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High-toughness high-temperature-resistant RAFM steel and design method thereof based on machine learning

A technology of machine learning and design method, applied in the field of steel materials, which can solve time-consuming and complex problems

Active Publication Date: 2021-07-06
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

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  • High-toughness high-temperature-resistant RAFM steel and design method thereof based on machine learning
  • High-toughness high-temperature-resistant RAFM steel and design method thereof based on machine learning
  • High-toughness high-temperature-resistant RAFM steel and design method thereof based on machine learning

Examples

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Embodiment 1

[0053] A high-strength, toughness and high-temperature-resistant RAFM steel in this embodiment is designed by using the method of the present invention, and the smelting and subsequent heat treatment are carried out in strict accordance with the composition and heat treatment parameters designed in the present invention.

[0054] The RAFM steel includes the following chemical components in mass percent: 0.12%C, 10.5%Cr, 1.6%W, 0.52%Si, 0.6%Mn, 0.27%V, 0.26%Ta, 0.001%Zr, 0.01%Y, 0.002% %Ti, 0.04% N, and the rest are Fe elements and other unavoidable impurity elements. The heat treatment parameters of the RAFM steel are: normalizing temperature (NT) 1050°C, normalizing time (Nt) 20min, tempering temperature (TT) 600°C, tempering time (Tt) 90min.

Embodiment 2

[0056] A high-strength, toughness and high-temperature-resistant RAFM steel in this embodiment is designed by using the method of the present invention, and the smelting and subsequent heat treatment are carried out in strict accordance with the composition and heat treatment parameters designed in the present invention.

[0057] The RAFM steel includes the following chemical components in mass percent: 0.16%C, 9.5%Cr, 1.8%W, 0.48%Si, 0.7%Mn, 0.23%V, 0.10%Ta, 0.005%Zr, 0.05%Y, 0.012% %Ti, 0.02% N, the rest is Fe and other unavoidable impurity elements. The heat treatment parameters of the RAFM steel are: normalizing temperature (NT) 1010°C, normalizing time (Nt) 55min, tempering temperature (TT) 720°C, tempering time (Tt) 50min.

Embodiment 3

[0059] A high-strength, toughness and high-temperature-resistant RAFM steel in this embodiment is designed by using the method of the present invention, and the smelting and subsequent heat treatment are carried out in strict accordance with the composition and heat treatment parameters designed in the present invention.

[0060] The RAFM steel includes the following chemical components in mass percent: 0.13%C, 9.5%Cr, 1.7%W, 0.49%Si, 0.67%Mn, 0.25%V, 0.20%Ta, 0.002%Zr, 0.03%Y, 0.005% %Ti, 0.021% N, and the rest are Fe and other unavoidable impurity elements. The heat treatment parameters of the RAFM steel are: normalizing temperature (NT) 1010°C, normalizing time (Nt) 36min, tempering temperature (TT) 660°C, tempering time (Tt) 76min.

[0061] In the above-mentioned Examples 1-3, other unavoidable impurity elements are Al, Ni, Mo, Nb, Cu, B, S, P, O, and the proportion of each impurity element is: Al: 0-0.010%, Ni: 0~0.005%, Mo: 0~0.005%, Nb: 0~0.010%, Cu: 0~0.010%, B: 0~0.0...

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Abstract

The invention provides high-toughness high-temperature-resistant RAFM steel which comprises the following chemical components: 0.12 to 0.16 percent of C, 9.5 to 10.5 percent of Cr, 1.6 to 1.8 percent of W, 0.48 to 0.52 percent of Si, 0.6 to 0.7 percent of Mn, 0.23 to 0.27 percent of V, 0.10 to 0.26 percent of Ta, 0.001 to 0.005 percent of Zr and the like. The heat treatment parameters are as follows: the normalizing temperature is 1010-1050 DEG C, the normalizing time is 20-55 minutes, the tempering temperature is 600-720 DEG C, and the tempering time is 50-90 minutes. The invention further provides a machine learning-based design method of the steel. The RAFM steel disclosed by the invention has a relatively high use temperature upper limit and also has a relatively good tensile property at a high temperature; and meanwhile, the machine learning method constructed by the invention is high in generalization ability, and reasonable components and heat treatment parameters can be quickly and efficiently designed.

Description

technical field [0001] The invention relates to the technical field of iron and steel materials, in particular to a high-strength, high-temperature-resistant RAFM steel and a design method based on machine learning. Background technique [0002] Low-activation ferritic / martensitic (RAFM) steels developed from conventional 9Cr-1Mo steels are considered to be very promising structures for fusion reactors due to their good thermophysical, thermomechanical, and radiation resistance properties Material. As a metallic structural material, tensile properties are the most important fundamental factor in the design and application evaluation of RAFM steel. In fusion reactors, the improvement of high-temperature mechanical properties of structural materials is conducive to improving the utilization efficiency of nuclear energy. At present, the upper limit of the service temperature of RAFM steel is 550°C. In order to optimize the high temperature tensile properties of RAFM steels, ...

Claims

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Application Information

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IPC IPC(8): C22C38/02C22C38/04C22C38/22C22C38/24C22C38/26C22C38/28C21D1/18C21D1/28C21D6/00C21D11/00G16C60/00G16C20/70G16C20/50G16C20/30G06N20/20G06N20/10G06N5/00G06N3/08
CPCC22C38/22C22C38/02C22C38/04C22C38/24C22C38/26C22C38/28C22C38/005C22C38/001C21D1/28C21D1/18C21D11/00C21D6/002C21D6/005C21D6/008G16C60/00G16C20/70G16C20/50G16C20/30G06N20/20G06N20/10G06N3/08G06N5/01
Inventor 郑明杰李孝晨丁文艺
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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