Search Sites

Tetsu-to-Hagané Vol. 111 (2025), No. 1

ISIJ International
belloff

Grid List Abstracts

ONLINE ISSN: 1883-2954
PRINT ISSN: 0021-1575
Publisher: The Iron and Steel Institute of Japan

Backnumber

  1. Vol. 111 (2025)

  2. Vol. 110 (2024)

  3. Vol. 109 (2023)

  4. Vol. 108 (2022)

  5. Vol. 107 (2021)

  6. Vol. 106 (2020)

  7. Vol. 105 (2019)

  8. Vol. 104 (2018)

  9. Vol. 103 (2017)

  10. Vol. 102 (2016)

  11. Vol. 101 (2015)

  12. Vol. 100 (2014)

  13. Vol. 99 (2013)

  14. Vol. 98 (2012)

  15. Vol. 97 (2011)

  16. Vol. 96 (2010)

  17. Vol. 95 (2009)

  18. Vol. 94 (2008)

  19. Vol. 93 (2007)

  20. Vol. 92 (2006)

  21. Vol. 91 (2005)

  22. Vol. 90 (2004)

  23. Vol. 89 (2003)

  24. Vol. 88 (2002)

  25. Vol. 87 (2001)

  26. Vol. 86 (2000)

  27. Vol. 85 (1999)

  28. Vol. 84 (1998)

  29. Vol. 83 (1997)

  30. Vol. 82 (1996)

  31. Vol. 81 (1995)

  32. Vol. 80 (1994)

  33. Vol. 79 (1993)

  34. Vol. 78 (1992)

  35. Vol. 77 (1991)

  36. Vol. 76 (1990)

  37. Vol. 75 (1989)

  38. Vol. 74 (1988)

  39. Vol. 73 (1987)

  40. Vol. 72 (1986)

  41. Vol. 71 (1985)

  42. Vol. 70 (1984)

  43. Vol. 69 (1983)

  44. Vol. 68 (1982)

  45. Vol. 67 (1981)

  46. Vol. 66 (1980)

  47. Vol. 65 (1979)

  48. Vol. 64 (1978)

  49. Vol. 63 (1977)

  50. Vol. 62 (1976)

  51. Vol. 61 (1975)

  52. Vol. 60 (1974)

  53. Vol. 59 (1973)

  54. Vol. 58 (1972)

  55. Vol. 57 (1971)

  56. Vol. 56 (1970)

  57. Vol. 55 (1969)

  58. Vol. 54 (1968)

  59. Vol. 53 (1967)

  60. Vol. 52 (1966)

  61. Vol. 51 (1965)

  62. Vol. 50 (1964)

  63. Vol. 49 (1963)

  64. Vol. 48 (1962)

  65. Vol. 47 (1961)

  66. Vol. 46 (1960)

  67. Vol. 45 (1959)

  68. Vol. 44 (1958)

  69. Vol. 43 (1957)

  70. Vol. 42 (1956)

  71. Vol. 41 (1955)

Tetsu-to-Hagané Vol. 111 (2025), No. 1

Selective Visualization of Martensite in Bainitic Steel Using Backscattered Electron Images and Phase Fraction Evaluation Using Machine Learning

Hiroshi Imoto, Kaoru Sato, Kenji Ogata

pp. 1-8

Abstract

Multi-phase steels are often used to realize a combination of high strength and toughness and/or ductility. To optimize their mechanical properties, it is vital to accurately evaluate the grain size, hard phase size and distribution, and dislocation density. In this paper, we studied a new method for evaluating the morphology and phase fraction of the hard phase, i.e., the martensite-austenite constituent (M-A), which is an important component that governs the mechanical properties of high strength steels. Using a scanning electron microscope, martensite can be selectively visualized with a bright contrast by collecting high-angle backscattered electrons. This method identifies only martensite in isolation from other phases, whereas both martensite and austenite are highlighted with the conventional two-step etching method. In addition, machine learning image analysis allows accurate extraction of martensite even in the presence of inhomogeneous backscattered electron image contrast in the matrix. This method provides an accurate and simple evaluation of the morphology of martensite in multi-phase steels over a large area.

Bookmark

Share it with SNS

Article Title

Selective Visualization of Martensite in Bainitic Steel Using Backscattered Electron Images and Phase Fraction Evaluation Using Machine Learning

Effects of Laser Peening on Rotating Bending Fatigue Strength of Additive Manufactured Maraging Steel in Very High Cycle Fatigue Regime

Genya Nakamura, Akihiko Iwasaka, Yoshiyuki Furuya, Koji Takahashi

pp. 9-19

Abstract

Additive-manufacturing technology has attracted attention for the fabrication of components with complex shapes. However, the low fatigue strength of the metals produced via additive manufacturing poses a significant challenge. In this study, rotating–bending fatigue tests were performed on additive-manufactured maraging steel up to the very-high-cycle fatigue (VHCF) range (108 cycles). The effect of laser peening (LP) on the fatigue strength was examined. The LP introduced compressive residual stress near the surface, whereas tensile residual stress was generated internally. The fracture initiation point of the non-LP specimen was observed at the surface in the low-cycle range and in the interior in the VHCF range. In contrast, all the LP specimens fractured from the interior. LP was effective for increasing the fatigue strength in the low-cycle range; however, it reduced the fatigue strength in the VHCF range. The effect of LP on the VHCF strength was examined by focusing on the stress level at the fracture initiation point. Furthermore, the distribution of the defect size on the polished and fractured surfaces of the specimens was evaluated using extreme-value statistics. The results indicated that extreme-value statistics are effective for predicting the defect size in practical applications.

Bookmark

Share it with SNS

Article Title

Effects of Laser Peening on Rotating Bending Fatigue Strength of Additive Manufactured Maraging Steel in Very High Cycle Fatigue Regime

You can use this feature after you logged into the site.
Please click the button below.

Advanced Search

Article Title

Author

Abstract

Journal Title

Year

Please enter the publication date
with Christian era
(4 digits).

Please enter your search criteria.