基于物理的前模型,用于近乎实时的废核燃料组件定量成像
Ming Fang1, Riina Virta2,3, Peter Dendooven3
1Department of Nuclear, Plasma, and Radiological Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
Scientific reports
|March 23, 2025
概括
一种新的线性反向方法增强了被动性玛辐射断层扫描 (PGET) 用于核燃料核验. 这种方法准确量化了燃料针活动,克服了自我屏蔽和散射挑战,以改善核安全措施.
科学领域:
- 核工程 核工程是指核工程.
- 应用物理 应用物理
- 核安全保障措施 核安全保障
背景情况:
- 无源性玛辐射断层扫描 (PGET) 是国际原子能机构授权用于核燃料核验.
- 精确量化燃料针活动是具有挑战性的,因为自我屏蔽和散射.
- 现有的PGET方法在精确的活动测量方面存在困难.
研究的目的:
- 开发和验证用于PGET图像重建的线性反向方法.
- 为了提高在废燃料组件 (SFAs) 中的燃料针活动量化的准确性.
- 提高PGET系统建模的速度和效率.
主要方法:
- 开发了一种基于物理的前进模型,其中包含了对准器隔膜穿透和探测器散射.
- 框架图像重建作为线性反向问题.
- 使用VVER-1000和VVER-440 SFA模拟验证了增强的前向模型,与MCNP进行比较.
主要成果:
- 在前期模型和MCNP模拟之间的计数中实现了3.7%的相对差异.
- 在模拟中证明了卓越的图像质量和100%的燃料针识别准确性.
- 在活动量化中达到2.3%的平均不确定性.
- 从测量VVER-440 SFA数据成功重建图像,对所有引脚和水道进行成像.
结论:
- 增强的前模型显著加快了 PGET 协同图模拟和系统矩阵计算 (>100,000 倍比蒙特卡洛更快).
- 线性反向方法提供了准确的燃料针活动量化和更好的图像质量.
- 开发的方法显示了对现实世界核燃料检查和未来算法开发的巨大潜力.
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