使用混合非破坏性电磁测试和评估方法评估反应器压力容器钢中的脆性
Gábor Vértesy1, Madalina Rabung2, Antal Gasparics1
1HUN-REN Centre for Energy Research, 1121 Budapest, Hungary.
Materials (Basel, Switzerland)
|March 13, 2024
概括
非破坏性电磁测试 (NDE) 方法可以准确预测核反应堆钢中的脆性. 结合磁性测试和机器学习,可以显著改善对关键材料属性的预测,例如性-脆性过渡温度 (DBTT).
科学领域:
- 材料科学 材料科学 材料科学
- 核工程 核工程是指核工程.
- 非破坏性评估 (NDE) 是一种非破坏性评估.
背景情况:
- 中子辐射导致核反应堆压力容器钢的脆化,这是一个关键的安全问题.
- 准确评估这种脆弱性对于保持核电站完整性至关重要.
- 现有的非破坏性方法往往缺乏可靠的脆弱性评估所需的精度.
研究的目的:
- 评估新的非破坏性电磁测试和评估 (NDE) 方法来评估中子辐射诱导的脆性.
- 为了比较各种磁性NDE技术和机器学习算法的有效性.
- 建立一种可靠的方法来预测柔性-脆性过渡温度 (DBTT) 和其他机械性质.
主要方法:
- 微磁,多参数,微结构和应力分析 (3MA),磁性适应性测试 (MAT) 和巴克豪森噪声技术 (MBN) 的应用.
- 将NDE测量结果与破坏性确定的DBTT值进行比较.
- 整合多种NDE方法和机器学习 (ML) 算法进行协同分析.
主要成果:
- 3MA,MAT和MBN表现出很高的承诺,显示出彼此的良好一致性和与DBTT值的强烈相关性.
- 通过ML增强的多方法/多参数方法,在关键的±25°C值以下实现了DBTT预测错误.
- 机器学习算法成功地预测了不同材料的过渡温度,度强度和机械硬度,在不同材料中具有非常好的准确性.
结论:
- 结合NDE方法和机器学习,在核反应堆中非破坏性地确定钢材脆性方面取得了突破.
- 诺马德项目的方法为评估材料降解提供了可靠和精确的工具,提高了核安全.
- 这些发现支持未来实施先进的NDE技术来监测核反应堆压力容器.
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