Passive Gamma Emission Tomography (PGET) has been developed by the International Atomic Energy Agency as a way to directly image the spatial distribution of individual fuel pins in a spent nuclear fuel assembly and so determine potential diversion. Constructing the analysis and interpretation of PGET measurements rely on the availability of comprehensive datasets. Experimental data are expensive, limited, and so are augmented by Monte Carlo simulations. The main issue concerning Monte Carlo simulations is the high computational cost to simulate the 360 angular views of the tomography. Similar challenges pervade numerical science. To address this challenge, we have developed a physics-aware reduced order modeling approach. It provides a framework to combine a small subset of the 360 angular views with a computationally inexpensive proxy solution, that brings the essence of the physics, to obtain a real-time high-fidelity solution at all angular views, but at a fraction of the computational cost.
翻译:国际原子能机构开发了被动伽马射线透析仪(PGET),作为在乏核燃料组件中直接图像单个燃料针的空间分布的一种方式,从而确定潜在的转用。构建对PGET测量的分析和解释取决于能否获得综合数据集。实验数据昂贵、有限,因此通过蒙特卡洛模拟而得到补充。蒙特卡洛模拟的主要问题是模拟360度透视透视透视透视的计算成本高。类似的挑战渗透到数字科学中。为了应对这一挑战,我们开发了一个物理觉知的降低定序模型方法。它提供了一个框架,将360度角观的一小部分与计算成本低的代用法解决方案结合起来,带来物理学的精髓,在所有角观上获得实时的高不易变性解决方案,但计算成本的一小部分。</s>