The study of a neutron spectrum unfolding method based on particle swarm optimization combined with maximum likelihood expectation maximization

The neutron spectrum unfolding by Bonner sphere spectrometer(BSS) is considered a complex multidimensional model,which requires complex mathematical methods to solve the first kind of Fredholm integral equation. In order to solve the problem of the maximum likelihood expectation maximization(MLEM) algorithm which is easy to suffer the pitfalls of local optima and the particle swarm optimization(PSO) algorithm which is easy to get unreasonable flight direction and step length of particles, which leads to the invalid iteration and affect efficiency and accuracy, an improved PSO-MLEM algorithm, combined of PSO and MLEM algorithm, is proposed for neutron spectrum unfolding. The dynamic acceleration factor is used to balance the ability of global and local search, and improves the convergence speed and accuracy of the algorithm. Firstly, the Monte Carlo method was used to simulated the BSS to obtain the response function and count rates of BSS. In the simulation of count rate, four reference spectra from the IAEA Technical Report Series No. 403 were used as input parameters of the Monte Carlo method. The PSO-MLEM algorithm was used to unfold the neutron spectrum of the simulated data and was verified by the difference of the unfolded spectrum to the reference spectrum. Finally, the 252Cf neutron source was measured by BSS, and the PSO-MLEM algorithm was used to unfold the experimental neutron spectrum.Compared with maximum entropy deconvolution(MAXED), PSO and MLEM algorithm, the PSO-MLEM algorithm has fewer parameters and automatically adjusts the dynamic acceleration factor to solve the problem of local optima. The convergence speed of the PSO-MLEM algorithm is 1.4 times and 3.1 times that of the MLEM and PSO algorithms. Compared with PSO, MLEM and MAXED, the correlation coefficients of PSO-MLEM algorithm are increased by 33.1%, 33.5% and 1.9%, and the relative mean errors are decreased by 98.2%, 97.8% and 67.4%.

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.

Optimization method of Hadamard coding plate inγ‑ray computational ghost imaging

Owing to the constraints on the fabrication ofγ-ray coding plates with many pixels,few studies have been carried out onγ-ray computational ghost imaging.Thus,the development of coding plates with fewer pixels is essential to achieveγ-ray computational ghost imaging.Based on the regional similarity between Hadamard subcoding plates,this study presents an optimization method to reduce the number of pixels of Hadamard coding plates.First,a moving distance matrix was obtained to describe the regional similarity quantitatively.Second,based on the matrix,we used two ant colony optimization arrangement algorithms to maximize the reuse of pixels in the regional similarity area and obtain new compressed coding plates.With full sampling,these two algorithms improved the pixel utilization of the coding plate,and the compression ratio values were 54.2%and 58.9%,respectively.In addition,three undersampled sequences(the Harr,Russian dolls,and cake-cutting sequences)with different sampling rates were tested and discussed.With different sampling rates,our method reduced the number of pixels of all three sequences,especially for the Russian dolls and cake-cutting sequences.Therefore,our method can reduce the number of pixels,manufacturing cost,and difficulty of the coding plate,which is beneficial for the implementation and application ofγ-ray computational ghost imaging.

Trace element and sulfur isotope compositions of pyrite from the Tianqiao Zn–Pb–Ag deposit in Guizhou province,SW China:implication for the origin of ore-forming fluids

The Tianqiao Zn–Pb–Ag deposit in SW China,hosted by Devonian and Carboniferous limestone and clay rocks,is composed of sulfides such as sphalerite,galena,and pyrite.Pyrite is present in different paragenetic stages and can be divided into four types based on textures and mineral assemblages.Pyrite from the adjacent Shanshulin deposit(Py-SSL)is also used for comparison.Py1 shows framboid texture with grain diameter up to 1 mm and was commonly replaced by sphalerite.Py2 is characterized by overgrowth texture and displays inner oscillatory zoning.Py2 is associated with abundant sphalerite and galena.Py3 shows replacement relics textures where galena fills the fractures of pyrite.Py4 is a euhedral to subhedral crystal disseminated in dolomite and is characterized by deformation and fragmentation textures.Minor sphalerite and galena are associated with Py4.Py-SSL is subhedral and disseminated in dolomite,similar to Py4.Py1 was formed by a diagenetic or sedimentary process,whereas Py2 and Py3 were formed by multiple stages of ore fluids.Py4 and Py-SSL were formed at the carbonate-sulfide stage,but Py4 suffered from deformation after its formation.Py1,Py2,and Py3 are characterized by relative enrichment of Sb,Cu,and As,in contrast to Py4 and Py-SSL with higher Cr,W,Ge,Sn,Tl,Ni,and Ga contents.However,critical metals such as Ge,Ga,and In in pyrite are generally lower than10 ppm,which are not economically important.The trace element variation in Tianqiao pyrite with paragenesis results from fluid evolution in the Pb–Zn ore system and competition with co-precipitating minerals.Diagenetic and ore-forming hydrothermal fluids are responsible for the formation of different types of pyrite.Ore-related pyrite from the Tianqiao and Shanshulin deposits has Co and Ni distribution features similar to pyrite from sedimentary pyrite and submarine hydrothermal vents,different from those in volcanogenic massive sulfide,iron oxide-copper–gold,and porphyry Cu deposits,indicating their derivation of relatively low-temperature(<~250°C)hydrothermal fluids,similar to basin brines or seawater.,via fluid-rock interaction.This conclusion is also supported by the sulfur isotope composition of sulfides which are 13.0–13.5%,and 15.6–20.5%for Tianqiao and Shanshulin deposits,respectively.

Geochemical records of the sediments and their significance in Dongping Lake Area,the lower reach of Yellow River,North China

Dongping Lake area,located in the lower reaches of Yellow River,is an ideal place to study the changes of modern river and lake sedimentary environment.The sediment samples of Dawen River,Yellow River,and Dongping Lake were collected,and the major elements,trace elements and organic matter geochemical composition of the samples were analyzed.Cluster analysis,characteristic element ratio method and graphic method were used to explore the geochemical characteristics of sediments and their environmental implication.The results show that the contents of SiO_(2),Na_(2)O,TiO_(2) and Zr in sediments of Dawen River and Yellow River are relatively high,and the contents of iron and manganese oxides,organic matter,CaO,P2O5 and Sr in lake sediments are relatively high.That reveals the differences of sedimentary environments between the rivers and the lake.The contents of Sr and Zr in Dawen River are affected by the rapid migration of clastic materials in the upstream carbonate source area during the flood season;the δCe,ΣREE and REE’s ratios in the sediments of the Yellow River reflect the influence of the Loess source;and the distribution of elements changes along the flow direction during the flood season.The characteristics of pH,element composition and LREE&HREE fractionation of the lake sediments indicate that the sediment source is complex,and the lake environment is affected by the flood season.The study shows that the geochemical content and its variation characteristics of sediments effectively reveal the sedimentary environment,material composition and characteristics of flood season of rivers and the lake in the study area.

Unfolding neutron spectra from water-pumping-injection multilayered concentric sphere neutron spectrometer using self-adaptive differential evolution algorithm

A self-adaptive differential evolution neutron spectrum unfolding algorithm(SDENUA)is established in this study to unfold the neutron spectra obtained from a water-pumping-injection multilayered concentric sphere neutron spectrometer(WMNS).Specifically,the neutron fluence bounds are estimated to accelerate the algorithm convergence,and the minimum error between the optimal solution and input neutron counts with relative uncertainties is limited to 10^(-6)to avoid unnecessary calculations.Furthermore,the crossover probability and scaling factor are self-adaptively controlled.FLUKA Monte Carlo is 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 boron neutron capture therapy,and(4)a reactor spectrum.Subsequently,the measured neutron counts are unfolded 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 or an a priori default spectrum.The results indicate that the solutions of the SDENUA agree better with the IAEA spectra than those of MAXED and GRAVEL in UMG 3.1,and the errors of the final results calculated using the SDENUA are less than 12%.The established SDENUA can be used to unfold spectra from the WMNS.

Method for rapid warning and activity concentration estimates in online waterγ-spectrometry systems

Onlineγ-spectrometry systems for inland waters,most of which extract samples in situ and in real time,are able to produce reliable activity concentration measurements for waterborne radionuclides only when they are distributed relatively uniformly and enter into a steady-state diffusion regime in the measurement chamber.To protect residents’health and ensure the safety of the living environment,better timeliness is required for this measurement method.To address this issue,this study established a mathematical model of the online waterγ-spectrometry system so that rapid warning and activity estimates can be obtained for water under non-steady-state(NSS)conditions.In addition,the detection efficiency of the detector for radionuclides during the NSS diffusion process was determined by applying the computational fluid dynamics technique in conjunction with Monte Carlo simulations.On this basis,a method was developed that allowed the online waterγ-spectrometry system to provide rapid warning and activity concentration estimates for radionuclides in water.Subsequent analysis of the NSS-mode measurements of^(40)K radioactive solutions with different activity concentrations determined the optimum warning threshold and measurement time for producing accurate activity concentration estimates for radionuclides.The experimental results show that the proposed NSS measurement method is able to give warning and yield accurate activity concentration estimates for radionuclides 55.42 and 69.42 min after the entry of a 10 Bq/L^(40)K radioactive solution into the measurement chamber,respectively.These times are much shorter than the 90 min required by the conventional measurement method.Furthermore,the NSS measurement method allows the measurement system to give rapid(within approximately 15 min)warning when the activity concentrations of some radionuclides reach their respective limits stipulated in the Guidelines for Drinking-water Quality of the WHO,suggesting that this method considerably enhances the warning capacity of in situ online waterγ-spectrometry systems.

Design of weak current measurement system and research on temperature impact

A dedicated weak current measurement system was designed to measure the weak currents generated by the neutron ionization chamber.This system incorporates a second-order low-pass filter circuit and the Kalman filtering algorithm to effectively filter out noise and minimize interference in the measurement results.Testing conducted under normal temperature conditions has demonstrated the system's high precision performance.However,it was observed that temperature variations can affect the measurement performance.Data were collected across temperatures ranging from -20 to 70℃,and a temperature correction model was established through linear regression fitting to address this issue.The feasibility of the temperature correction model was confirmed at temperatures of -5 and 40℃,where relative errors remained below 0.1% after applying the temperature correction.The research indicates that the designed measurement system exhibits excellent temperature adaptability and high precision,making it particularly suitable for measuring weak currents.

Syn-collision Biotite Hornblende Granodiorite from the Zedong Area,Tibet:Zircon U–Pb Isotope Chronology,Petro-geochemistry,and Geodynamic Significance

Cu–Au mineralization is rare in the Jurassic–Early Tertiary batholiths related to the India–Asia collision. Geochemical analysis and U–Pb isotope chronology was carried out on Shuangbujiere biotite hornblende granodiorite from the Zedong area. Zircon grains of the biotite hornblende granodiorite show oscillatory growth zonation and have high Th/U ratios of 1.08–2.39, indicating a magmatic origin for the zircons. Geochrological test yielded a LA-ICP-MS U-Pb age of 51.5±1.0 Ma, suggesting that the emplacement age of the biotite hornblende granodiorite is Early Eocene. The Shuangbujiere biotite hornblende granodiorites have geochemical features characteristic of adakite and are associated with a calc–alkaline metaluminous I-type granite enriched in Sr, high in Mg~#(49.6–54.9) and Sr/Y, and depleted in Y and Yb. These results indicate that this intrusion formation may have been associated with crustal thickening caused by the early collision of the Indian and Eurasian Plates. As the process of crustal thickening continued, the heating of the underplated basaltic magma caused the thickened lower crust amphibolite to dehydrate the melt and form a high-K calc–alkaline adakitic melt at about 848°C. Meanwhile, magma mixing of the underplated basaltic melt and high-K calc–alkaline adakitic melt formed a high-Mg# adakite representative of the sys-collisional tectonic setting.