With analysis of producer's and factor supplier's dual optimization motives,this paper developed an optimal nominal output growth rate model that can conduct quantified estimation.Result of estimation of China...With analysis of producer's and factor supplier's dual optimization motives,this paper developed an optimal nominal output growth rate model that can conduct quantified estimation.Result of estimation of China's optimal industrial structure between1992 and 2009 indicates that optimal nominal output growth rate model has successfully quantified the impact of major events occurring in the process of China's economic operation on the level of deviation between actual industrial structure and optimal industrial structure.Quantitative indicators involved in this model can provide industrial policy instruments for the Chinese government in developing and adjusting industrial structure targets,optimizing resource allocation and advancing industrial structure optimization and upgrade.展开更多
The development of measurement geometry for medical X-ray computed tomography (CT) scanners was carried out from the first to the fourth-generation. This concept has also been applied for imaging of industrial proce...The development of measurement geometry for medical X-ray computed tomography (CT) scanners was carried out from the first to the fourth-generation. This concept has also been applied for imaging of industrial processes such as pipe flows or for improving design, operation, optimization and troubleshooting. Nowadays, gamma CT permits to visualize failure equipment points in three-dimensional analysis and in sections of chemical and petrochemical industries. The aim of this work is the development of the mechanical system on a third-generation industrial CT scanner to analyze laboratorial process columns which perform highly efficient separation, turning the ^6oCo, ^75Se, ^137Cs and/or ^192Ir sealed gamma-ray source(s) and the NaI(Tl) multidetector array. It also has a translation movement along the column axis to obtain as many slices of the process flow as needed. The mechanical assembly for this third-generation industrial CT scanner is comprised by strength and rigidity structural frame in stainless and carbon steels, rotating table, source shield and collimator with pneumatic exposure system, spur gear system, translator, rotary stage, drives and stepper motors. The use of suitable spur gears has given a good repeatability and high accuracy in the degree of veracity. The data acquisition boards, mechanical control interfaces, software for movement control and image reconstruction were specially development. A multiphase phantom capable to be setting with solid, liquid and gas was testing. The scanner was setting for 90 views and 19 projections for each detector totalizing 11,970 projections. Experiments to determine the linear attenuation coefficients of the phantom were carried out which applied the Lambert-Beer principle. Results showed that it was possible to distinguish between the phases even the polymethylmethacrylate and the water have very similar density and linear attenuation coefficients. It was established that the newly developed third-generation fan-beam arrangement gamma scanner unit has a good spatial resolution acceptable given the size of the used phantom in this study. The tomografic reconstruction algorithm in used 60 ~ 60 pixels images was the Alternative Minimization (AM) technique and was implemented in MATLAB and VB platforms. The mechanical system presented a good performance in terms of strength, rigidity, accuracy and repeatability with great potential to be used for education or program which dedicated to training chemical and petrochemical industry professionals and for industrial process optimization in Brazil.展开更多
Cities are the main material processors asso- ciated with industrialization. The development of urban production based on fossil fuels is the major contributor to the rise of greenhouse gas density, and to global warm...Cities are the main material processors asso- ciated with industrialization. The development of urban production based on fossil fuels is the major contributor to the rise of greenhouse gas density, and to global warming. The concept of urban industrial structure optimization is considered to be a solution to urban sustainable develop- ment and global climate issues. Enforcing energy con- servation and reducing carbon emissions are playing key roles in addressing these issues. As such, quantitative accounting and the evaluation of energy consumption and corresponding carbon emissions, which are by-products of urban production, are critical, in order to discover potential opportunities to save energy and to reduce emissions. Conventional evaluation indicators, such as "energy consumption per unit output value" and "emissions per unit output value", are concerned with immediate consumptions and emissions; while the indirect consump- tions and emissions that occur throughout the supply chain are ignored. This does not support the optimization of the overall urban industrial system. To present a systematic evaluation framework for cities, this study constructs new evaluation indicators, based on the concepts of "embodied energy" and "embodied carbon emissions", which take both the immediate and indirect effects of energy consumption and emissions into account. Taking Beijing as a case, conventional evaluation indicators are compared with the newly constructed ones. Results show that the energy consumption and emissions of urban industries are represented better by the new indicators than by conventional indicators, and provide useful information for urban industrial structure optimization.展开更多
Design,scaling-up,and optimization of industrial reactors mainly depend on step-by-step experiments and engineering experience,which is usually time-consuming,high cost,and high risk.Although numerical simulation can ...Design,scaling-up,and optimization of industrial reactors mainly depend on step-by-step experiments and engineering experience,which is usually time-consuming,high cost,and high risk.Although numerical simulation can reproduce high resolution details of hydrodynamics,thermal transfer,and reaction process in reactors,it is still challenging for industrial reactors due to huge computational cost.In this study,by combining the numerical simulation and artificial intelligence(AI)technology of machine learning(ML),a method is proposed to efficiently predict and optimize the performance of industrial reactors.A gas–solid fluidization reactor for the methanol to olefins process is taken as an example.1500 cases under different conditions are simulated by the coarse-grain discrete particle method based on the Energy-Minimization Multi-Scale model,and thus,the reactor performance data set is constructed.To develop an efficient reactor performance prediction model influenced by multiple factors,the ML method is established including the ensemble learning strategy and automatic hyperparameter optimization technique,which has better performance than the methods based on the artificial neural network.Furthermore,the operating conditions for highest yield of ethylene and propylene or lowest pressure drop are searched with the particle swarm optimization algorithm due to its strength to solve non-linear optimization problems.Results show that decreasing the methanol inflow rate and increasing the catalyst inventory can maximize the yield,while decreasing methanol the inflow rate and reducing the catalyst inventory can minimize the pressure drop.The two objectives are thus conflicting,and the practical operations need to be compromised under different circumstance.展开更多
The economic growth pattern in China is changing from high-speed development to high-quality development.In order to promote high-quality economic development,it is necessary to promote the transformation and upgradin...The economic growth pattern in China is changing from high-speed development to high-quality development.In order to promote high-quality economic development,it is necessary to promote the transformation and upgrading of all aspects of social reproduction.Artificial intelligence has promoted high-quality economic development in China from the aspects of innovation effect,technology spillover effect,factor improvement effect,and technology optimization effect.However,there are still several problems in China's Al development,such as the lack of core technologies,privacy and security,as well as the lack of high-tech talents.To this end,China should advance basic theoretical research and key generic technology development to improve the self-reliance of science and technology,as well as optimize the development environment of the industry and improve the relevant laws and regulations as well as the ethical norms system.A system to train high-quality personnel and a mechanism that allows personnel flow should be established to promote high-quality economic development.展开更多
基金sponsored by major program of Human and Social Sciences Key Research Center under the Ministry of Education,Theory and Policy Research for the Development of China's Strategic Emerging Industries(Approval No.10JJD790013)National Social Sciences Fund major program"New Tendencies of World Industrial Development and China's Fostering of Strategic Emerging Industries"(Approval No.12&ZD068)major program of Liaoning Social Sciences Planning Fund Research on Strategies for Industrial Structure Optimization of Liaoning Province(Approval No.L10AJL004)
文摘With analysis of producer's and factor supplier's dual optimization motives,this paper developed an optimal nominal output growth rate model that can conduct quantified estimation.Result of estimation of China's optimal industrial structure between1992 and 2009 indicates that optimal nominal output growth rate model has successfully quantified the impact of major events occurring in the process of China's economic operation on the level of deviation between actual industrial structure and optimal industrial structure.Quantitative indicators involved in this model can provide industrial policy instruments for the Chinese government in developing and adjusting industrial structure targets,optimizing resource allocation and advancing industrial structure optimization and upgrade.
文摘The development of measurement geometry for medical X-ray computed tomography (CT) scanners was carried out from the first to the fourth-generation. This concept has also been applied for imaging of industrial processes such as pipe flows or for improving design, operation, optimization and troubleshooting. Nowadays, gamma CT permits to visualize failure equipment points in three-dimensional analysis and in sections of chemical and petrochemical industries. The aim of this work is the development of the mechanical system on a third-generation industrial CT scanner to analyze laboratorial process columns which perform highly efficient separation, turning the ^6oCo, ^75Se, ^137Cs and/or ^192Ir sealed gamma-ray source(s) and the NaI(Tl) multidetector array. It also has a translation movement along the column axis to obtain as many slices of the process flow as needed. The mechanical assembly for this third-generation industrial CT scanner is comprised by strength and rigidity structural frame in stainless and carbon steels, rotating table, source shield and collimator with pneumatic exposure system, spur gear system, translator, rotary stage, drives and stepper motors. The use of suitable spur gears has given a good repeatability and high accuracy in the degree of veracity. The data acquisition boards, mechanical control interfaces, software for movement control and image reconstruction were specially development. A multiphase phantom capable to be setting with solid, liquid and gas was testing. The scanner was setting for 90 views and 19 projections for each detector totalizing 11,970 projections. Experiments to determine the linear attenuation coefficients of the phantom were carried out which applied the Lambert-Beer principle. Results showed that it was possible to distinguish between the phases even the polymethylmethacrylate and the water have very similar density and linear attenuation coefficients. It was established that the newly developed third-generation fan-beam arrangement gamma scanner unit has a good spatial resolution acceptable given the size of the used phantom in this study. The tomografic reconstruction algorithm in used 60 ~ 60 pixels images was the Alternative Minimization (AM) technique and was implemented in MATLAB and VB platforms. The mechanical system presented a good performance in terms of strength, rigidity, accuracy and repeatability with great potential to be used for education or program which dedicated to training chemical and petrochemical industry professionals and for industrial process optimization in Brazil.
文摘Cities are the main material processors asso- ciated with industrialization. The development of urban production based on fossil fuels is the major contributor to the rise of greenhouse gas density, and to global warming. The concept of urban industrial structure optimization is considered to be a solution to urban sustainable develop- ment and global climate issues. Enforcing energy con- servation and reducing carbon emissions are playing key roles in addressing these issues. As such, quantitative accounting and the evaluation of energy consumption and corresponding carbon emissions, which are by-products of urban production, are critical, in order to discover potential opportunities to save energy and to reduce emissions. Conventional evaluation indicators, such as "energy consumption per unit output value" and "emissions per unit output value", are concerned with immediate consumptions and emissions; while the indirect consump- tions and emissions that occur throughout the supply chain are ignored. This does not support the optimization of the overall urban industrial system. To present a systematic evaluation framework for cities, this study constructs new evaluation indicators, based on the concepts of "embodied energy" and "embodied carbon emissions", which take both the immediate and indirect effects of energy consumption and emissions into account. Taking Beijing as a case, conventional evaluation indicators are compared with the newly constructed ones. Results show that the energy consumption and emissions of urban industries are represented better by the new indicators than by conventional indicators, and provide useful information for urban industrial structure optimization.
基金supported by the National Natural Science Foundation of China(grant Nos.22293024,22293021,and 22078330)the Youth Innovation Promotion Association,Chinese Academy of Sciences(grant No.2019050).
文摘Design,scaling-up,and optimization of industrial reactors mainly depend on step-by-step experiments and engineering experience,which is usually time-consuming,high cost,and high risk.Although numerical simulation can reproduce high resolution details of hydrodynamics,thermal transfer,and reaction process in reactors,it is still challenging for industrial reactors due to huge computational cost.In this study,by combining the numerical simulation and artificial intelligence(AI)technology of machine learning(ML),a method is proposed to efficiently predict and optimize the performance of industrial reactors.A gas–solid fluidization reactor for the methanol to olefins process is taken as an example.1500 cases under different conditions are simulated by the coarse-grain discrete particle method based on the Energy-Minimization Multi-Scale model,and thus,the reactor performance data set is constructed.To develop an efficient reactor performance prediction model influenced by multiple factors,the ML method is established including the ensemble learning strategy and automatic hyperparameter optimization technique,which has better performance than the methods based on the artificial neural network.Furthermore,the operating conditions for highest yield of ethylene and propylene or lowest pressure drop are searched with the particle swarm optimization algorithm due to its strength to solve non-linear optimization problems.Results show that decreasing the methanol inflow rate and increasing the catalyst inventory can maximize the yield,while decreasing methanol the inflow rate and reducing the catalyst inventory can minimize the pressure drop.The two objectives are thus conflicting,and the practical operations need to be compromised under different circumstance.
文摘The economic growth pattern in China is changing from high-speed development to high-quality development.In order to promote high-quality economic development,it is necessary to promote the transformation and upgrading of all aspects of social reproduction.Artificial intelligence has promoted high-quality economic development in China from the aspects of innovation effect,technology spillover effect,factor improvement effect,and technology optimization effect.However,there are still several problems in China's Al development,such as the lack of core technologies,privacy and security,as well as the lack of high-tech talents.To this end,China should advance basic theoretical research and key generic technology development to improve the self-reliance of science and technology,as well as optimize the development environment of the industry and improve the relevant laws and regulations as well as the ethical norms system.A system to train high-quality personnel and a mechanism that allows personnel flow should be established to promote high-quality economic development.