TORONE - TOtal characterisation for Remote Observation in Nuclear Environments

TORONE - 核环境远程观测的总体表征

• 批准号: EP/P018505/1
• 负责人: Philip A Martin
• 金额: $ 163.62万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FP018505%2F1
• 关键词: TORONE; TOtal; characterisation; Remote; Observation

The future use of nuclear energy in the UK and internationally is very much dependent on the ability to characterise the various highly radioactive environments that occur in the nuclear industry for both efficient decontamination and decommissioning as well as in the design of new nuclear fission reactors as well as fusion reactors. Currently, site and material characterisation is costly and time consuming because remote methods for the environmental, chemical and geoscientific characterisation of man-made and natural materials, specifically designed for the nuclear arena, are limited. The inaccessible, complex and confined nature of these often high-radioactivity environments can preclude traditional field-based data collection techniques, which are often focused on sample collection and off-site analysis. With costs entering the tens or even hundreds of thousands of pounds for sample analysis in a particular plant, and the possibility that access is so restricted that obtaining samples may actually be impossible, remote in-situ analysis prior to segregation may offer a cheaper, safer, quicker and thus far more attractive solution. On their own, current in-situ techniques (e.g. gamma spectroscopy, 3D laser scanning, elemental composition through laser induced breakdown spectroscopy), each answer a particular characterisation question, but on their own only provide a component of the full characterisation picture that is required for instance for waste segregation. This project aims to combine such technologies into an integrated system, with each technology contributing in real-time to form a seamless jigsaw - a 'total characterisation' picture - setting characterised materials into the spatial context of the environment they are located in. Advanced robotics and control technologies will be used in a similar way to NASA's Curiosity Rover to form the flexible platform necessary for the trials in a range of nuclear environments from Sellafield in the UK to Fukushima in Japan.

英国和国际上核能的未来使用在很大程度上取决于对核工业中发生的各种高放射性环境进行有效去污和退役以及设计新的核裂变反应堆和聚变反应堆的能力。目前，场地和材料表征是昂贵和耗时的，因为专门为核竞技场设计的人造和天然材料的环境、化学和地球科学表征的远程方法是有限的。这些往往是高放射性的环境难以进入、复杂和封闭，因此无法采用传统的实地数据收集技术，这些技术往往侧重于样本收集和场外分析。由于在特定工厂中用于样品分析的成本进入数万甚至数十万英镑，并且访问受到如此限制以至于实际上可能不可能获得样品的可能性，分离之前的远程原位分析可以提供更便宜、更安全、更快并且因此更具吸引力的解决方案。目前的原位技术（例如伽马光谱法、3D激光扫描、通过激光诱导击穿光谱法的元素组成）各自回答了特定的表征问题，但其自身仅提供了例如废物分离所需的完整表征图的一部分。该项目旨在将这些技术联合收割机结合到一个集成系统中，每种技术都能实时地形成一个无缝的拼图--一个“整体表征”的图片--将表征的材料设置到它们所处环境的空间背景中。先进的机器人技术和控制技术将以类似于美国宇航局的Currency Rover的方式使用，以形成在从英国的塞拉菲尔德到日本的福岛的一系列核环境中进行试验所必需的灵活平台。

项目成果

A compact, single-detector, ?-imaging system for in-situ radiation characterisation and localisation

用于原位辐射表征和定位的紧凑型单探测器 β 成像系统

• 发表时间: 2019
• 作者: I Tsitsimpelis

Robotic Exploration of an Unknown Nuclear Environment Using Radiation Informed Autonomous Navigation

• DOI: 10.3390/robotics10020078
• 发表时间: 2021-06-01
• 期刊: ROBOTICS
• 影响因子: 3.7
• 作者: Groves, Keir;Hernandez, Emili;Lennox, Barry
• 通讯作者: Lennox, Barry

Mona: an Affordable Open-Source Mobile Robot for Education and Research

• DOI: 10.1007/s10846-018-0866-9
• 发表时间: 2019-06-01
• 期刊: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
• 影响因子: 3.3
• 作者: Arvin, Farshad;Espinosa, Jose;Lennox, Barry
• 通讯作者: Lennox, Barry

Robotic arm material characterisation using LIBS and Raman in a nuclear hot cell decommissioning environment.

• DOI: 10.1016/j.jhazmat.2021.125193
• 发表时间: 2021-01
• 期刊: Journal of hazardous materials
• 影响因子: 13.6
• 作者: P. Coffey;N. Smith;B. Lennox;Gerben Kijne;Bob A. Bowen;Adrian Davis-Johnston;P. Martin

MallARD: An Autonomous Aquatic Surface Vehicle for Inspection and Monitoring of Wet Nuclear Storage Facilities

• DOI: 10.3390/robotics8020047
• 发表时间: 2019-06
• 期刊: Robotics
• 影响因子: 3.7
• 作者: K. Groves;A. West;Konrad Gornicki;S. Watson;J. Carrasco;B. Lennox