A novel method for gamma spectrum analysis of low-level and intermediate-level radioactive waste

The uncertainty of nuclide libraries in the analysis of the gamma spectra of low-and intermediate-level radioactive waste(LILW)using existing methods produces unstable results.To address this problem,a novel spectral analysis method is proposed in this study.In this method,overlapping peaks are located using a continuous wavelet transform.An improved quadratic convolution method is proposed to calculate the widths of the peaks and establish a fourth-order filter model to estimate the Compton edge baseline with the overlapping peaks.Combined with the adaptive sensitive nonlinear iterative peak,this method can effectively subtracts the background.Finally,a function describing the peak shape as a filter is used to deconvolve the energy spectrum to achieve accurate qualitative and quantitative analyses of the nuclide without the aid of a nuclide library.Gamma spectrum acquisition experiments for standard point sources of Cs-137 and Eu-152,a segmented gamma scanning experiment for a 200 L standard drum,and a Monte Carlo simulation experiment for triple overlapping peaks using the closest energy of three typical LILW nuclides(Sb-125,Sb-124,and Cs-134)are conducted.The results of the experiments indicate that(1)the novel method and gamma vision(GV)with an accurate nuclide library have the same spectral analysis capability,and the peak area calculation error is less than 4%;(2)compared with the GV,the analysis results of the novel method are more stable;(3)the novel method can be applied to the activity measurement of LILW,and the error of the activity reconstruction at the equivalent radius is 2.4%;and(4)The proposed novel method can quantitatively analyze all nuclides in LILW without a nuclide library.This novel method can improve the accuracy and precision of LILW measurements,provide key technical support for the reasonable disposal of LILW,and ensure the safety of humans and the environment.

Quantitative algorithm for airborne gamma spectrum of large sample based on improved shuffled frog leaping-particle swarm optimization convolutional neural network

In airborne gamma ray spectrum processing,different analysis methods,technical requirements,analysis models,and calculation methods need to be established.To meet the engineering practice requirements of airborne gamma-ray measurements and improve computational efficiency,an improved shuffled frog leaping algorithm-particle swarm optimization convolutional neural network(SFLA-PSO CNN)for large-sample quantitative analysis of airborne gamma-ray spectra is proposed herein.This method was used to train the weight of the neural network,optimize the structure of the network,delete redundant connections,and enable the neural network to acquire the capability of quantitative spectrum processing.In full-spectrum data processing,this method can perform the functions of energy spectrum peak searching and peak area calculations.After network training,the mean SNR and RMSE of the spectral lines were 31.27 and 2.75,respectively,satisfying the demand for noise reduction.To test the processing ability of the algorithm in large samples of airborne gamma spectra,this study considered the measured data from the Saihangaobi survey area as an example to conduct data spectral analysis.The results show that calculation of the single-peak area takes only 0.13~0.15 ms,and the average relative errors of the peak area in the U,Th,and K spectra are 3.11,9.50,and 6.18%,indicating the high processing efficiency and accuracy of this algorithm.The performance of the model can be further improved by optimizing related parameters,but it can already meet the requirements of practical engineering measurement.This study provides a new idea for the full-spectrum processing of airborne gamma rays.

Design of Gamma Spectrum Data Acquisition and Processing System Based on ARM / DSP

Research for detecting or obtaining radionuclide by gamma energy spectrum data acquisition and process system is one of the key issues about intelligent measurement of gamma-ray spectrum. For this reason, a software and hardware implementation schematic design based on ARM ( Advanced RISC Machines) + DSP ( Digital Signal Processor) architecture for gamma energy spectrum data acquisition and processing system is proposed. The paper discusses in detail some key technologies such as communication interface design between microcontroller ARM and digital signal processor DSP,distribution scheduling under multi-task in the ARM-Linux,DSP handling procedures for multi-channel A / D high-speed sample. At the same time,because the traditional Gaussian fitting to determine the boundary of peak is not ideal,it puts forward a weighting factor of Gaussian function least squares fitting realize boundary determined. Finally gamma-spectrum data from sodium iodide NaI( TI) scintillation detector is tested and processed in the new system. The results show that gamma energy spectrum data acquisition and process system is perfect functionality, stable and convergence in unimodal. Compared with data from conventional energy spectrometers,the system can keep better energy resolution in a wide range of pulse pass rate.

Identification of the unknown shielding parameters with gammaray spectrum using a derivative-free inverse radiation transport model

Identifying the unknown geometric and material information of a multi-shield object by analyzing the radiation signature measurements is always an important problem in national and global security. In order to identify the unknown shielding layer thicknesses of a source/shield system with gamma-ray spectra, we have developed a derivative-free inverse radiation transport model based on a differential evolution algorithm with global and local neighbourhoods(IRT-DEGL). In the present paper, the IRT-DEGL model is further extended for estimating the unknown thicknesses with random initial guesses and material mass densities of multi-shielding layers as well as their combinations. Using the detected gamma-ray spectra,the illustration of inverse studies is implemented and the main influence factors for inverse results are also analyzed.

A novel approach for feature extraction from a gamma‑ray energy spectrum based on image descriptor transferring for radionuclide identification

This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.

GEANT4 simulation of the characteristic gamma-ray spectrum of TNT under soil induced by DT neutrons

The characteristic gamma-ray spectrum of TNT in the soil induced by DT neutrons is measured by the PFTNA demining system. The GEANT4 toolkit is used to simulate the whole experimental procedure. The simulated spectra are compared with the experimental spectra, and they are mainly consistent. The share of the background sources such as neutrons and gamma is obtained and the contribution that the experimental apparatus to the background, such as shielding, detector sleeve and moderator, is analyzed. The effective gamma signal(from soil and TNT) is 29% of the full spectrum signal, and the background signal, more than 68%, this is mainly produced by shielding and the detector sleeve. By gradually optimizing the shielding and the cadmium sheet of the detector sleeve, the share of the effective gamma signal increases to 47%, and the background signal reduces to 18%.

Extraction of full energy peak of ^(137)Cs from in situ NaI(Tl)gamma-ray spectrum

A Levenberg–Marquardt Gaussian fitting algorithm has been used for analyzing the overlap of three peaks(the 583-ke V peak of^(208)Tl, the 609-ke V peak of214 Bi, and the 662-ke V peak of^(137)Cs) using an in situ Na I(Tl) scintillation spectrometer. The algorithm, in addition,was compared with a genetic algorithm used for multiple deconvolution. The three fitted peak areas(583, 609, and662 ke V) were calculated from the measured gamma-ray spectra obtained from a simulation experiment in which a^(137) Cs source was buried at different soil depths(from 18 to38 cm). The application of the Levenberg–Marquardt algorithm yielded similar results compared to the genetic algorithm. A lack-of-fit test showed that the fitting is good when the instrumental noise levels were estimated from replicated analyses. The relative fitting error of the total net area and the residual standard deviation were within 5 %and 0.04, respectively, and the goodness of the fitting was better than 0.98. While the methods used in this paper give high performance, the results may lead to incorrect estimation when the signal-to-noise ratio is smaller than-30 d B. This study is useful for the determination of radioactive specific activity of^(137) Cs by in situ spectrometry.

烃源岩测井识别与评价方法研究进展

烃源岩测井识别与定量评价对油气资源潜力勘查、储量评估及非常规油气勘探开发至关重要。烃源岩自身岩性和成熟度等差异、测井序列对烃源岩响应灵敏程度不同以及不同方法适用性区别等导致烃源岩测井评价工作仍受到限制。目前亟需进一步挖掘地球物理测井资料中蕴含的烃源岩信息,搭建烃源岩品质与测井信息之间桥梁,并实现以自生自储为特性的非常规油气烃源岩品质测井精细表征。笔者等首先阐明烃源岩分类及其地质表征参数,并分析不同类别烃源岩在常规测井序列及成像和核磁共振等新技术测井序列上响应特征。烃源岩通常表现为“四高一低”(高GR、高AC、高CNL、高RT和低DEN)测井响应特征。除单因素分析外,可优选交会图及构建敏感参数等实现烃源岩定性识别。而烃源岩有机碳含量(TOC)等参数测井定量预测方面则可采用ΔlgR法、修正ΔlgR法(变基线和变系数)、自然伽马能谱测井法、多元回归法、Litho Scanner测井资料法以及人工智能方法实现。在分别评述不同TOC含量测井计算方法的优缺点和适用条件的基础上,指出通过TOC结合生烃潜量等参数计算可实现烃源岩品质测井综合评价。最后解析烃源岩测井识别与评价工作中存在的问题与发展趋势,以期为油气资源评价及非常规油气勘探开发提供理论指导与技术支撑。

基于航空高光谱和伽马能谱的铀矿勘查集成软件开发与应用

航空高光谱和航空伽马能谱是当前铀矿勘查领域两类重要的数据源,由于其异构且海量的特性,使数据的处理难度大,处理效率低,协同应用效果不足。在这种情况下开发一款面向航空高光谱和伽马能谱的铀矿勘查集成软件显得尤为重要。文章根据航空高光谱和航空伽马能谱数据的类型及处理方法,开展了针对两种数据应用的集成软件系统的设计。研究引入虚拟总线结构,实现了对不同数据处理模块的调用,并以Visual Basic为主要开发语言,对前台主系统进行搭建。最终利用搭建好的系统,以银根地区的航空高光谱和伽马能谱数据为数据源,完成软件的应用测试。测试结果发现,利用GS融合算法可以较好地保留地表纹理信息,同时丰富图像颜色,从而为铀矿赋矿围岩岩性的准确识别与划分提供参考。

铀矿勘查中航放信息提取技术应用研究

航空伽马能谱测量(简称航放测量)是一种快速有效勘查隐伏铀矿的勘探方法。相比于裸露于地表附近的铀矿体,隐伏铀矿体在地表引起的矿致异常信息相对较弱。为了提取深部铀矿在地表产生的弱异常信息,文章以相山铀矿田为例采用铀变异系数、航放参数F、铀富集系数、元素含量与面积(CA)分形4种方法,对相山铀矿田航放测量数据(1∶5万)进行成矿信息提取,运用打分综合信息定量法对相山铀矿田进行了成矿预测。预测结果显示,航放综合信息异常与已知矿体位置吻合度较高,对已知矿床判断的正确率为76.4%,为铀矿勘查中航放信息有效提取提供了技术指导,具有一定的实用价值。

某深埋输水隧洞放射性环境地质调查与评价

为探究某深埋输水隧洞穿越地层的放射性环境质量,采用原位测试和样品分析等手段,研究隧洞施工期的不利因素。结果表明:隧洞地表沿线的放射性元素含量在背景值变化范围内,未发现放射性异常现象。隧洞穿越的7个钻孔内γ总量和地温测井的结果表明:孔内核素放射性水平较低,基本处于豁免水平,但地温存在异常区域,施工期务必引起重视。钻孔目的层的岩心放射性核素活度浓度低,属于豁免范围内,孔内地下水放射性水平低,满足Ⅲ类地下水要求。辐射防护的计算结果显示,隧洞段地表沿线γ有效剂量当量为0.15 mSv/年,符合国家要求。隧洞段内照射指数和等效镭浓度符合约束值,ZK16钻孔的目的层外照射指数略高于标准值。因此,地下隧洞在施工期需着重关注洞内放射性水平,在辐射异常地段加强岩石采样与分析工作,以保证施工安全。

Standard spectrum measurement and simulation of elemental capture spectroscopy log

We have established a set of laboratory measurements which is used for capturing element gammma spectrum. Standard captured gamma ray spectra for ten elements, including Si, Ca, Fe, are obtained using the measurements for the first time in China. We also simulated the capture gamma ray spectra of the ten elements using Monte Carlo methodology with the same parameters of our experimental measurements. Comparing the experiment and simulation results with the data from the International Atomic Energy Agency＇s Nuclear Data Center, we obtained the standard captured gamma ray spectra of the ten elements, which, as calibration spectra, are used to calibrate the raw spectrum in data processing. This method solved the key problem during the conversion from the original measuring spectrum to the yield of each element in the data processing. The method can effectively improve the accuracy of the element yield calculation.

利用地面γ总量转换为空气吸收剂量率进行环境辐射水平评价——以桂阳县潘家村和永兴县土桥村实测数据为例

在长期的铀矿普查中,我国积累了海量的γ总量数据资料,但应用这些数据进行放射性环境评价的研究极少。本文从γ总量和空气吸收剂量率的测量原理出发,通过梳理γ总量、放射性核素含量与空气吸收剂量率之间的关系,建立起地面γ总量与空气吸收剂量率之间的联系,分析了仪器参数对测量误差的影响,认为γ总量仪器bK/bU=2.287、bTh/bU=0.430时,测量的γ总量与空气吸收剂量率满足严格线性关系,因此γ总量仪器的bK/bU、bTh/bU值越接近这两个数值,测得的γ总量转换为空气吸收剂量率越准确;利用湖南省电离辐射计量站模型进行了γ总量转换为空气吸收剂量率的系数求解,并分析了误差,推测了仪器参数中钾的铀当量值、钍的铀当量值的大致范围;在郴州市桂阳县潘家村岩体和郴州市永兴县土桥村灰岩地区进行了γ总量、γ能谱、空气吸收剂量率的同点位实测,结果显示,当核素含量比CK/CU均值小于1、CTh/CU均值小于3时,利用γ总量(FD3013仪器测得)估算的空气吸收剂量率与利用Beck公式根据能谱估算的空气吸收剂量率的误差基本处于同等水平,均方根误差均小于15%。根据国内核素的CK/CU、CTh/CU均值,认为国内大部分地区可以利用由FD3013仪器(或类似性能仪器)测得的γ总量数据估算空气吸收剂量率。利用已有铀矿普查资料中的γ总量数据转换计算有效空气吸收剂量率,为快速大面积评估环境天然放射性外照射水平提供了方法参考。

面向PGNAA技术的碘化钠探测器MCNP模拟计算

碘化钠(NaI)探测器因其优秀的探测效率和相对较低的成本在瞬发γ射线中子活化分析技术(prompt gamma-ray neutron activation analysis,PGNAA)中具有广泛应用。为了获取PGNAA测量过程中探测器对γ射线的响应,针对NaI探测器建立了蒙特卡罗模型,基于该模型对中子以及γ射线输运过程进行模拟计算。对^(60)Co、^(137)Cs、^(152)Eu、^(133)Ba和^(241)Am标准点源以及^(137)Cs水体源进行了测量分析,并与MCNP模拟计算进行对比,结果显示两者吻合。之后结合D-D中子发生器对水溶液进行测量,并分析H元素辐射俘获反应产生的2.223 MeV特征γ射线。研究结果表明,MCNP模拟计算的H元素特征峰计数与测量的结果偏差为13%,证明了MCNP建立的NaI测量系统模型能够实现对γ和中子混合输运过程的模拟仿真,可为后续系统优化工作的开展奠定基础。

低温对NaI(Tl)探测器的性能影响研究

本研究详细测试了在-40~20℃温度变化下,NaI(Tl)探测器对^(60)Co的能谱响应的峰位移和能量分辨率的变化,以及探测器输出脉冲信号的性能参数的变化。在从20℃下降至0℃的过程中,能谱呈现向右的漂移,随后从0℃继续下降时,表现为向左漂移。在-20~20℃的范围内,^(60)Co能谱的1.33MeV峰位偏移量较小,不超过3.2%。然而,当温度低于-20℃时,峰位明显向左移动,在-40℃时,偏移量最大,达到24.86%。与此同时,温度下降导致NaI(Tl)探测器的能谱能量分辨率变差,从20℃下降至-40℃,^(60)Co能谱的1.33MeV峰的能量分辨率从5.20%上升至8.67%。此外,输出脉冲的脉宽随温度下降呈现逐渐增加的趋势,探测器的计数率上限随着温度下降逐渐降低。最后通过采用相对峰位校正的方法,成功对低温下的温度漂移进行了校正,确保了在不同温度下γ射线特征峰位置的一致性。这些研究结果对于提升NaI(Tl)探测器在低温环境中的性能和应用具有重要意义。

豫西嵩县南部萤石矿床放射性特征及其找矿意义

中国是全球最大的萤石消费国,随着航天、半导体、通讯等领域的快速发展,萤石矿的消费量及价格呈逐年上升趋势,其稀缺性和战略重要性日益提高,近几年萤石矿的勘查和开发力度亦在加大,但现阶段萤石矿勘查主要还是利用填图、工程等手段。本研究选取了嵩县南部4个代表性强的萤石矿床,利用伽马能谱仪对不同岩性的放射性进行测量,识别萤石矿床的放射性特征,圈定放射性异常带(点),结果显示各类岩性的γ射线辐射强度值为5.54~68.54μR/h,U、Th、K和总量Tc含量分别为3.1×10^(-6)~30.1×10^(-6)、12.1×10^(-6)~90.1×10^(-6)、0.1%~8.7%、13.0×10^(-6)~99.3×10^(-6)。研究认为,不同岩性以及不同类型萤石矿石之间的放射性特征存在规律性,其放射性异常带(点)和萤石矿的位置一致性较好,萤石矿体的放射强度较围岩均表现为低值异常的特征,其中Th元素的异常表现最具稳定性。因此,通过测量不同岩性的放射性差异,可有效地指示萤石矿体位置等信息,为萤石矿找矿勘查提供新的工作思路和方法。

放射性同位素分离在线检测软件设计与实现

核素分离是放射性同位素制备的关键技术之一,其中快速准确地判断目标核素的分离情况对同位素分离十分重要。本研究针对放射性同位素分离典型过程,基于闪烁体探测器设计和开发了一款放射性同位素分离在线检测软件,用于测量分离过程中管路内流动的放射性情况,包括计数率、放射性核素组成。测量信号传输至分离装置控制系统,进行分析、处理、显示。核素判别中利用序贯贝叶斯核素识别算法,并基于遗传算法优化卡尔曼滤波器,实现更优的参数估计,准确快速地判别混合物中特定放射性核素,提高核素分离过程的效率和准确性。该软件基于串口通信实现设备与系统之间的数据传输,实现了数据采集、实时测量、可视化显示、γ能谱绘制、γ能谱分析、系统设置、流程控制、核素识别等功能,软件界面简洁,经实验测试,运行稳定,人机交互友好,具有较好的实用性和可维护性,可为放射性同位素分离制备在线检测提供技术参考。

应用自然伽马能谱法恢复碳酸盐岩沉积时的古水深——以山西兴县关家崖马五5亚段为例

古水深分析对还原古环境与盆地构造演化历史具有重要的意义。目前古水深恢复多以定性为主,对样品可靠性的要求较高,且易受资料条件限制,而自然伽马能谱法具有易获取、成本低、受控因素少等优点,可结合水深函数半定量恢复水深,但该方法多被用于陆相碎屑岩的研究中,是否适用于海相碳酸盐岩尚需验证。以鄂尔多斯盆地关家崖剖面奥陶系马家沟组五5亚段为例,利用自然伽玛能谱法恢复了碳酸盐岩沉积时的古水深,恢复结果与碳同位素法、生物遗迹法、岩石组构法显示的结果一致。研究验证了自然伽马能谱法在恢复碳酸盐岩沉积时的古水深方面具有较高的可信度与实用性。

低计数特征的自然伽马能谱测井数据滤波方法研究

岩石天然放射性强度较弱,自然伽马能谱测井所测得的能谱计数较低,低计数特征使得地层衰变随机误差影响被放大,造成测量能谱质量差、测井曲线统计噪声大的情况。该文通过对比多种能谱滤波结果,使单深度点能谱最大程度还原准确能谱信息;利用曲线形态,针对求解的U、Th、K含量曲线进行深度域的滤波处理,综合从高噪声、低计数的数据中准确提取地层信息;利用中国石油集团测井有限公司的过钻具自然伽马能谱仪器的实测数据验证该方法的有效性。结果表明:对于计数低、谱形差的自然伽马能谱,高斯滤波、卷积滤波效果相对较好,该文提出结合这2种方法的复合滤波可以准确地还原出高保真的能谱形状;深度域的滤波,卡尔曼滤波相对自适应滤波方法有一定优势;依次经过能谱滤波和深度滤波后,结果的准确性和重复性有了大幅提升。该文所介绍的针对低计数特征的自然伽马能谱测井滤波方法,可以有效提高U、Th、K的测量精度。

岩心数字化技术研究与应用

岩心是油气田勘探开发的核心战略资源之一,在油气藏岩相、储层物性、含油性的研究中发挥着重要作用。与纸质资料相比,岩心实物地质资料具有缩减性和可变性的特点,岩心“原貌”不可能长久保存,从而降低了岩心的使用价值。岩心数字化技术可以及时采集岩心各项原始数据,丰富岩心地质信息,提升岩心资料利用率,因此开展岩心数字化技术研究具有重要意义。根据胜利油田岩心数字化建设的生产实践,对岩心数字化的概念、设备和技术内容进行了阐述,分析了岩心伽马能谱测量、XRF元素测试、磁化率测试、CT扫描等多种重要的岩心数字化技术,并探讨了各项技术的地质应用效果。研究结果表明,岩心数字化技术具有测试快、连续性好、数据多、精度高等优势,可以精细反映沉积物的变化特征,能为泥页岩、碳酸盐岩和砂砾岩等地层的沉积成因、储层描述及评价、物质组成等问题的研究提供重要的地质依据,具有较为广阔的应用前景。岩心数字化资料是基于岩心直接获得的岩心尺度的连续性资料,从资料性质上来看介于原始资料和成果资料之间,更侧重于岩心的“原始性”,是第一手的地质资料。岩心数字化资料具有独特而重要的应用价值,是提高岩心应用水平的重要技术手段。