Advanced methodologies for airborne radiometric surveying of nuclear sites

核场地机载辐射测量的先进方法

• 批准号: 2764922
• 金额: --
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2764922
• 关键词: Advanced; methodologies; airborne; radiometric; surveying

the event of a nuclear incident it is highly desirable to get precise positional information on radiation spread, magnitude and type as quickly as possible. The use of UAV (drones) to provide this response capability is considered preferable over manned aircraft but yet to become a fully mature technology. This exciting hands-on experimental PhD, also involving advanced data processing, programming and modelling will seek to optimise the detection systems, data collection methodologies and processing algorithms to enhance the accuracy and sensitivity of UAV systems for detecting and localising both anthropogenic and natural radiation sources. The project will utilise the extensive resources of the National Nuclear User Facility for Hot Robotics at the 245-acre Fenswood Farm facility outside Bristol. The student will utilise both multirotor and fixed wing VTOL systems to conduct their research, with annual deployment opportunities in the Chornobyl exclusion zone and other 'interest' countries.

在核事故发生时，非常需要尽快获得有关辐射传播、级别和类型的准确位置信息。使用无人机(无人机)提供这种反应能力被认为比载人飞机更可取，但尚未成为一项完全成熟的技术。这一激动人心的动手实验博士学位也涉及先进的数据处理、编程和建模，将寻求优化探测系统、数据收集方法和处理算法，以提高无人机系统探测和定位人为和自然放射源的准确性和灵敏度。该项目将利用布里斯托尔郊外占地245英亩的芬斯伍德农场设施的国家核用户设施的广泛资源。学生将利用多旋翼和固定翼垂直起降系统进行研究，每年有机会在Chornobyl隔离区和其他感兴趣的国家部署。