors have proposed different approaches for the experimental data post-processing that can be classified into three families: (1) approaches based on 'off-line' measurements [6,7], (2) approaches based on 'on-line' measurements [8][9][10][11] and (3) approaches based on a mix of 'on-line' and 'off-line' measurements [12,13]. The first and third families are not satisfying because the approaches are very time and material consuming.…”

Section: Introductionmentioning

confidence: 99%

A simplified analytical model for post-processing experimental results from tube bulging test: Theory, experimentations, simulations

Boudeau

Malécot

2012

International Journal of Mechanical Sciences

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A complete analytical model combined with a very simple experimental procedure is proposed. It permits the post-processing of experimental measures to obtain the stress-strain curve for tubes very quickly and well adapted for industrial use. The quality of the results is proved by comparison with experimental measures and finite element results. Anisotropy in tube is revealed by plotting the (r,a) curve where r and a stand for strain and stress path respectively. Two quadratic criteria (Hill 1948 and Hill 1993) are studied and it is found that the Hill 1993 criterion seems the best to represent tube anisotropy for 316L stainless steel tube studied in the present paper.

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Determination of stress–strain relationship of tubular material with hydraulic bulge test

Cited by 53 publications

References 10 publications

Flow stress identification of tubular materials using the progressive inverse identification method

Flow stress identification of tubular materials using the progressive inverse identification method

Mechanical characterization and constitutive parameter identification of anisotropic tubular materials for hydroforming applications

A simplified analytical model for post-processing experimental results from tube bulging test: Theory, experimentations, simulations

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