This study compares the“cavitation to no-cavitation”transition processes and the resulting pressure oscillation effects of water,liquid oxygen and liquid methane in an adjustable cavitation Venturi tube through back...This study compares the“cavitation to no-cavitation”transition processes and the resulting pressure oscillation effects of water,liquid oxygen and liquid methane in an adjustable cavitation Venturi tube through back pressure experiments.The modal characteristics of cavitation images and the frequency domain characteristics of vibrations were analyzed using the proper orthogonal decomposition(POD)and fast Fourier transform(FFT).By observing with a transparent Venturi tube and high-speed photography,combined with one-dimensional homogeneous flow simulation,the evolution laws of cavitation length and downstream pressure oscillation during the processes of changing the pressure ratio p_(r) and the throat area A_(t) were studied.The evolution laws of cavitation length and flow pattern about working parameters were obtained,revealing the correlation between cavitation and vibration.Under low pressure ratios,the oscillation of bubble collapse dominated by the returning jet causes the tail of the cavitation area to be lengthened,resulting in an increase in downstream amplitude.Increasing the pressure ratio can effectively control the cavitation length and reduce the amplitude of downstream pressure oscillation.Reducing the throat area by moving the plug cone increases the cavitation length,and the downstream oscillation amplitude first increases and then decreases,with an oscillation maximum value existing.展开更多
The Corona Virus Disease 2019(COVID-19)pandemic is still imposing a devastating impact on public health,the economy,and society.Predicting the development of epidemics and exploring the effects of various mitigation s...The Corona Virus Disease 2019(COVID-19)pandemic is still imposing a devastating impact on public health,the economy,and society.Predicting the development of epidemics and exploring the effects of various mitigation strategies have been a research focus in recent years.However,the spread simulation of COVID-19 in the dynamic social system is relatively unexplored.To address this issue,considering the outbreak of COVID-19 at Nanjing Lukou Airport in 2021,we constructed an artificial society of Nanjing Lukou Airport based on the Artificial societies,Computational experiments,and Parallel execution(ACP)approach.Specifically,the artificial society includes an environmental model,population model,contact networks model,disease spread model,and intervention strategy model.To reveal the dynamic variation of individuals in the airport,we first modeled the movement of passengers and designed an algorithm to generate the moving traces.Then,the mobile contact networks were constructed and aggregated with the static networks of staff and passengers.Finally,the complex dynamical network of contacts between individuals was generated.Based on the artificial society,we conducted large-scale computational experiments to study the spread characteristics of COVID-19 in an airport and to investigate the effects of different intervention strategies.Learned from the reproduction of the outbreak,it is found that the increase in cumulative incidence exhibits a linear growth mode,different from that(an exponential growth mode)in a static network.In terms of mitigation measures,promoting unmanned security checks and boarding in an airport is recommended,as to reduce contact behaviors between individuals and staff.展开更多
The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and control.To meet these demands,the parallel systems method rooted ...The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and control.To meet these demands,the parallel systems method rooted in the artificial systems,computational experiments,and parallel execution(ACP)approach has been developed.The method cultivates a cycle termed parallel intelligence,which iteratively creates data,acquires knowledge,and refines the actual system.Over the past two decades,the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines,offering vers atile interdisciplinary solutions for complex systems across diverse fields.This review explores the origins and fundamental concepts of the parallel systems method,showcasing its accomplishments as a diverse array of parallel technologies and applica-tions while also prognosticating potential challenges.We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.展开更多
Strategy evaluation and optimization in response to troubling urban issues has become a challenging issue due to increasing social uncertainty,unreliable predictions,and poor decision-making.To address this problem,we...Strategy evaluation and optimization in response to troubling urban issues has become a challenging issue due to increasing social uncertainty,unreliable predictions,and poor decision-making.To address this problem,we propose a universal computational experiment framework with a fine-grained artificial society that is integrated with data-based models.The purpose of the framework is to evaluate the consequences of various combinations of strategies geared towards reaching a Pareto optimum with regards to efficacy versus costs.As an example,by modeling coronavirus disease 2019 mitigation,we show that Pareto frontier nations could achieve better economic growth and more effective epidemic control through the analysis of real-world data.Our work suggests that a nation’s intervention strategy could be optimized based on the measures adopted by Pareto frontier nations through large-scale computational experiments.Our solution has been validated for epidemic control,and it can be generalized to other urban issues as well.展开更多
Optical-SAR image matching is a fundamental task for remote sensing applications.While existing methods perform well on some popular datasets such as SEN1-2 and WHU-SEN-City,their generalizability across diverse data ...Optical-SAR image matching is a fundamental task for remote sensing applications.While existing methods perform well on some popular datasets such as SEN1-2 and WHU-SEN-City,their generalizability across diverse data sources such as satellites,spatial resolutions,and scenes remains insufficiently investigated,hindering the practical implementation of optical-SAR matching in various downstream tasks.Thus,3MOS,the first multi-source,multi-resolution,and multi-scene optical-SAR dataset,was proposed in our study to address this gap.This dataset consists of 113k optical-SAR image pairs,with the SAR data collected from five satellites and resolutions ranging from 3.5 m to 12.5 m,further categorized into eight scenes,such as urban,rural,and plains through a simple but practical classification strategy.Based on this dataset,the performance of optical-SAR matching methods was evaluated through the data with diverse characteristics.Additionally,extensive experiments were conducted,and the following two findings were obtained.1)None of the state-of-the-art methods achieved consistently superior performance across different sources,resolutions,and scenes,specifying significant generalization challenges for diverse downstream task data.2)Training data distribution significantly impacted the matching performance of deep-learning models,highlighting the domain adaptation challenge in optical-SAR image matching.Furthermore,the practical utility of the dataset was comprehensively validated through multimodal change detection experiments,demonstrating its substantial value for a wide range of downstream applications.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.T2221002)。
文摘This study compares the“cavitation to no-cavitation”transition processes and the resulting pressure oscillation effects of water,liquid oxygen and liquid methane in an adjustable cavitation Venturi tube through back pressure experiments.The modal characteristics of cavitation images and the frequency domain characteristics of vibrations were analyzed using the proper orthogonal decomposition(POD)and fast Fourier transform(FFT).By observing with a transparent Venturi tube and high-speed photography,combined with one-dimensional homogeneous flow simulation,the evolution laws of cavitation length and downstream pressure oscillation during the processes of changing the pressure ratio p_(r) and the throat area A_(t) were studied.The evolution laws of cavitation length and flow pattern about working parameters were obtained,revealing the correlation between cavitation and vibration.Under low pressure ratios,the oscillation of bubble collapse dominated by the returning jet causes the tail of the cavitation area to be lengthened,resulting in an increase in downstream amplitude.Increasing the pressure ratio can effectively control the cavitation length and reduce the amplitude of downstream pressure oscillation.Reducing the throat area by moving the plug cone increases the cavitation length,and the downstream oscillation amplitude first increases and then decreases,with an oscillation maximum value existing.
基金supported by the National Natural Science Foundation of China(Nos.62173337,21808181 and 72071207)the Hunan Key Laboratory of Intelligent Decision-Making Technology for Emergency Management(No.2020TP1013)Humanity and Social Science Youth Foundation of Ministry of China(No.19YJCZH073).
文摘The Corona Virus Disease 2019(COVID-19)pandemic is still imposing a devastating impact on public health,the economy,and society.Predicting the development of epidemics and exploring the effects of various mitigation strategies have been a research focus in recent years.However,the spread simulation of COVID-19 in the dynamic social system is relatively unexplored.To address this issue,considering the outbreak of COVID-19 at Nanjing Lukou Airport in 2021,we constructed an artificial society of Nanjing Lukou Airport based on the Artificial societies,Computational experiments,and Parallel execution(ACP)approach.Specifically,the artificial society includes an environmental model,population model,contact networks model,disease spread model,and intervention strategy model.To reveal the dynamic variation of individuals in the airport,we first modeled the movement of passengers and designed an algorithm to generate the moving traces.Then,the mobile contact networks were constructed and aggregated with the static networks of staff and passengers.Finally,the complex dynamical network of contacts between individuals was generated.Based on the artificial society,we conducted large-scale computational experiments to study the spread characteristics of COVID-19 in an airport and to investigate the effects of different intervention strategies.Learned from the reproduction of the outbreak,it is found that the increase in cumulative incidence exhibits a linear growth mode,different from that(an exponential growth mode)in a static network.In terms of mitigation measures,promoting unmanned security checks and boarding in an airport is recommended,as to reduce contact behaviors between individuals and staff.
基金National Natural Science Foundation of China(62202477,62173337,62276272,21808181,72071207,72025405,72088101)Special Key Project of Biosafety Technologies(2022YFC2604000)+3 种基金National Major Research&Develop-ment Program of China,Social Science Foundation of Shanghai(2022JG204-ZGL730)Na-tional Social Science Foundation of China(22ZDA102)Hunan Science and Technology Plan project(2020TP1013,2020JJ4673,2023JJ40685)Na-tional University of Defense Technology(NUDT)for its 70h anniversary.
文摘The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and control.To meet these demands,the parallel systems method rooted in the artificial systems,computational experiments,and parallel execution(ACP)approach has been developed.The method cultivates a cycle termed parallel intelligence,which iteratively creates data,acquires knowledge,and refines the actual system.Over the past two decades,the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines,offering vers atile interdisciplinary solutions for complex systems across diverse fields.This review explores the origins and fundamental concepts of the parallel systems method,showcasing its accomplishments as a diverse array of parallel technologies and applica-tions while also prognosticating potential challenges.We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.
基金supported by the National Natural Science Foundation of China(62173337,21808181,and 72071207)supported by the National Natural Science Foundation of China(71790615,72025405,91846301,72088101)+2 种基金the Hunan Science and Technology Plan Project(2020TP1013 and 2020JJ4673)the Shenzhen Basic Research Project for Development of Science and Technology(JCYJ20200109141218676 and 202008291726500001)the Innovation Team Project of Colleges in Guangdong Province(2020KCXTD040).
文摘Strategy evaluation and optimization in response to troubling urban issues has become a challenging issue due to increasing social uncertainty,unreliable predictions,and poor decision-making.To address this problem,we propose a universal computational experiment framework with a fine-grained artificial society that is integrated with data-based models.The purpose of the framework is to evaluate the consequences of various combinations of strategies geared towards reaching a Pareto optimum with regards to efficacy versus costs.As an example,by modeling coronavirus disease 2019 mitigation,we show that Pareto frontier nations could achieve better economic growth and more effective epidemic control through the analysis of real-world data.Our work suggests that a nation’s intervention strategy could be optimized based on the measures adopted by Pareto frontier nations through large-scale computational experiments.Our solution has been validated for epidemic control,and it can be generalized to other urban issues as well.
基金supported by the National Natural Science Foundation of China(No.12472189)the Science and Technology Innovation Program of Hunan Province(No.2022RC1196).
文摘Optical-SAR image matching is a fundamental task for remote sensing applications.While existing methods perform well on some popular datasets such as SEN1-2 and WHU-SEN-City,their generalizability across diverse data sources such as satellites,spatial resolutions,and scenes remains insufficiently investigated,hindering the practical implementation of optical-SAR matching in various downstream tasks.Thus,3MOS,the first multi-source,multi-resolution,and multi-scene optical-SAR dataset,was proposed in our study to address this gap.This dataset consists of 113k optical-SAR image pairs,with the SAR data collected from five satellites and resolutions ranging from 3.5 m to 12.5 m,further categorized into eight scenes,such as urban,rural,and plains through a simple but practical classification strategy.Based on this dataset,the performance of optical-SAR matching methods was evaluated through the data with diverse characteristics.Additionally,extensive experiments were conducted,and the following two findings were obtained.1)None of the state-of-the-art methods achieved consistently superior performance across different sources,resolutions,and scenes,specifying significant generalization challenges for diverse downstream task data.2)Training data distribution significantly impacted the matching performance of deep-learning models,highlighting the domain adaptation challenge in optical-SAR image matching.Furthermore,the practical utility of the dataset was comprehensively validated through multimodal change detection experiments,demonstrating its substantial value for a wide range of downstream applications.
