Bridging the gap in environmental gamma ray spectrometry [ENVIRONMENT]

缩小环境伽马射线光谱测定的差距 [环境]

• 批准号: NE/I018956/1
• 负责人: Andrew Tyler
• 金额: $ 8.74万
• 依托单位: University of Stirling
• 依托单位国家: 英国
• 项目类别: Training Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI018956%2F1
• 关键词: Bridging; gap; environmental; gamma; ray

In-situ and mobile gamma spectrometry systems are important tools for measuring environmental radioactivity, characterising contaminated land and detecting radioactive particles. Key limitations remain: for example in calibration and spectral interrogation. Application has been limited by poor spectral resolution of scintillation technology (NaI(Tl), BGO) and the high acquisition and running costs of bulky and fragile semi-conductor technology (HPGe). Moreover, the accuracy of measurement and detection capability are compromised by issues of source burial. Solutions to this problem have become the 'Holy Grail' of environmental gamma ray spectrometry (Tyler, 2007). The forward scattering of gamma photons about the full energy peak has been successfully implemented by the PI Tyler in a number of environments to quantify the depth distribution of 137Cs and 40K (Tyler et al., 1996; Tyler, 1999; Tyler et al., 2001; Tyler 2004). For radionuclides and decay series, which emit energetically different gamma photon peaks, the two line method has also proven successful, especially for U, Th and 226Ra contaminated land (Tyler, 2007). The recent emergence of large LaBr3(Ce) and LaCl3 crystals demonstrates the exciting potential of developing detectors with substantially higher spectral resolution (<3% at 662 keV) and greater detection efficiency per unit volume compared with NaI(Tl) technology, without the issues that compromise the utility of HPGe detectors. The higher detector density and photoelectric cross section significantly reduces the background Compton continuum thus permitting the detection of more complex spectra, which when coupled with a thin Be or C window, will facilitate superior detection capability for low energy gamma photon emissions (e.g. 241Am, 234Th). As a result, simpler spectral processing and improved detection limits enables shorter acquisition times and the opportunity to focus on more intelligent data processing for radionuclide and site (3 dimensional) characterisation. Techniques to reduce the noise introduced by shorter integration times are being developed (Tyler, 2007), similar to noise reduction techniques such as the minimum noise fraction transformations used in image analysis (Tyler et al., 2006: Rainey et al., 2003). These post-processing techniques can be very powerful in yielding subtle spectral changes that correlate with real physical/contaminant change. The implementation of computational intelligence type classification of gamma spectral information provides the opportunity for more powerful real time processing with shorter integration times by using primary and scattered secondary gamma photon information. Training these techniques from measurements with new detector technology at pre-characterised sites and using Monte Carlo simulations will yield more efficient and higher accuracy data extraction than is currently achievable. This forms the hypothesis of this PhD proposal. Following a literature review and training in gamma spectrometry, the student will derive the project design, including the choice of detector technology. The student will determine the detector's radiometric response characteristics and its stability across a range of climatic conditions within controlled climate chambers at Stirling. These data will be used in the detector setup, deployment and software development. Following training in MCNPX Monte Carlo Code (Los Alamos National Laboratory; London Oct. 2011), simulations of detector response will be developed and validated through laboratory work and more complex characterisation of the environment radiation field. A database of simulated and real spectra will be built to support the development of real time high accuracy radiological survey and 3D mapping of site contamination. The student will trial and validate the system alongside existing projects: particle contamination of beaches (Nuvia Limited); site contamination by Stirling with SEPA and the EA.

原位和移动伽马能谱系统是测量环境放射性、表征受污染土地和检测放射性颗粒的重要工具。关键的限制仍然存在：例如在校准和光谱询问方面。由于闪烁技术（NaI(Tl)， BGO）的光谱分辨率较差，以及笨重易碎的半导体技术（HPGe）的高获取和运行成本，限制了其应用。此外，测量精度和探测能力受到源埋藏问题的影响。这个问题的解决方案已经成为环境伽马射线能谱的“圣杯”（Tyler, 2007）。PI Tyler已经成功地在多个环境中实现了全能量峰附近伽马光子的前向散射，以量化137Cs和40K的深度分布（Tyler et al., 1996; Tyler, 1999; Tyler et al., 2001; Tyler 2004）。对于发射能量不同的伽马光子峰的放射性核素和衰变序列，两条线方法也被证明是成功的，特别是对于U， Th和226Ra污染的土地（Tyler, 2007）。最近出现的大型LaBr3（Ce）和LaCl3晶体表明，与NaI（Tl）技术相比，开发具有更高光谱分辨率（在662 keV下<3%）和更高单位体积检测效率的探测器具有令人兴奋的潜力，而不会影响HPGe探测器的效用。较高的探测器密度和光电截面显著降低了背景康普顿连续谱，从而允许检测更复杂的光谱，当与薄Be或C窗口相结合时，将促进对低能伽马光子发射（例如241Am， 234）的卓越检测能力。因此，更简单的光谱处理和改进的检测极限可以缩短采集时间，并有机会专注于更智能的数据处理，以进行放射性核素和现场（三维）表征。通过缩短积分时间来降低噪声的技术正在开发中（Tyler, 2007），类似于图像分析中使用的最小噪声分数变换等降噪技术（Tyler等人，2006；Rainey等人，2003）。这些后处理技术在产生与真实物理/污染物变化相关的细微光谱变化方面非常强大。伽马光谱信息计算智能分类的实现，为利用主伽马光子信息和散射次伽马光子信息以更短的积分时间进行更强大的实时处理提供了机会。在预先确定的地点用新的探测器技术训练这些测量技术，并使用蒙特卡罗模拟，将产生比目前可实现的更有效和更高精度的数据提取。这就形成了本博士论文的假设。在文献回顾和伽玛能谱学培训之后，学生将推导出项目设计，包括探测器技术的选择。学生将确定探测器的辐射响应特性及其在斯特林受控气候室的一系列气候条件下的稳定性。这些数据将用于探测器的设置、部署和软件开发。在MCNPX蒙特卡洛代码培训之后（洛斯阿拉莫斯国家实验室，2011年10月，伦敦），探测器响应的模拟将通过实验室工作和更复杂的环境辐射场特征来开发和验证。将建立模拟和真实光谱数据库，以支持实时高精度辐射测量和现场污染三维制图的发展。该学生将与现有项目一起试验和验证该系统：海滩颗粒污染（Nuvia Limited）；斯特林污染的地方环保局和环保局