Journal of the Japan Society for Technology of Plasticity
Online ISSN : 1882-0166
Print ISSN : 0038-1586
ISSN-L : 0038-1586
Volume 61 , Issue 709
Showing 1-4 articles out of 4 articles from the selected issue
Regular Papers
  • Nobuyoshi KAWAMURA, Takashi SAKAI, Ka KOU, Yingjun JIN, Hitoshi OMATA
    Type: research-article
    2020 Volume 61 Issue 709 Pages 27-32
    Published: 2020
    Released: February 25, 2020
    JOURNALS RESTRICTED ACCESS

    The lightweight 2000 series aluminum alloy has excellent specific strength and recyclability. However, defects such as cracks and wrinkles are generated when bending the sheet material. To solve these problems, we aimed to improve the bending workability by heat treatment with laser irradiation. When we use the laser irradiation, only bending part can be applied the heat because the irradiation width and the irradiated part can be set as desired. We found improved bending workability up to 90° cold bending by lowering the cooling rate after laser irradiation heat treatment. Therefore, to clarify the factors in the improvement of bending workability, changes in the crystal grain, texture, and hardness were investigated using SEM equipment. For a specimen with improved bending workability, the amount of precipitates decreased and their size increased, resulting in a coarser precipitate.

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  • Akira SHIGA, Tomohiro YAMASHITA, Yutaka NEISHI, Osamu UMEZAWA
    Type: research-article
    2020 Volume 61 Issue 709 Pages 33-39
    Published: 2020
    Released: February 25, 2020
    JOURNALS RESTRICTED ACCESS

    To apply hollow forming technology for car parts, it is necessary to understand the ductile fracture mechanism of hollow forming. In this study, the cold drawing test and the finite element method analysis (FEM) of hollow specimens were carried out. It was clarified that the ductile fracture of hollow specimens in cold drawing was affected by both stress triaxiality and Lode angle parameter. As a result of fracture observation of a hollow specimen, an equiaxed dimple and an elongated dimple were observed. A mixed-mode ductile fracture mechanism (shear deformation of voids and typical void growth and coalescence) for hollow specimens in cold drawing is assumed.

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  • ―Study on Void Closure of Large Steel Ingot, 4th Report―
    Kengo MOURI, Takeshi ARIMA, Michiaki FUKUYA, Kenji MATSUDA
    Type: research-article
    2020 Volume 61 Issue 709 Pages 40-47
    Published: 2020
    Released: February 25, 2020
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    Previous studies have shown that true strain is effective for evaluating void closure in multipass forging. However, the above-mentioned result was obtained by numerical simulation and an experiment using hot steel with a reduced-scale model having a spherical void, and it has not been confirmed whether it is effective with a real machine. Therefore, in this study, the effectiveness of using true strain was verified in real machine tests. The following conclusions were obtained. 1) In the ultrasonic test (UT) after the third forging, despite the equivalent strain applied to two steel ingots being the same, a large difference occurred in the defect distribution. From this result, it was clarified that the closing behavior of the void in actual machines under multipass forging cannot be evaluated using equivalent strain. 2) In the UT after the fourth forging, as a result of applying the same true strain to two steel ingots, the defects of both steel ingots almost disappeared and the results were the same. Therefore, it was clarified that the closing behavior of the void in actual machines under multipass forging can be evaluated using true strain.

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  • Kohta KOENUMA, Akinori YAMANAKA, Ikumu WATANABE, Toshihiko KUWABARA
    Type: research-article
    2020 Volume 61 Issue 709 Pages 48-55
    Published: 2020
    Released: February 25, 2020
    JOURNALS RESTRICTED ACCESS

    Deformation of an aluminum alloy sheet is affected by its underlying crystallographic texture and has been widely studied by the crystal plasticity finite element method (CPFEM). The numerical material test based on the CPFEM allows us to quantitatively estimate the stress-strain curve and the Lankford value (r-value), which depend on the texture of aluminum alloy sheets. However, in the use of the numerical material test as a means of optimizing the texture to design aluminum alloys, the CPFEM is computationally expensive. We propose a methodology for rapidly estimating the stress -strain curve and r-value of aluminum alloy sheets using deep learning with a neural network. We train the neural network with synthetic texture and stress-strain curves calculated by the numerical material test. To capture the features of synthetic texture from a {111} pole figure image, the neural network incorporates a convolution neural network. Using the trained neural network, we can estimate the uniaxial stress-strain curve and the in-plane anisotropy of the r-value for various textures that contain Cube and S components. The results indicate that the neural network trained with the results of the numerical material test is a promising methodology for rapidly estimating the deformation of aluminum alloy sheets.

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