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鉄と鋼 Vol. 108 (2022), No. 7

ISIJ International
belloff

Grid List Abstracts
オンライン版ISSN: 1883-2954
冊子版ISSN: 0021-1575
発行機関: The Iron and Steel Institute of Japan

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  1. Vol. 110 (2024)

    1. No.7
    2. No.6
    3. No.5
    4. No.4
    5. No.3
    6. No.2
    7. No.1

  2. Vol. 109 (2023)

    1. No.12
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    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
    12. No.1

  3. Vol. 108 (2022)

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    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
    12. No.1

  4. Vol. 107 (2021)

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    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    12. No.1

  5. Vol. 106 (2020)

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    5. No.8
    6. No.7
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  6. Vol. 105 (2019)

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    5. No.8
    6. No.7
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  7. Vol. 104 (2018)

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    5. No.8
    6. No.7
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  8. Vol. 103 (2017)

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    5. No.8
    6. No.7
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  9. Vol. 102 (2016)

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    5. No.8
    6. No.7
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  10. Vol. 101 (2015)

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    6. No.7
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  11. Vol. 100 (2014)

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    6. No.7
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  12. Vol. 99 (2013)

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  13. Vol. 98 (2012)

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  14. Vol. 97 (2011)

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  15. Vol. 96 (2010)

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  16. Vol. 95 (2009)

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  17. Vol. 94 (2008)

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  18. Vol. 93 (2007)

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    5. No.8
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  19. Vol. 92 (2006)

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    5. No.8
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  20. Vol. 91 (2005)

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  21. Vol. 90 (2004)

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  22. Vol. 89 (2003)

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  23. Vol. 88 (2002)

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    4. No.9
    5. No.8
    6. No.7
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  24. Vol. 87 (2001)

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    3. No.10
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    6. No.7
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  25. Vol. 86 (2000)

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    3. No.10
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    5. No.8
    6. No.7
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  26. Vol. 85 (1999)

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    6. No.7
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  27. Vol. 84 (1998)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
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  28. Vol. 83 (1997)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
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  29. Vol. 82 (1996)

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    3. No.10
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    5. No.8
    6. No.7
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    10. No.3
    11. No.2
    12. No.1

  30. Vol. 81 (1995)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
    12. No.1

  31. Vol. 80 (1994)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
    12. No.1

  32. Vol. 79 (1993)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
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    10. No.3
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  33. Vol. 78 (1992)

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    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
    12. No.1

  34. Vol. 77 (1991)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
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  35. Vol. 76 (1990)

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    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
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  36. Vol. 75 (1989)

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    3. No.10
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    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
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  37. Vol. 74 (1988)

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    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
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    10. No.3
    11. No.2
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  38. Vol. 73 (1987)

    1. No.16
    2. No.15
    3. No.14
    4. No.13
    5. No.12
    6. No.11
    7. No.10
    8. No.9
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    10. No.7
    11. No.6
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  39. Vol. 72 (1986)

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    2. No.15
    3. No.14
    4. No.13
    5. No.12
    6. No.11
    7. No.10
    8. No.9
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    10. No.7
    11. No.6
    12. No.5
    13. No.4
    14. No.3
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  40. Vol. 71 (1985)

    1. No.16
    2. No.15
    3. No.14
    4. No.13
    5. No.12
    6. No.11
    7. No.10
    8. No.9
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    10. No.7
    11. No.6
    12. No.5
    13. No.4
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  41. Vol. 70 (1984)

    1. No.16
    2. No.15
    3. No.14
    4. No.13
    5. No.12
    6. No.11
    7. No.10
    8. No.9
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    10. No.7
    11. No.6
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  42. Vol. 69 (1983)

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    3. No.14
    4. No.13
    5. No.12
    6. No.11
    7. No.10
    8. No.9
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  43. Vol. 68 (1982)

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    3. No.14
    4. No.13
    5. No.12
    6. No.11
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  44. Vol. 67 (1981)

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    3. No.14
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    5. No.12
    6. No.11
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    13. No.4
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  45. Vol. 66 (1980)

    1. No.14
    2. No.13
    3. No.12
    4. No.11
    5. No.10
    6. No.9
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    8. No.7
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  46. Vol. 65 (1979)

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  47. Vol. 64 (1978)

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  48. Vol. 63 (1977)

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    3. No.12
    4. No.11
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    6. No.9
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  49. Vol. 62 (1976)

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    3. No.12
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    5. No.10
    6. No.9
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    8. No.7
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  50. Vol. 61 (1975)

    1. No.15
    2. No.14
    3. No.13
    4. No.12
    5. No.11
    6. No.10
    7. No.9
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    10. No.6
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    12. No.4
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  51. Vol. 60 (1974)

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    3. No.12
    4. No.11
    5. No.10
    6. No.9
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  52. Vol. 59 (1973)

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  53. Vol. 58 (1972)

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  54. Vol. 57 (1971)

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  55. Vol. 56 (1970)

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  56. Vol. 55 (1969)

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  57. Vol. 54 (1968)

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  58. Vol. 53 (1967)

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  59. Vol. 52 (1966)

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  60. Vol. 51 (1965)

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  61. Vol. 50 (1964)

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  62. Vol. 49 (1963)

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  63. Vol. 48 (1962)

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  64. Vol. 47 (1961)

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  65. Vol. 46 (1960)

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  66. Vol. 45 (1959)

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  67. Vol. 44 (1958)

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  68. Vol. 43 (1957)

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  69. Vol. 42 (1956)

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  70. Vol. 41 (1955)

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    11. No.2
    12. No.1

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08 May. (Last 30 Days)

鉄と鋼 Vol. 108 (2022), No. 7

初期Al濃度が異なる多元系チタン合金溶湯からのAlの蒸発挙動

水上 英夫, 白井 善久, Alec Mitchell

pp. 383-393

DOI:

10.2355/tetsutohagane.TETSU-2022-004

抄録

This study examines the evaporation of Al from a molten commercial Ti alloy with different Al concentrations after partial melting in a small electron beam furnace. Electron probe micro analysis confirmed that the Al concentration in the molten region was uniform. The movement of Al in the molten region was not found to be the rate determining step. The Al concentration in the molten region consistently decreased with an increasing melting time but in a non-linear manner. The activity of Al in the molten alloy was calculated using thermodynamic data, which indicated that it increased with an increasing Al concentration in the ingot. However, the activity of Al in the molten alloy did not increase linearly under the influence of the other alloying elements. The overall mass transfer coefficient of Al from molten alloy during evaporation increased with an increasing initial Al concentration with the mass transfer coefficient of Al depending on the activity of Al. An evaporation model was constructed by considering the mutual interaction between Al and the other alloying elements. This evaporation model was able to predict the amount of Al evaporation from the multi-component Ti alloy melt.

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初期Al濃度が異なる多元系チタン合金溶湯からのAlの蒸発挙動

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偏心管のプレス曲げ加工における変形特性

中島 邦斗, 内海 能亜, 吉田 昌史

pp. 394-404

DOI:

10.2355/tetsutohagane.TETSU-2021-126

抄録

Tubes are widely applied as structural members and members for fluid transmission. However, there is a concern that the strength of the tube will decrease because thickness deviation will occur during bending and the thickness on the tension side will decrease. Therefore, the authors devised an eccentric tube that eccentric the inner diameter of the tube and increases or decreases the thickness in the tube. In this study, we conducted an experiment and Finite Element Analysis (FEA) for the purpose of researching the deformation property of the eccentric tube and evaluating the appropriate value of the eccentricity e. As a result, it was found that, as a deformation property of the eccentric tube, even if there is a difference in thickness in the same tube, the thickness deviation becomes large in the case of thin wall. Furthermore, it was found that the flattening was reduced by setting the thick part of the eccentric tube to the tension side. In addition, the target value of the thickness after processing was set, and the eccentricity e at which the thickness after bending was close to the target value was estimated by FEA. As a result of conducting an experiment using the obtained eccentricity e, it was found that the thickness after processing can be made close to the target value by adjusting the eccentricity e.

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偏心管のプレス曲げ加工における変形特性

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炭素鋼におけるスポット状レーザ焼入れ部の組織とナノ硬さの関係

安田 武司, 正瑞 来夢, 西本 浩司, 奥本 良博, 大村 孝仁

pp. 405-416

DOI:

10.2355/tetsutohagane.TETSU-2021-090

抄録

The laser-quenching-induced heat-affected zone (HAZ) of carbon steel was nano-mechanically and sub-micro-structurally characterized. Ferrite–pearlite-structured JIS G 4053 SCM440 specimens were laser-irradiated at 275, 260, or 240 W. The specimens were mechanically characterized by nano-indentation, and the micro-structures were observed with scanning electron microscopy (SEM). The HAZ consisted of various phases and micro-structures, including auto-tempered martensite, as-quenched martensite, martensite containing undissolved cementite, and the original ferrite–pearlite. The region and fraction of the HAZ micro-structures depended on the distance from the sample surface and the laser power. The nanohardness of the martensite structures varied widely presumably depending on the thermal history and local carbon content. In particular, the hardness of the martensite containing the undissolved cementite could be interpreted in terms of the solute carbon content estimated based on the area fractions of the undissolved cementite and precipitated carbide, as observed in the binarized SEM images. The thermal history was theoretically simulated to ensure that the micro-structures and associated hardness values were reasonable.

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炭素鋼におけるスポット状レーザ焼入れ部の組織とナノ硬さの関係

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高速度工具鋼のベラーグ形成に及ぼすMC炭化物の影響

福元 志保, 福丸 大志郎

pp. 417-423

DOI:

10.2355/tetsutohagane.TETSU-2022-005

抄録

The present study investigated the microstructure of cutting tool in order to clarify their wear mechanism of cutting tool made of high speed tool steel in the metal cutting process. A special protective oxide surface, which mainly consist of iron, vanadium and oxygen is formed on the surface of the tool during dry cutting wear test. Iron could be diffused from cutting tool and cutting material, and vanadium which alloyed to improve tool life as MC carbide in high speed steel is from cutting tool. During cutting wear test, an amorphous oxide surface seems to exist in a liquid state. At the cutting temperature on the contact point of tool, the surface as so-called “Belag” is melted as a result of eutectic reaction of iron oxide and vanadium oxide. The surface has a role of fluid lubrication between work material and tool. Therefore, the surface is effective in protecting against tool wear at this cutting speed.

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高速度工具鋼のベラーグ形成に及ぼすMC炭化物の影響

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機械学習によるフェライト系耐熱鋼のクリープ破断寿命予測

櫻井 惇也, 出村 雅彦, 井上 純哉, 山﨑 政義

pp. 424-437

DOI:

10.2355/tetsutohagane.TETSU-2022-003

抄録

We have attempted to predict creep rupture time for a wide range of ferritic heat resistant steels with machine learning methods using the NIMS Creep Data Sheet (CDS). The dataset consisted of commercial steel data from 27 sheets in the CDS, covering various grades of carbon steels, low alloy steels, and high Cr steels. The prediction models were constructed using three methods, support vector regression (SVR), random forest, and gradient tree boosting with 5132 training data in order to predict log rupture time from chemical composition (19 elements), test temperature, and stress. Evaluation with 451 test data proved that all three models exhibited high predictivity of creep rupture time; in particular, the performance of the SVR model was the highest with a root mean squared error as low as 0.14 over the log rupture time, which value means that, on average, the prediction error was factor 1.38 (=100.14). The high predictivity achieved with no use of information on microstructure was presumably because the data used was for commercial steels in which there should be a correlation between the composition and the microstructure. We confirmed that the prediction did not work well exceptionally for two heats having the same composition but different microstructures with and without stress relief annealing. The predictivity could be drastically improved by adding the 0.2% proof stress at the creep test temperature as one of the explanatory variables. As a use case of the prediction model, the effect of elements was evaluated for modified 9Cr 1Mo steels.

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機械学習によるフェライト系耐熱鋼のクリープ破断寿命予測

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