Cosmic-ray muons are highly penetrating background-radiation particles found in natural environments.In this study,we develop and test a plastic scintillator muon detector based on machine-learning algorithms.The dete...Cosmic-ray muons are highly penetrating background-radiation particles found in natural environments.In this study,we develop and test a plastic scintillator muon detector based on machine-learning algorithms.The detector underwent muon position-resolution tests at the Institute of Modern Physics in Lanzhou using a multiwire drift chamber(MWDC)experimental platform.In the simulation,the same structural and performance parameters were maintained to ensure the reliability of the simulation results.The Gaussian process regression(GPR)algorithm was used as the position-reconstruction algorithm owing to its optimal performance.The results of the Time Difference of Arrival algorithm were incorporated as one of the features of the GPR model to reconstruct the muon hit positions.The accuracy of the position reconstruction was evaluated by comparing the experimental results with Geant4 simulation results.In the simulation,large-area plastic scintillator detectors achieved a position resolution better than 20 mm.In the experimental-platform tests,the position resolutions of the test detectors were 27.9 mm.We also analyzed factors affecting the position resolution,including the critical angle of the total internal reflection of the photomultiplier tubes and distribution of muons in the MWDC.Simulations were performed to image both large objects and objects with different atomic numbers.The results showed that the system could image high-and low-Z materials in the constructed model and distinguish objects with significant density differences.This study demonstrates the feasibility of the proposed system,thereby providing a new detector system for muon-imaging applications.展开更多
Based on volume of fluid(VoF)interface capturing method and shear-stress transport(SST)k-ω turbulence model,numerical simulation was performed to reveal the flow mechanism of metal melts in melt delivery nozzle(MDN)d...Based on volume of fluid(VoF)interface capturing method and shear-stress transport(SST)k-ω turbulence model,numerical simulation was performed to reveal the flow mechanism of metal melts in melt delivery nozzle(MDN)during gas atomization(GA)process.The experimental validation indicated that the numerical models could give a reasonable prediction on the melt flow process in the MDN.With the decrease of the MDN inner-diameter,the melt flow resistance increased for both molten aluminum and iron,especially achieving an order of 10^(2) kPa in the case of the MDN inner-diameter≤1 mm.Based on the conventional GA process,the positive pressure was imposed on the viscous aluminum alloy melt to overcome its flow resistance in the MDN,thus producing powders under different MDN inner-diameters.When the MDN inner-diameter was reduced from 4 to 2 mm,the yield of fine powder(<150μm)soared from 54.7%to 94.2%.The surface quality of powders has also been improved when using a smaller inner-diameter MDN.展开更多
The muon radiography imaging technique for high-atomic-number objects(Z)and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation det...The muon radiography imaging technique for high-atomic-number objects(Z)and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation detection imaging.However,few imaging studies have been reported on low and medium Z objects at the centimeter scale.This paper presents an imaging system that consists of three layers of a position-sensitive detector and four plastic scintillation detectors.It acquires data by coincidence detection technique of cosmic-ray muon and its secondary particles.A 3D imaging algorithm based on the density of the coinciding muon trajectory was developed,and 4D imaging that takes the atomic number dimension into account by considering the secondary particle ratio information was achieved.The resultant reconstructed 3D images could distinguish between a series of cubes with 5-mm-side lengths and 2-mm-intervals.If the imaging time is more than 20 days,this method can distinguish intervals with a width of 1 mm.The 4D images can specify target objects with low,medium,and high Z values.展开更多
Muon tomography is a novel method for the non-destructive imaging of materials based on muon rays,which are highly penetrating in natural background radiation.Currently,the most commonly used imaging methods include m...Muon tomography is a novel method for the non-destructive imaging of materials based on muon rays,which are highly penetrating in natural background radiation.Currently,the most commonly used imaging methods include muon radiography and muon tomography.A previously studied method known as coinciding muon trajectory density tomography,which utilizes muonic secondary particles,is proposed to image low and medium atomic number(Z)materials.However,scattering tomography is mostly used to image high-Z materials,and coinciding muon trajectory density tomography exhibits a hollow phenomenon in the imaging results owing to the self-absorption effect.To address the shortcomings of the individual imaging methods,hybrid model tomography combining scattering tomography and coinciding muon trajectory density tomography is proposed and verified.In addition,the peak signal-to-noise ratio was introduced to quantitatively analyze the image quality.Different imaging models were simulated using the Geant4 toolkit to confirm the advantages of this innovative method.The simulation results showed that hybrid model tomography can image centimeter-scale materials with low,medium,and high Z simultaneously.For high-Z materials with similar atomic numbers,this method can clearly distinguish those with apparent differences in density.According to the peak signal-to-noise ratio of the analysis,the reconstructed image quality of the new method was significantly higher than that of the individual imaging methods.This study provides a reliable approach to the compatibility of scattering tomography and coinciding muon trajectory density tomography.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12275120,11875163)Ministry of Science and Technology of China(No.2020YFE0202001)+1 种基金Science and Technology Innovation Program of Hunan Province(No.2022RC1202)Hunan Provincial Natural Science Foundation(No.2021JJ20006).
文摘Cosmic-ray muons are highly penetrating background-radiation particles found in natural environments.In this study,we develop and test a plastic scintillator muon detector based on machine-learning algorithms.The detector underwent muon position-resolution tests at the Institute of Modern Physics in Lanzhou using a multiwire drift chamber(MWDC)experimental platform.In the simulation,the same structural and performance parameters were maintained to ensure the reliability of the simulation results.The Gaussian process regression(GPR)algorithm was used as the position-reconstruction algorithm owing to its optimal performance.The results of the Time Difference of Arrival algorithm were incorporated as one of the features of the GPR model to reconstruct the muon hit positions.The accuracy of the position reconstruction was evaluated by comparing the experimental results with Geant4 simulation results.In the simulation,large-area plastic scintillator detectors achieved a position resolution better than 20 mm.In the experimental-platform tests,the position resolutions of the test detectors were 27.9 mm.We also analyzed factors affecting the position resolution,including the critical angle of the total internal reflection of the photomultiplier tubes and distribution of muons in the MWDC.Simulations were performed to image both large objects and objects with different atomic numbers.The results showed that the system could image high-and low-Z materials in the constructed model and distinguish objects with significant density differences.This study demonstrates the feasibility of the proposed system,thereby providing a new detector system for muon-imaging applications.
基金the National Natural Science Foundation of China(No.52074157)Shenzhen Science and Technology Innovation Com-mission,China(Nos.JSGG20180508152608855,KQTD20170328154443162)Shenzhen Key Laboratory for Additive Manufacturing of High-performance Materials,China(No.ZDSYS201703031748354).
文摘Based on volume of fluid(VoF)interface capturing method and shear-stress transport(SST)k-ω turbulence model,numerical simulation was performed to reveal the flow mechanism of metal melts in melt delivery nozzle(MDN)during gas atomization(GA)process.The experimental validation indicated that the numerical models could give a reasonable prediction on the melt flow process in the MDN.With the decrease of the MDN inner-diameter,the melt flow resistance increased for both molten aluminum and iron,especially achieving an order of 10^(2) kPa in the case of the MDN inner-diameter≤1 mm.Based on the conventional GA process,the positive pressure was imposed on the viscous aluminum alloy melt to overcome its flow resistance in the MDN,thus producing powders under different MDN inner-diameters.When the MDN inner-diameter was reduced from 4 to 2 mm,the yield of fine powder(<150μm)soared from 54.7%to 94.2%.The surface quality of powders has also been improved when using a smaller inner-diameter MDN.
基金supported by the Ministry of Science and Technology of China Foundation(No.2020YFE0202001)the National Natural Science Foundation of China(No.11875163)the Natural Science Foundation of Hunan Province(No.2021JJ20006).
文摘The muon radiography imaging technique for high-atomic-number objects(Z)and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation detection imaging.However,few imaging studies have been reported on low and medium Z objects at the centimeter scale.This paper presents an imaging system that consists of three layers of a position-sensitive detector and four plastic scintillation detectors.It acquires data by coincidence detection technique of cosmic-ray muon and its secondary particles.A 3D imaging algorithm based on the density of the coinciding muon trajectory was developed,and 4D imaging that takes the atomic number dimension into account by considering the secondary particle ratio information was achieved.The resultant reconstructed 3D images could distinguish between a series of cubes with 5-mm-side lengths and 2-mm-intervals.If the imaging time is more than 20 days,this method can distinguish intervals with a width of 1 mm.The 4D images can specify target objects with low,medium,and high Z values.
基金supported by the National Natural Science Foundation of China(No.11875163)Natural Science Foundation of Hunan Province(Nos.2021JJ20006 and 2021JJ40444)+1 种基金Ministry of Science and Technology of China(No.2020YFE0202001)Department of Education of Hunan Province(Nos.19B488 and 21A0281)。
文摘Muon tomography is a novel method for the non-destructive imaging of materials based on muon rays,which are highly penetrating in natural background radiation.Currently,the most commonly used imaging methods include muon radiography and muon tomography.A previously studied method known as coinciding muon trajectory density tomography,which utilizes muonic secondary particles,is proposed to image low and medium atomic number(Z)materials.However,scattering tomography is mostly used to image high-Z materials,and coinciding muon trajectory density tomography exhibits a hollow phenomenon in the imaging results owing to the self-absorption effect.To address the shortcomings of the individual imaging methods,hybrid model tomography combining scattering tomography and coinciding muon trajectory density tomography is proposed and verified.In addition,the peak signal-to-noise ratio was introduced to quantitatively analyze the image quality.Different imaging models were simulated using the Geant4 toolkit to confirm the advantages of this innovative method.The simulation results showed that hybrid model tomography can image centimeter-scale materials with low,medium,and high Z simultaneously.For high-Z materials with similar atomic numbers,this method can clearly distinguish those with apparent differences in density.According to the peak signal-to-noise ratio of the analysis,the reconstructed image quality of the new method was significantly higher than that of the individual imaging methods.This study provides a reliable approach to the compatibility of scattering tomography and coinciding muon trajectory density tomography.
