Nuclear Fuel-debris Characterisation via Multimodal Spectroscopy and Analytics (NuFAMSA)

2011年3月11日，一场大地震伴随着15米高的海啸，导致福岛核电站发生了前所未有的事故。接下来的几天里，福岛第一核电站的反应堆发生了堆芯熔毁。自那时以来，已计划开展清除熔化燃料的复杂活动，其中一个主要挑战是核燃料碎片的定性，包括其探测、保障、这项研究汇集了来自英国和日本的研究人员和工业家组成的互补和多学科专家团队，以探索高光谱成像（HSI）的使用沿着其他传感器技术和数据融合，有效地确定核燃料碎片的特性，传统的视觉技术已经用于福岛反应堆堆芯碎片的远程视觉评估。已经提出了一些能够收集整个电磁频谱数据的光谱学方法，作为通过其各自的光谱指纹区分含燃料碎片和非裂变堆芯层裂的更强大的技术。这些包括激光诱导击穿光谱（LIBS）、拉曼、伽马射线光谱和中子分析。然而，这些技术仅限于基于点的测量，这是一个关键的限制，导致无法捕获分析场景的空间信息。跨空间位置的多个基于点的测量是可能的，但代价是非常耗时、在小区域内并且具有差的空间分辨率。实际上，这些技术无法扫描空间位置，只能收集光谱数据。为了解决这个问题，本研究引入了HSI，HSI能够同时捕获待分析场景的空间和光谱内容。与传统的图像不同，它捕获了光谱可见光范围内的三个通道（红，绿色和蓝色），HSI捕获了数百个通道，不仅覆盖了可见光，还覆盖了部分红外范围（通常为400- 2500 nm），超出了人眼可以看到的范围。事实上，在高光谱图像中，每个像素的内容是包含该像素捕获的材料的光谱响应或指纹的矢量阵列。因此，HSI能够获取空间位置的光谱信息，显示分析现场存在的材料的不同特征及其分布，该项目的核心思想是利用HSI技术生成空间图，在图中可将含燃料碎片与非裂变堆芯碎片区分开来，避免碎片回收期间的再次临界。根据不同的光谱指纹，还预计HSI可用于进一步识别某些废物类型，并在准确位置内自动检测这些废物。此外，HSI可以与其他传感器技术相结合，其中HSI可以用作预筛选工具，以指导LIBS、伽马射线能谱中子分析的基于点的采集。我们预计，拟议的研究将导致新的和非常有价值的检查技术，可以支持在日本，英国和世界各地的核退役。

On 11th March 2011, a major Earthquake followed by a 15-metre tsunami caused an unprecedented accident in the Fukushima nuclear power plant. Fukushima Dai-ichi reactors suffered core meltdowns in the following days. Since then, complex activities for the removal of the melted fuel have been planned, where one of the main challenges is the characterisation of nuclear fuel-debris, including its detection, safeguard, retrieval and disposal.This research brings together a complementary and multidisciplinary expert team of researchers and industrialists from the UK and Japan to explore the use of hyperspectral imaging (HSI) along with other sensor technologies and data fusion for the effective characterisation of nuclear fuel-debris.Conventional visual techniques have already been used for remote visual assessment of the core debris in the reactors at Fukushima. Some spectroscopy approaches, able to collect data across the electromagnetic spectrum have already been proposed as more powerful techniques to distinguish fuel-containing debris from non-fissile core spall via their respective spectral fingerprints. These include Laser Induced Breakdown Spectroscopy (LIBS), Raman, gamma-ray spectroscopy, and neutron assay. However, these techniques are limited to point-based measurements, a key limitation leading to no spatial information of the scene under analysis being captured. Multiple point-based measurements across a spatial location are possible, but at the cost of being extremely time-consuming, within small areas, and with a poor spatial resolution. In practical terms, these techniques are unable to scan a spatial location, and only spectral data can be collected. To address this limitation, HSI is introduced in this research.HSI is able to simultaneously capture the spatial and spectral content of a given scene under analysis. Unlike conventional images, which capture three channels (Red, Green and Blue) in the visible range of the spectrum, HSI captures hundreds of channels covering not only the visible but part of the infrared range (normally 400-2500nm), going beyond what the human eye can see. In fact, in a hyperspectral image, the content of each pixel is a vector array containing the spectral response or fingerprint of the material captured by that pixel. Therefore, HSI is able to capture spectral information across a spatial location, exposing the different fingerprints of the materials present in the scene under analysis, and their distribution.The core idea of this project is to use HSI technology to generate spatial maps in which fuel-containing debris can be distinguished from non-fissile core spall, avoiding re-criticality during debris retrievals. Based on the different spectral fingerprints, it is also expected that HSI can be used to further characterise certain waste types and automatically detect them within an accurate location. Moreover, HSI can be combined with other sensor technologies, where HSI can be used as a pre-screening tool to direct the point-based acquisition of LIBS, gamma-ray spectroscopy neutron assay. We anticipate that the proposed research will lead to new and highly valuable inspection technology which can support nuclear decommissioning in Japan, the UK and around the world.