Here,we analyze the characteristics and the formation mechanisms of low-level jets(LLJs)in the middle reaches of the Yangtze River during the 2010 mei-yu season using Wuhan station radiosonde data and the fifth genera...Here,we analyze the characteristics and the formation mechanisms of low-level jets(LLJs)in the middle reaches of the Yangtze River during the 2010 mei-yu season using Wuhan station radiosonde data and the fifth generation of the European Centre for Medium-Range Weather Forecasts(ERA5)reanalysis dataset.Our results show that the vertical structure of LLJs is characterized by a predominance of boundary layer jets(BLJs)concentrated at heights of 900-1200 m.The BLJs occur most frequently at 2300 LST(LST=UTC+8 hours)but are strongest at 0200 LST,with composite wind velocities>14 m s^(-1).Synoptic-system-related LLJs(SLLJs)occur most frequently at 0800 LST but are strongest at 1100LST,with composite wind velocities>12 m s^(-1).Both BLJs and SLLJs are characterized by a southwesterly wind direction,although the wind direction of SLLJs is more westerly,and northeasterly SLLJs occur more frequently than northeasterly BLJs.When Wuhan is south of the mei-yu front,the westward extension of the northwest Pacific subtropical high intensifies,and the low-pressure system in the eastern Tibetan Plateau strengthens,favoring the formation of LLJs,which are closely related to precipitation.The wind speeds on rainstorm days are greater than those on LLJ days.Our analysis of four typical heavy precipitation events shows the presence of LLJs at the center of the precipitation and on its southern side before the onset of heavy precipitation.BLJs were shown to develop earlier than SLLJs.展开更多
The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce...The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.展开更多
Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is co...Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.展开更多
The treatment of non-small cell lung cancer(NSCLC)remains a challenge due to tumor evolution during anti-angiogenesis therapies,in which the mechanism of vascular mimicry(VM)is believed to result in ineffective treatm...The treatment of non-small cell lung cancer(NSCLC)remains a challenge due to tumor evolution during anti-angiogenesis therapies,in which the mechanism of vascular mimicry(VM)is believed to result in ineffective treatment[1].To conquer this challenge,substantial effort has recently been devoted to seeking out natural compounds on account of their multitarget actions.As a traditional herbal medicine,platycodin D(PD)is the major bioactive monomer derived from Platycodon grandiflorum(P.grandiflorum)and is used as an expectorant for pulmonary disease in Asia[2].展开更多
The development of single electrode with multifunctional purposes for electrochemical devices remains a symbolic challenge in recent technology.This work explores interfacially-rich transition metal nitride hybrid tha...The development of single electrode with multifunctional purposes for electrochemical devices remains a symbolic challenge in recent technology.This work explores interfacially-rich transition metal nitride hybrid that consist of nickel nitride and vanadium oxynitride(VO_(0.26)N_(0.52))on robust carbon fiber(denoted CF/Ni_(3)N/VON)as trifunctional electrode for hydrogen evolution reaction(HER),oxygen evolution reaction(OER),and sodium ion batteries(SIBs).The as-prepared CF/Ni_(3)N/VON exhibits low HER overpotential of 48 m V@10 m A cm^(-2),OER overpotential of 287 m V@10 m A cm^(-2),and sodium-ion anode storage reversible capacity of 555 m A h g^(-1)@0.2 C.Theoretical analyses reveal that the Ni_(3)N effectively facilitates hydrogen desorption for HER,increases the electrical conductivity for OER,and promotes the Na-ion storage intercalation process,while the VON substantially elevates the water dissociation kinetics for HER,accelerates the adsorption of OH*intermediate for OER and enhances the Na-ion surface adsorption storage process.Owing to the excellent HER and OER performances of the CF/Ni_(3)N/VON electrode,an overall water splitting device denoted as CF/Ni_(3)N/VON//CF/Ni_(3)N/VON was not only assembled showing an operating voltage of 1.63 V at current density of 10 m A cm^(-2)but was also successfully self-powered by the assembled CF/Ni_(3)N/VON//CF/Na_(3)V_(2)(PO_(4))_(3) flexible sodium ion battery.This work will contribute to the development of efficient and cost-effective flexible integrated electrochemical energy devices.展开更多
In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of u...In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.展开更多
As a new type of lightweight structure,metallic lattice structure has higher stiffness and strength to weight ratio.To freely obtain 316L lattice structures with designed cell structure and adjustable porosity,additiv...As a new type of lightweight structure,metallic lattice structure has higher stiffness and strength to weight ratio.To freely obtain 316L lattice structures with designed cell structure and adjustable porosity,additive manufacturing combined with investment casting was conducted to fabricate the 316L lattice structures with Kelvin cell.The compression simulation of 316L lattice structures with different porosities was carried out by using the finite element method.The numerical simulation results were verified by compression experiment,and the simulated results were consistent with the compression tests.The compressive mechanical properties of 316L lattice structures are directly related to porosity and independent of strut diameters.The 316L lattice structures with Kelvin cell have a smooth stress-strain curve and obvious plastic platform,and the hump stress-strain curves are avoided.展开更多
The energy-resolved neutron imaging spectrometer(ERNI)will be installed in 2022 according to the spectrometer construction plan of the China Spallation Neutron Source(CSNS).The instrument requires neutron detectors wi...The energy-resolved neutron imaging spectrometer(ERNI)will be installed in 2022 according to the spectrometer construction plan of the China Spallation Neutron Source(CSNS).The instrument requires neutron detectors with the coverage area of approximately 4 m^(2)in 5°-170°neutron diffraction angle.The neutron detection efficiency needs to be better than 40%at 1 A neutron wavelength.The spatial resolution should be better than 3 mm×50 mm in the horizontal and vertical directions respectively.We develop a one-dimensional scintillator neutron detector which is composed of the^(6)Li F/Zn S(Ag)scintillation screens,the wavelength-shifting fiber(WLSF)array,the silicon photomultipliers(Si PMs),and the self-designed application-specific integrated circuit(ASIC)readout electronics.The pixel size of the detector is designed as 3 mm×50 mm,and the neutron-sensitive area is 50 mm×200 mm.The performance of the detector prototype is measured using neutron beam 20#of the CSNS.The maximum counting rate of 247 k Hz,and the detection efficiency of63%at 1.59 A are obtained.The test results show that the performance of the detector fulfills the physical requirements of the ERNI under construction at the CSNS.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.42230612,41620104009,41705019,42075186,and 41975058)the Projects of the S&T Development Foundation of the Hubei Meteorological Bureau(Grants No.2021Q04 and 2020Y04)。
文摘Here,we analyze the characteristics and the formation mechanisms of low-level jets(LLJs)in the middle reaches of the Yangtze River during the 2010 mei-yu season using Wuhan station radiosonde data and the fifth generation of the European Centre for Medium-Range Weather Forecasts(ERA5)reanalysis dataset.Our results show that the vertical structure of LLJs is characterized by a predominance of boundary layer jets(BLJs)concentrated at heights of 900-1200 m.The BLJs occur most frequently at 2300 LST(LST=UTC+8 hours)but are strongest at 0200 LST,with composite wind velocities>14 m s^(-1).Synoptic-system-related LLJs(SLLJs)occur most frequently at 0800 LST but are strongest at 1100LST,with composite wind velocities>12 m s^(-1).Both BLJs and SLLJs are characterized by a southwesterly wind direction,although the wind direction of SLLJs is more westerly,and northeasterly SLLJs occur more frequently than northeasterly BLJs.When Wuhan is south of the mei-yu front,the westward extension of the northwest Pacific subtropical high intensifies,and the low-pressure system in the eastern Tibetan Plateau strengthens,favoring the formation of LLJs,which are closely related to precipitation.The wind speeds on rainstorm days are greater than those on LLJ days.Our analysis of four typical heavy precipitation events shows the presence of LLJs at the center of the precipitation and on its southern side before the onset of heavy precipitation.BLJs were shown to develop earlier than SLLJs.
基金This work was supported financially by the National Natural Science Foundation of China(No.12375176).
文摘The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.
基金financially supported by the Technology Development Fund of China Academy of Machinery Science and Technology(No.170221ZY01)。
文摘Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.
基金funded by the National Natural Science Foundation of China(Grant Nos.:82004081 and 52073145)the National Natural Science Foundation of Nanjing University of Chinese Medicine,China(Grant No.:NZY82004081).
文摘The treatment of non-small cell lung cancer(NSCLC)remains a challenge due to tumor evolution during anti-angiogenesis therapies,in which the mechanism of vascular mimicry(VM)is believed to result in ineffective treatment[1].To conquer this challenge,substantial effort has recently been devoted to seeking out natural compounds on account of their multitarget actions.As a traditional herbal medicine,platycodin D(PD)is the major bioactive monomer derived from Platycodon grandiflorum(P.grandiflorum)and is used as an expectorant for pulmonary disease in Asia[2].
基金Tao Cheng thanks the support from Suzhou Key Laboratory of Functional Nano&Soft Materials,Collaborative Innovation Center of Suzhou Nano Science&Technology,the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the 111 Project+2 种基金the National Natural Science Foundation of China(No.21903058 and No.22173066)the Natural Science Foundation of Jiangsu Province(BK20190810)William A.GoddardⅢis supported by the Liquid Sunlight Alliance,which is supported by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences,Fuels from Sunlight Hub under Award Number DE-SC0021266.
基金supported by the Hunan Provincial Natural Science Foundation (2021JJ30087)the Science and Technology Innovation Program of Hunan Province (2022WZ1012)the Fundamental Research Funds for the Central Universities and Guangxi Key Laboratory of Information Materials&Guilin University of Electronic Technology,China (211011K)。
文摘The development of single electrode with multifunctional purposes for electrochemical devices remains a symbolic challenge in recent technology.This work explores interfacially-rich transition metal nitride hybrid that consist of nickel nitride and vanadium oxynitride(VO_(0.26)N_(0.52))on robust carbon fiber(denoted CF/Ni_(3)N/VON)as trifunctional electrode for hydrogen evolution reaction(HER),oxygen evolution reaction(OER),and sodium ion batteries(SIBs).The as-prepared CF/Ni_(3)N/VON exhibits low HER overpotential of 48 m V@10 m A cm^(-2),OER overpotential of 287 m V@10 m A cm^(-2),and sodium-ion anode storage reversible capacity of 555 m A h g^(-1)@0.2 C.Theoretical analyses reveal that the Ni_(3)N effectively facilitates hydrogen desorption for HER,increases the electrical conductivity for OER,and promotes the Na-ion storage intercalation process,while the VON substantially elevates the water dissociation kinetics for HER,accelerates the adsorption of OH*intermediate for OER and enhances the Na-ion surface adsorption storage process.Owing to the excellent HER and OER performances of the CF/Ni_(3)N/VON electrode,an overall water splitting device denoted as CF/Ni_(3)N/VON//CF/Ni_(3)N/VON was not only assembled showing an operating voltage of 1.63 V at current density of 10 m A cm^(-2)but was also successfully self-powered by the assembled CF/Ni_(3)N/VON//CF/Na_(3)V_(2)(PO_(4))_(3) flexible sodium ion battery.This work will contribute to the development of efficient and cost-effective flexible integrated electrochemical energy devices.
基金supported in part by Shanghai Pujiang Program under Grant No.21PJ1402600in part by Natural Science Foundation of Chongqing,China under Grant No.CSTB2022NSCQ-MSX0375+4 种基金in part by Song Shan Laboratory Foundation,under Grant No.YYJC022022007in part by Zhejiang Provincial Natural Science Foundation of China under Grant LGJ22F010001in part by National Key Research and Development Program of China under Grant 2020YFA0711301in part by National Natural Science Foundation of China under Grant 61922049。
文摘In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.
基金supported by the Ministry of Education,Singapore(MOE2019-T2-1-093 and MOE-T2EP10122-0002)the Energy Market Authority of Singapore(EMA-EP009-SEGC-020)+1 种基金the Agency for Science,Technology and Research(U2102d2004 and U2102d2012)the National Research Foundation Singapore(NRF-CRP26-2021RS-0002).
基金supported by the Technology Development Fund of the China Academy of Machinery Science and Technology(No.170221ZY01).
文摘As a new type of lightweight structure,metallic lattice structure has higher stiffness and strength to weight ratio.To freely obtain 316L lattice structures with designed cell structure and adjustable porosity,additive manufacturing combined with investment casting was conducted to fabricate the 316L lattice structures with Kelvin cell.The compression simulation of 316L lattice structures with different porosities was carried out by using the finite element method.The numerical simulation results were verified by compression experiment,and the simulated results were consistent with the compression tests.The compressive mechanical properties of 316L lattice structures are directly related to porosity and independent of strut diameters.The 316L lattice structures with Kelvin cell have a smooth stress-strain curve and obvious plastic platform,and the hump stress-strain curves are avoided.
基金the National Natural Science Foundation of China(Grant Nos.11875273,U1832111,61964001,and 12275049)the Science Foundation of Guangdong Province of China(Grant No.2020B1515120025)+3 种基金the Neutron Physics Laboratory Funding of China Academy of Engineering Physics(Grant No.2018BC03)the General Project of Jiangxi Province Key Research and Development Program(Grant No.20212BBG73012)the Key Scientific Research Projects of Henan Higher Education Institutions(Grant Nos.23A490002 and 24A490001)the Engineering Research Center of Nuclear Technology Application(Grant No.HJSJYB2021-4)。
文摘The energy-resolved neutron imaging spectrometer(ERNI)will be installed in 2022 according to the spectrometer construction plan of the China Spallation Neutron Source(CSNS).The instrument requires neutron detectors with the coverage area of approximately 4 m^(2)in 5°-170°neutron diffraction angle.The neutron detection efficiency needs to be better than 40%at 1 A neutron wavelength.The spatial resolution should be better than 3 mm×50 mm in the horizontal and vertical directions respectively.We develop a one-dimensional scintillator neutron detector which is composed of the^(6)Li F/Zn S(Ag)scintillation screens,the wavelength-shifting fiber(WLSF)array,the silicon photomultipliers(Si PMs),and the self-designed application-specific integrated circuit(ASIC)readout electronics.The pixel size of the detector is designed as 3 mm×50 mm,and the neutron-sensitive area is 50 mm×200 mm.The performance of the detector prototype is measured using neutron beam 20#of the CSNS.The maximum counting rate of 247 k Hz,and the detection efficiency of63%at 1.59 A are obtained.The test results show that the performance of the detector fulfills the physical requirements of the ERNI under construction at the CSNS.
