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.

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.

Analysis of the elemental spectral characteristics of single elemental capture spectrum log using Monte-Carlo simulation

In this study,the gamma-ray spectrum of single elemental capture spectrum log was simulated.By numerical simulation we obtain a single-element neutron capture gamma spectrum.The neutron and photon transportable processes were simulated using the Monte Carlo N-Particle Transport Code System(MCNP),where an Am–Be neutron source generated the neutrons and thermal neutron capture reactions with the stratigraphic elements.The characteristic gamma rays and the standard gamma spectra were recorded,from analyzing of the characteristic spectra analysis we obtain the ten elements in the stratum,such as Si,Ca,Fe,S,Ti,Al,K,Na,Cl,and Ba.Comparing with single elemental capture gamma spectrum of Schlumberger,the simulated characteristic peak and the spectral change results are in good agreement with Schlumberger.The characteristic peak positions observed also consistent with the data obtained from the National Nuclear Data Center of the International Atomic Energy Agency.The neutron gamma spectrum results calculated using this simple method have practical applications.They also serve as an reference for data processing using other types of element logging tools.

Gaussian fitting in gamma-ray spectral decomposition

In order to extract the information of 662-keV 137Cs spectra from the overlapping peaks with 583-keV 208Tl,609-keV 214Bi,the overlapping peaks are measured by in-situ γ-ray spectrometer using a NaI(Tl) detector.The spectral model is optimized by the Gaussian fitting algorithm,and the optimized fitting indexes for fitting/original value are from 0.96 to 0.99.Gaussian fitting verified by experiment is feasible for γ-ray spectrum analysis.The full energy peak of 137Cs is extracted correctly from the overlapping peaks,it is important for in-situ γ-ray spectrometer to estimate contamination of 137Cs in radiated environment and nuclear accident.

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。

Implicit FWHM calibration for gamma-ray spectra

FWHM calibration is one of the essential procedures in gamma-ray spectra analysis.Traditional method is time consumption and poor flexibility because of extra measurement on calibration source.This paper introduces an implicit calibration method based on symmetric zero-area conversion.The single peaks can be differentiated from doublets.Meanwhile,the extracted FWHM values can be applied in the fitting process.Various forms of calibration equations are introduced and compared with practical spectrum data under this method.

Study on element detection and its correction in iron ore concentrate based on a prompt gamma-neutron activation analysis system

A prompt gamma-neutron activation analysis(PGNAA) system was developed to detect the iron content of iron ore concentrate. Because of the self-absorption effect of gamma-rays and neutrons, and the interference of chlorine in the neutron field, the linear relationship between the iron analytical coefficient and total iron content was poor, increasing the error in the quantitative analysis. To solve this problem, gamma-ray self-absorption compensation and a neutron field correction algorithm were proposed, and the experimental results have been corrected using this algorithm. The results show that the linear relationship between the iron analytical coefficient and total iron content was considerably improved after the correction. The linear correlation coefficients reached 0.99 or more.

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。

Gamma调试系统在液晶电视上的应用

由于人眼对于亮暗的感知有差异,同时显示器在信号输出和输入也不是纯线性关系,加上机芯信号处理影响及液晶电视背光个体差异,导致各灰度图像的色温差异。为了矫正这些差异带来的影响,提升亮暗和色温的显示效果,Gamma调试系统在液晶电视中的开发和应用显得尤为关键。Gamma调试系统会根据人眼感知、机芯特点和显示屏幕特性来矫正色温和亮度曲线。通过对Gamma曲线的研究和应用最大限度降低亮度损失,优化亮度曲线,调节0~255阶各灰阶的色温和色坐标,提高各灰度图像的色温达到一致,同时能满足不同场景的色温需要,对提升能效也有大有益处。

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。

2022年IAEA国际比对γ谱分析结果及思考

对2022年国际原子能机构(IAEA)国际比对测试中的γ谱分析进行总结,为以后的检测和比对组织工作提供参考。使用高纯锗γ谱仪,采用相对比较法,对3种不同水样中的^(60)Co、^(134)Cs、^(137)Cs、^(210)Pb、^(241)Am的活度浓度进行了检测。各核素检测结果与目标值的相对偏差范围为-15.25%~8.95%,可接受率100%,对于传统上采用放化方法测量的^(210)Pb,本次使用γ谱测量,与目标值的相对偏差为8.95%。对于质控样中给出的核素,采用相对比较法得到的结果相对偏差较小,由比对组织者提供统一的质控样可有效减小比对结果中由标准品溯源带来的误差。

Possible Therapeutic Use of Bumetanide in the Treatment of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder. Autism Spectrum Disorder is diagnosed early on in a child’s life, anywhere from eighteen to twenty-four months. The disorder is characterized by variable degrees, by difficulties in nonverbal communication, verbal communication, social interaction, repetitive behaviors, and movement. The occurrence of ASD has been increasing globally, with the most recent prevalence studies indicating that they are present in six per one thousand children and one in every sixty-eight people of all ages, with a higher incidence among males, with a ratio of four to one. There is no specific target demographic for Autism Spectrum Disorder, nor is there a cure. Over the last few decades, there have been advancements in treating the symptoms associated with Autism Spectrum Disorder. Among the many different fields of research associated with Autism Spectrum Disorder, Bumetanide has shown to be a promising drug therapy for children suffering from Autism, treating specifically the behavioral symptoms associated with ASD. Bumetanide is forty times more potent than furosemide and is a loop diuretic mainly acting in the ascending limb of the loop of Henle. A clinical trial conducted found a decrease in the Childhood Autism Rating Scale (CARS) score, showing improvement in Autism Spectrum Disorder symptoms, such as repetitive behavior and initiating or participating in the social interaction.

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。

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。