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Boron-lined gaseous neutron detectors are being widely used in neutron detection to replace 3He proportional counters, and the boron film’s parameters comprise the key factors influencing the performance of such detectors. However, the method of characterizing boron film is relatively simple at present. In this study, boron films stuck to ultrathin glass substrate with different mass proportions of epoxy to natural boron (MPENBs) were prepared. A variety of characterization methods, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, white-light interferometry, and multiple tape tests, were used to test the boron films simultaneously, and the test results are discussed herein. Moreover, neutron imaging was conducted to analyze the uniformity of boron-10 atoms. These characterization results demonstrate that the optimized MPENB formulation is 0.16 with the boron atomic ratio of chemical elements (ARCE) at approximately 68.8% and surface roughness Sa = 1.457 μm and that the structure of boron film is uniform and fluffy, contributing to improving the boron-lined method.

Segmented Gamma Scanning (SGS) is a kind of nondestructive testing (NDT) techniques, widely used in online detection for nuclear waste drums to record the types and contents of radionuclides in the nuclear wastes. It is convenient to classify and dispose of nuclear waste according to the test results, and it also avoids radiation damage to inspectors from the destructive analysis. A new software of the radioactive analysis and monitoring system for nuclear waste barrels with SGS was developed in this work, which is mainly composed of two parts including control upper computer software and radionuclide analysis software, in which control software contained motion control and Multi-channel Analyzer (MCA) control. The controlling of the mechanical platform realized the rotation of the waste drums and the synchronous lifting and lowering of the transmission source and the detector, so as to facilitate the layered scanning of the drums. The motion control is an indispensable part of the detection system, whose precision of the movement is directly affected the accuracy of the detection results. In the radioactive measurement, a high purity germanium (HPGe) gamma-ray spectrometer was used to obtain the gamma-ray spectrum, in which the MCA was responsible for the control of spectrometer and gamma-ray spectrum data record. Therefore, the MCA control part must adjust the high voltage of the HPGe and the parameters of measurement. The gamma-ray spectrum contained the radioactive information of the nuclear wastes in the drums. The analysis of the radioactive data is the core of the software, including spectrum data resolving and the radioactive reconstructed of the radionuclides in the drums. Finally, the information such as the type and activity of the radionuclides in the barrels was provided to the user. The software was written with the C# programming language, which realized the accurate control and operation of the mechanical device and the orderly performed of motion detection. To establish communication, the software used Ethernet’s TCP/IP as the control network, in which the manual mode and auto mode were alternatives. In conclusion, the software promotes the coordination and integration of motion control, MCA control and gamma-ray spectrum data analysis in the process of automatic detection of barreled nuclear waste with SGS.

Rock burst early warning technology is currently applied mainly in microseismic monitoring. Rock burst signals indicate the micro-fracture phenomena of a rock and can transmit earthquake waves through the rock before they are finally received by a detector. A characteristic decomposition of rock micro-fracture signals was conducted by the singular value Empirical Mode Decomposition (EMD) algorithm to effectively decompose the characteristic signals of a rock micro-fracture from mixed microseismic signals, with a low signal to noise ratio to ensure prediction precision. When comparing the proposed method with wavelet decomposition and EMD, it was found that the local characteristics of the signals were retained effectively. The proposed algorithm was verified by applying it in a laboratory simulation and to the decomposition of microseismic signals from a hydro-power station. It was concluded that the improved algorithm had a better decomposition precision than wavelet decomposition and EMD decomposition and could effectively separate the characteristic signals of micro-earthquakes. This could provide a significant basis for the identification of the abnormal microseismic signals of rock micro-fractures as well as a pre-warning of rock fractures. It is therefore of practical significance to study rock fracture early warning technology.

As one of the most advanced non-destructive analytical techniques for nuclear wastes, tomographic Gamma Scanning (TGS) is able to give accurate quantitative and qualitative measurements of nuclear waste barrels. OSEM (Ordered Subsets Expectation Maximization) has been used in transmission TGS image reconstruction on account of its good reconstruction quality and ideal convergence rate. In this paper, an improved method—NMO-OSEM (Non-minimization optimization OSEM) was proposed, it's an iterative algorithm with corrected initial values optimized by non-minimization optimization method. To evaluate its performance, a TGS system is used to perform transmission measurements on barreled nuclear wastes. The results show: ①Compared with the reconstructed images by traditional OSEM under 6 transmission energies (122 keV, 344 keV, 779 keV, 964 keV, 1112 keV, 1408 keV), the improved NMO-OSEM has a great advantage in reducing the artifacts and effectively improving the quality of the reconstructed images. ②the attenuation coefficients values of 72 voxels under 3 emission energies (662 keV, 1173 keV and 1332 keV) reconstructed by the proposed algorithm are more accurate (range of error: 0.22%–13.83%) than reconstructed by traditional OSEM (range of error: 1.31%–32.21%), which proves this method has more stable reconstruction precision and could be regarded as an ideal option for real applications.

A self-adaptive differential evolution neutron spectrum unfolding algorithm (SDENUA) was established in this paper to unfold the neutron spectra obtained from a Water-pumping-injection Multi-layered concentric sphere Neutron Spectrometer (WMNS). Specifically, the neutron fluence bounds were estimated to accelerate the algorithm convergence, the minimum error between the optimal solution and the input neutron counts with relative uncertainties was limited to 10-6 to avoid useless calculation. Furthermore, the crossover probability and scaling factor were controlled self-adaptively. FLUKA Monte Carlo was used to simulate the readings of the WMNS under (1) a spectrum of Cf-252 and (2) its spectrum after being moderated, (3) a spectrum used for BNCT, and (4) a reactor spectrum, and the measured neutron counts unfolded by using the SDENUA. The uncertainties of the measured neutron count and the response matrix are considered in the SDENUA, which does not require complex parameter tuning and the priori default spectrum. Results indicate that the solutions of the SDENUA are more in agreement with the IAEA spectra than that of the MAXED and GRAVEL in UMG 3.1, and the errors of the final results calculated by SDENUA are under 12%. The established SDENUA has potential applications for unfolding spectra from the WMNS.

Valid interpretations require precise and accurate determination of magnetotelluric impedance. Although remote reference magnetotellurics has been extensively investigated, majority of these studies have focused on the non-correlation between noise and signal or between the noise in the base station and that in the reference station. Few works have explored the correlation between magnetic signals in the base station and in the reference station. This study analyzes the effects of remote reference magnetotellurics on the sounding curve under different noise intensities in the base station. Results showed that regular remote reference magnetotellurics induce a limited quality-improving effect on the sounding curve and fail to satisfy the further data processing requirements at a low signal-to-noise ratio (SNR), suggesting that regular remote reference magnetotelluric methods cannot obtain an accurate transfer function under a low SNR for a time series. Comparison of various magnetic field data revealed that a strong correlation exists among magnetic signals 60 km apart at the Longmenshan area. Thus, the remote reference magnetotelluric method based on the magnetic field correlation between the base and reference stations is proposed to screen the power spectrum and undo the noise. The effectiveness and correctness of the proposed method are validated by the results of the theoretical and field data processing and of the intermediate data analysis, further proving that the remote reference magnetotelluric method based on magnetic field correlation is superior to the regular remote reference magnetotelluric method.

To control a multi-joints bipedal robot, it is necessary to choose a proper law of control that ensures the safe and stable motions of the robot. Even for the simplest postures, such as sitting and stand- ing, there are constraints to respect so that the inverse geometric model (MGI) would not have in nitive solutions. In this paper, a particular task of sitting-to-standing is simulated for a bipedal robot using MATLAB. The articulation evolution and the variation of the shoulder position are evaluated using typical control and hierarchical redundant control in which the cases of with and without constraints are both considered. The simulation results show that the hierarchi- cal redundant control has a better effect than the typical one, and when considering the constraints, the articulations' angular velocities vary more smoothly so that the motor is better protected.

For the need of improving the capacity of the geohazards monitoring, a professional monitoring system has been developed based on the Internet of things, WSN (Wireless Sensor Network) and network communication technology. The system consists of wireless sensing network, transmission network and data monitoring and analysis center. The WSN technology was used to organize network with displacement, tilt angle and rainfall in the wireless sensing network which could achieve perception and control all aspects of the monitoring area. The monitoring data can be transferred in two methods by the transmission network which was established based on the GSM and Beidou. The wireless sensing nodes can be controlled remotely by data monitoring and analysis center. For example, the acquisition interval can be modified remotely, the current data can be controlled to return immediately and sensing nodes can be controlled to entry into low power mode in order to save power, which means that Machine to Machine mode of geological disaster monitoring had been realized in the system.

Vast quantities of low-level solid nuclear wastes are produced in the operation and decommissioning of nuclear facilities. These radioactive nuclear wastes are usually contained in special drums. Consequently, these nuclear waste drums must be tested, classified and their levels measured before they are placed in a final repository. There are certain dangers during the detection process; there is an urgent need for a safe, efficient, and autonomous system to inspect these nuclear waste drums. This study describes the methods involved in scanning and measuring the vertical section of radioactive waste drums and describes using the programmable logic controller (PLC-SIEMENS S7-1200) in order to construct an automated system as well as a detection system. According to the waste drum test flow, we designed a control program that utilizes the STEP7 Software as well as a monitoring program using SIEMENS WinCC that is flexible within the computer's central monitoring system. In the future, this system may be applied beyond the scale of a laboratory; nuclear enterprises may be able to adopt this process for sampling checks on contaminated waste. This study ensures the detection efficiency of waste drums as well as the safety of their operators. Furthermore, the proposed system effectively promotes the disposal and management of radioactive waste, which has potential applications in engineering.

According to the statistical properties of the nuclear signal pulse on the amplitude and time, a random pulse generator for simulating nuclear radiation signals is designed in this paper. The noise of the ADC acquisition circuit is used to obtain two-way seeds of random number. The obtained seeds of random number are processed by linear feedback shift register (LFSR) to generate high-speed and uniformly distributed random number continuously, then random numbers of Gaussian distribution are produced based on lookup table method and random numbers of exponential distribution are produced by setting the threshold value. Random numbers of Gaussian distribution are sent to the D/A converter to convert digital signal to analog signal, and random numbers of exponential distribution are sent to control time interval between two pulse signals. Eventually the random pulse that follows the gauss distribution on the amplitude and the exponential distribution on the time interval between two adjacent pulse signals is shaped by pulse shaped circuit. The practical test results show that the random pulse follows the gauss distribution on the amplitude and the exponential distribution on the time interval between two adjacent pulse signals, meeting statistical regularity of nuclear signal.

A parallel algorithm for terrain generation based on CUDA architecture is proposed in this paper, which aims to address the problems of high computational load and low efficiency when generating large scale terrains using the Perlin noise superposition method. The Perlin noise superposition method is combined with independent calculation of each point based on the characteristics of all adjacent points. The Perlin noise value of each terrain grid point is transferred to a GPU thread for calculation, so that the terrain generation process is executed in completely parallel in the GPU. Experimental results show that The GPU algorithm generates a grid of size 25000000 (25 million grid points) needs only 0.6355 s, while the original CPU algorithm takes 23.3723 s, so, the parallel processing algorithm can improve the efficiency of the terrain generation and meet the requirements for large-scale terrain generation compared with the original algorithm.

There is a key research issue to accurately select out neutron signals and discriminate gamma signals from a mixed radiation field in the neutron detection. This paper proposes a fractal spectrum discrimination approach by means of different spectrum characteristics of neutron and gamma. Figure of merit and average discriminant error ratio are adopted together to evaluate the discriminant effects. Different neutron and gamma signals with various noises and pulse pile-ups are simulated according to real data in the literature. The proposed approach is compared with the digital charge integration and pulse gradient methods. It is found that the fractal approach exhibits the best discriminant performance among three methods. The fractal spectrum approach is not sensitive to the high frequency noises and pulse pile-ups. It means that the proposed approach takes the advantages of anti-noises and high discriminant ability, and can be used to better discriminate neutron and gamma in neutron detection., Comment: 10 pages, 8 figures, 6 tables in Chinese Physics C 2016

Mining and smelting activities are the main causes for the increasing pollution of heavy metals in soil, water body and stream sediment. An environmental geochemical investigation was carried out in and around the Panzhihua mining and smelting area to determine the extent of chemical contamination in soil and sediment. The main objective of this study was to investigate the environmental geochemistry of Ti, V, Cr, Mn, Cu, Pb, Zn and As in soil and sediment and to assess the degree of pollution in the study area. The data of heavy metal concentrations reveal that soils and sediments in the area have been slightly contaminated. Geochemical maps of Igeo of each heavy metal show that the contaminated sites are located in V-Timagnetite sloping and smelting, gangues dam. The pollution sources of the selected elements come mainly from dusts resultant from mining activities and other three-waste-effluents. The area needs to be monitored regularly for trace metal, especially heavy metal enrichment.

A total of 31 topsoil samples were systematically collected from the Panzhihua mining area including steel smelting, coal mining, urban and rural districts. A normalization procedure was adopted to establish the environmental geochemical baseline models for this area. By using the above baseline models, the regional geochemical baseline values of As, Cr, Cu, Ni, Pb and Zn were determined. On the basis of the baselines, the enrichment factors were used to analyze the mechanism of trace metal pollution in topsoil from anthropogenic sources, and the results showed that the serious trace metal pollution is caused by human activities in coal mine, iron mine, smelting factory, tailing dam and other industrial districts in the Panzhihua area.

Noise is an important factor in image quality of TGS In according to the Neighborhood Homogeneous Measurement (NHM) was proposed to process the salt-pepper noise of TGS image system which avoided the shortcomings of traditional median filtering algorithm and improved median filtering algorithm. A cross noise measurement window was designed in adaptive median filtering algorithm to adjust the domain of image pixel, which divided image pixel into noise and signal point through the calculation results of NHM. The iteration method was introduced to inhibit noise signal. The results showed that adaptive median filtering algorithm could effectively reduce the salt-pepper noise of TGS image system.

We present the design and optimization of a prompt γ-ray neutron activation analysis (PGNAA) thermal neutron output setup based on Monte Carlo simulations using MCNP5 computer code. In these simulations, the moderator materials, reflective materials, and structure of the PGNAA 252Cf neutrons of thermal neutron output setup are optimized. The simulation results reveal that the thin layer paraffin and the thick layer of heavy water moderating effect work best for the 252Cf neutron spectrum. Our new design shows a significantly improved performance of the thermal neutron flux and flux rate, that are increased by 3.02 times and 3.27 times, respectively, compared with the conventional neutron source design.

Long-range alpha detectors (LRADs) are attracting much attention in the decommissioning of nuclear facilities because of some problems in obtaining source positions on an interior surface during pipe decommissioning. By utilizing the characteristic that LRAD detects alphas by collecting air-driving ions, this article applies a method to localize the radioactive source by ions' fluid property. By obtaining the ion travel time and the airspeed distribution in the pipe, the source position can be determined. Thus this method overcomes the ion's lack of periodic characteristics. Experimental results indicate that this method can approximately localize the source inside the pipe. The calculation results are in good agreement with the experimental results.