The dynamics of calcium(Ca)and magnesium(Mg)in the forest floor and topsoil caused by anthropogenic and natural processes continue to be a concern in temperate forests.However,the impacts of abiotic and biotic variabl...The dynamics of calcium(Ca)and magnesium(Mg)in the forest floor and topsoil caused by anthropogenic and natural processes continue to be a concern in temperate forests.However,the impacts of abiotic and biotic variables as well as their interactions remain unclear,especially in areas undergoing long-term forest restoration.In this study,Ca and Mg concentrations in the forest floor and topsoil from 239 forest plots across the Loess Plateau were measured,and the effects of forest types,climate,soil properties,stand characteristics and nitrogen deposition were explored.The results showed significantly higher Ca concentrations in the forest floor(20.68±8.04 mg/g)than in the topsoil(13.28±12.83 mg/g),whereas Mg exhibited the inverse pattern(3.64±1.09 and 10.11±2.51 mg/g,respectively).The effect of forest types was only significant on forest floor Ca,and Ca concentrations were higher in broadleaf and mixed forests than in coniferous forests.Overall,Ca and Mg concentrations in forest floor and topsoil increased with latitudes while decreased with elevations,and the significance of the trends varied among forest types.Forest floor Ca and Mg were mainly influenced by environmental variables aboveground,i.e.,basal area(BA)and mean annual precipitation(MAP),respectively;topsoil Ca and Mg were more affected by soil properties(soil C/N and pH,respectively).Those suggested a depletion of Ca belowground was associated with forest growth and enriched soil nitrogen,and the leaching of mobile Mg was correlated with rainfall and soil acidification.Besides,the impact of environmental variables on Ca-Mg balance(Ca/Mg ratio)belowground was primarily through the regulation of Ca.Elucidating the influence of environmental variables will improve our ability to predict future changes in base cations and thus forest soil health in the greening vegetated Loess Plateau.展开更多
Nitrogen(N)serves as an essential nutrient for yield formation across diverse crop types.However,agricultural production encounters numerous challenges,notably high N fertilizer rates coupled with low N use efficiency...Nitrogen(N)serves as an essential nutrient for yield formation across diverse crop types.However,agricultural production encounters numerous challenges,notably high N fertilizer rates coupled with low N use efficiency and serious environmental pollution.Deep placement of nitrogen fertilizer(DPNF)is an agronomic measure that shows promise in addressing these issues.This review aims to offer a comprehensive understanding of DPNF,beginning with a succinct overview of its development and methodologies for implementation.Subsequently,the optimal fertilization depth and influencing factors for different crops are analyzed and discussed.Additionally,it investigates the regulation and mechanism underlying the DPNF on crop development,yield,N use efficiency and greenhouse gas emissions.Finally,the review delineates the limitations and challenges of this technology and provides suggestions for its improvement and application.This review provides valuable insight and reference for the promotion and adoption of DPNF in agricultural practice.展开更多
This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital cos...This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.展开更多
Integrated agronomic optimization(IAO)adopts suitable crop varieties,sowing dates,planting density,and advanced nutrient management to redesign the entire production system according to the local environment,and it ca...Integrated agronomic optimization(IAO)adopts suitable crop varieties,sowing dates,planting density,and advanced nutrient management to redesign the entire production system according to the local environment,and it can achieve synergistic improvements in crop yields and resource utilization.However,the intensity and magnitude of the impacts of IAO on soil quality under long-term intensive production and high nitrogen use efficiency(NUE)require further clarification.Based on a 13-year field experiment conducted in Dawenkou,Tai'an,Shadong Province,China,we investigated the effects of four cultivation modes on the grain yield,NUE,and soil aggregate structure,as well as the fraction of organic matter(SOM)and soil quality,reflected by the integrated fertility index(IFI),during the winter wheat maturation periods in 2020–2022.The four cultivation modes were traditional local farming(T1),farmer-based improvement(T2),increased yield regardless of production cost(T3),and integrated soil–crop system management(T4).As the IAO modes,T2 and T4 were characterized by denser planting,reduced nitrogen(N)fertilizer application rates,and delayed sowing compared to T1 and T3,respectively.In this long-term experiment,IAO was found to maintain aggregate stability,increase SOM content(by increasing organic carbon and total nitrogen of the light fraction(LF)and the particulate organic matter fraction(POM)),and improve SOM quality(by increasing the proportions of LF and POM and the ratio of organic carbon to total nitrogen in SOM).Compared to T1,the IFI values of T2,T3,and T4 increased by 10.91,23.38,and 25.55%,and by 17.78,6.41,and 28.94%in the 0–20 and 20–40 cm soil layers,respectively.The grain yield of T4 was 22.52%higher than that of T1,and reached 95.98%of that in T3.Furthermore,the NUE of T4 was 35.61%higher than those of T1 and T3.In conclusion,our results suggest that the IAO mode T4 synergistically increases grain yield and NUE in winter wheat,while maximizing soil quality.展开更多
In order to study the diurnal variation of soil CO2 effiux from temperate meadow steppes in Northeast China, and determine the best time for observation, a field experiment was conducted with a LI-6400 soil CO2 flux s...In order to study the diurnal variation of soil CO2 effiux from temperate meadow steppes in Northeast China, and determine the best time for observation, a field experiment was conducted with a LI-6400 soil CO2 flux system under five typical plant communi- ties （Suaeda glauca （Sg）, Chloris virgata （Cv）, Puecinellia distans （Pd）, Leymus chinensis （Lc） and Phragmites australis （Pa）） and an alkali-spot land （As） at the meadow steppe of western Songnen Plain. The results showed that the diurnal variation of soil CO2 effiux exhibited a single peak curve in the growing season. Diurnal maximum soil respiration （Rs） often appeared between 1 1：00 and 13：00, while the minimum occurred at 21：00-23：00 or before dawn. Air temperature near the soil surface （Ta） and soil temperature at 10 cm depth （Tlo） exerted dominant control on the diurnal variations of soil respiration. The time-windows 7：00-9：00 could be used as the optimal measuring time to represent the daily mean soil CO2 effiux at the Cv, Pd, Lc and Pa sites. The daily mean soil CO2 effiux was close to the soil COz effiux from 15：00 to 17：00 and the mean of 2 individual soil CO2 effiux from 15：00 to 19：00 at the As and Sg sites, respectively. During nocturnal hours, negative soil CO2 fluxes （CO2 downwards into the soil） were frequently observed at the As and Sg sites, the magnitude of the negative CO2 fluxes were 0.10-1.55 gmol/（m2.s） and 0.10-0.69 gmol/（m2.s）at the two sites. The results im- plied that alkaline soils could absorb CO2 under natural condition, which might have significant implications to the global carbon budget accounting.展开更多
Seven types of activated carbon were used to investigate the effect of their structure on separation of CO2 from（H2 ＋ CO2） gas mixture by the adsorption method at ambient temperature and higher pressures. The resul...Seven types of activated carbon were used to investigate the effect of their structure on separation of CO2 from（H2 ＋ CO2） gas mixture by the adsorption method at ambient temperature and higher pressures. The results showed that the limiting factors for separation of CO2 from 53.6 mol% H2 ＋ 46.4 mol% CO2 mixture and from 85.1 mol% H2 ＋ 14.9 mol% CO2 mixture were different at 20 °C and about 2 MPa. The best separation result could be achieved when the pore diameter of the activated carbon ranged from 0.77 to 1.20 nm, and the median particle size was about2.07 lm for 53.6 mol% H2 ＋ 46.4 mol% CO2 mixture and 1.41 lm for 85.1 mol% H2 ＋ 14.9 mol% CO2 mixture. The effect of specific area and pore diameter of activated carbon on separation CO2 from 53.6 mol% H2 ＋ 46.4 mol% CO2 mixture was more significant than that from 85.1 mol% H2 ＋ 14.9 mol% CO2 mixture. CO2 in the gas phase can be decreased from 46.4 mol% to 2.3 mol%–4.3 mol% with a two-stage separation process.展开更多
In Intelligent Transportation Systems(ITS),controlling the trafficflow of a region in a city is the major challenge.Particularly,allocation of the traffic-free route to the taxi drivers during peak hours is one of the ch...In Intelligent Transportation Systems(ITS),controlling the trafficflow of a region in a city is the major challenge.Particularly,allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control the trafficflow.So,in this paper,the route between the taxi driver and pickup location or hotspot with the spatial-temporal dependencies is optimized.Initially,the hotspots in a region are clustered using the density-based spatial clustering of applications with noise(DBSCAN)algorithm tofind the hot spots at the peak hours in an urban area.Then,the optimal route is allocated to the taxi driver to pick up the customer in the hotspot.Before allocating the optimal route,each route between the taxi driver and the hot spot is mapped to the number of taxi drivers.Among the map function,the optimal map is selected using the rain opti-mization algorithm(ROA).If more than one map function is obtained as the opti-mal solution,the map between the route and the taxi driver who has done the least number of trips in the day is chosen as thefinal solution This optimal route selec-tion leads to control of the trafficflow at peak hours.Evaluation of the approach depicts that the proposed trafficflow control scheme reduces traveling time,wait-ing time,fuel consumption,and emission.展开更多
It is a challenge to conserve energy for the large-scale petrochemical enterprises due to complex production process and energy diversification. As critical energy consumption equipment of atmospheric distillation oil...It is a challenge to conserve energy for the large-scale petrochemical enterprises due to complex production process and energy diversification. As critical energy consumption equipment of atmospheric distillation oil refining process, the atmospheric distillation column is paid more attention to save energy. In this paper, the optimal problem of energy utilization efficiency of the atmospheric distillation column is solved by defining a new energy efficiency indicator - the distillation yield rate of unit energy consumption from the perspective of material flow and energy flow, and a soft-sensing model for this new energy efficiency indicator with respect to the multiple working conditions and intelligent optimizing control strategy are suggested for both increasing distillation yield and decreasing energy consumption in oil refining process. It is found that the energy utilization efficiency level of the atmospheric distillation column depends closely on the typical working conditions of the oil refining process, which result by changing the outlet temperature, the overhead temperature, and the bottom liquid level of the atmospheric pressure tower. The fuzzy C-means algorithm is used to classify the typical operation conditions of atmospheric distillation in oil refining process. Furthermore, the LSSVM method optimized with the improved particle swarm optimization is used to model the distillation rate of unit energy consumption. Then online optimization of oil refining process is realized by optimizing the outlet temperature, the overhead temperature with IPSO again. Simulation comparative analyses are made by empirical data to verify the effectiveness of the proposed solution.展开更多
A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably m...A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably mixed with fluctuant and abnormal values. Models established on the basis of the data without data processing can cause misleading results, which cannot be used for the optimal design of hot rolling process. Thus, a method of industrial data processing of C-Mn steel was proposed based on the data analysis. The Bayesian neural network was employed to establish the reliable mechanical property prediction models for the optimal design of hot rolling process. By using the multi-objective optimization algorithm and considering the individual requirements of costumers and the constraints of the equipment, the optimal design of hot rolling process was successfully applied to the rolling process design for Q345B steel with 0.017% Nb and 0.046% Ti content removed. The optimal process design results were in good agreement with the industrial trials results, which verify the effectiveness of the optimal design of hot rolling process.展开更多
The dynamic analysis and optimal design of reactive extraction are challenging due to high nonlinearity of model equations and tough decision of judging criteria. In this work, a dynamic rate-based method is developed...The dynamic analysis and optimal design of reactive extraction are challenging due to high nonlinearity of model equations and tough decision of judging criteria. In this work, a dynamic rate-based method is developed on g PROMS platform to get easy access to the solutions of reactive extraction with phase splitting. Based on rigorous criteria, dynamic analysis from initial state to final equilibrium(e.g., evolution of phase composition, mass transfer rate and reaction rate) and optimal design of operating conditions(e.g., extractant dosage and feed molar ratio) are achieved. To illustrate the method, the esterification of n-hexyl acetate is taken as an example. The approach proves to be reliable in the analysis and optimization of the exemplified system, which provides instructive reference for further process design and simulation of reactive extraction.展开更多
In this paper, a reinforcement learning （RL）-based Sarsa temporal-difference （TD） algorithm is applied tosearch for a unified bidding and operation strategy for a coal-fired power plant with monoethanolamine（MEA...In this paper, a reinforcement learning （RL）-based Sarsa temporal-difference （TD） algorithm is applied tosearch for a unified bidding and operation strategy for a coal-fired power plant with monoethanolamine（MEA）-based post-combustion carbon capture under different carbon dioxide （CO2） allowance market con-ditions. The objective of the decision maker for the power plant is to maximize the discounted cumulativeprofit during the power plant lifetime. Two constraints are considered for the objective formulation. Firstly,the tradeoff between the energy-intensive carbon capture and the electricity generation should be made un-der presumed fixed fuel consumption. Secondly, the CO2 allowances purchased from the CO2 allowance mar-ket should be approximately equal to the quantity of COs emission from power generation. Three case stud-ies are demonstrated thereafter. In the first case, we show the convergence of the Sarsa TD algorithm andfind a deterministic optimal bidding and operation strategy. In the second case, compared with the inde-pendently designed operation and bidding strategies discussed in most of the relevant literature, the SarsaTD-based unified bidding and operation strategy with time-varying flexible market-oriented CO2 capturelevels is demonstrated to help the power plant decision maker gain a higher discounted cumulative profit.In the third case, a competitor operating another power plant identical to the preceding plant is consideredunder the same CO2 allowance market. The competitor also has carbon capture facilities but applies a differ-ent strategy to earn profits. The discounted cumulative profits of the two power plants are then compared,thus exhibiting the competitiveness of the power plant that is using the unified bidding and operation strat-egy explored by the Sarsa TD algorithm.展开更多
基金supported by the National Natural Science Foundation of China(42401054)Natural Science Foundation of Hebei Province(D2024205019)Science and Technology Project of Hebei Education Department(BJ2025014).
文摘The dynamics of calcium(Ca)and magnesium(Mg)in the forest floor and topsoil caused by anthropogenic and natural processes continue to be a concern in temperate forests.However,the impacts of abiotic and biotic variables as well as their interactions remain unclear,especially in areas undergoing long-term forest restoration.In this study,Ca and Mg concentrations in the forest floor and topsoil from 239 forest plots across the Loess Plateau were measured,and the effects of forest types,climate,soil properties,stand characteristics and nitrogen deposition were explored.The results showed significantly higher Ca concentrations in the forest floor(20.68±8.04 mg/g)than in the topsoil(13.28±12.83 mg/g),whereas Mg exhibited the inverse pattern(3.64±1.09 and 10.11±2.51 mg/g,respectively).The effect of forest types was only significant on forest floor Ca,and Ca concentrations were higher in broadleaf and mixed forests than in coniferous forests.Overall,Ca and Mg concentrations in forest floor and topsoil increased with latitudes while decreased with elevations,and the significance of the trends varied among forest types.Forest floor Ca and Mg were mainly influenced by environmental variables aboveground,i.e.,basal area(BA)and mean annual precipitation(MAP),respectively;topsoil Ca and Mg were more affected by soil properties(soil C/N and pH,respectively).Those suggested a depletion of Ca belowground was associated with forest growth and enriched soil nitrogen,and the leaching of mobile Mg was correlated with rainfall and soil acidification.Besides,the impact of environmental variables on Ca-Mg balance(Ca/Mg ratio)belowground was primarily through the regulation of Ca.Elucidating the influence of environmental variables will improve our ability to predict future changes in base cations and thus forest soil health in the greening vegetated Loess Plateau.
基金funded by grants from the National Natural Science Foundation of China(32301947,32272220 and 32172120)the China Postdoctoral Science Foundation(2023M730909).
文摘Nitrogen(N)serves as an essential nutrient for yield formation across diverse crop types.However,agricultural production encounters numerous challenges,notably high N fertilizer rates coupled with low N use efficiency and serious environmental pollution.Deep placement of nitrogen fertilizer(DPNF)is an agronomic measure that shows promise in addressing these issues.This review aims to offer a comprehensive understanding of DPNF,beginning with a succinct overview of its development and methodologies for implementation.Subsequently,the optimal fertilization depth and influencing factors for different crops are analyzed and discussed.Additionally,it investigates the regulation and mechanism underlying the DPNF on crop development,yield,N use efficiency and greenhouse gas emissions.Finally,the review delineates the limitations and challenges of this technology and provides suggestions for its improvement and application.This review provides valuable insight and reference for the promotion and adoption of DPNF in agricultural practice.
文摘This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.
基金jointly supported by the Key Research and Development Program of Shandong Province,China(LJNY202103 and 2023TZXD086)the National Major Agricultural Science and Technology Project,China(NK202218080315)+1 种基金the Project of Central Government Guiding Local Science and Technology Development,China(YDZX2022130)the Cooperative Promotion Plan of Major Agricultural Technologies of Shandong Province,China(SDNYXTTG-2023-10)。
文摘Integrated agronomic optimization(IAO)adopts suitable crop varieties,sowing dates,planting density,and advanced nutrient management to redesign the entire production system according to the local environment,and it can achieve synergistic improvements in crop yields and resource utilization.However,the intensity and magnitude of the impacts of IAO on soil quality under long-term intensive production and high nitrogen use efficiency(NUE)require further clarification.Based on a 13-year field experiment conducted in Dawenkou,Tai'an,Shadong Province,China,we investigated the effects of four cultivation modes on the grain yield,NUE,and soil aggregate structure,as well as the fraction of organic matter(SOM)and soil quality,reflected by the integrated fertility index(IFI),during the winter wheat maturation periods in 2020–2022.The four cultivation modes were traditional local farming(T1),farmer-based improvement(T2),increased yield regardless of production cost(T3),and integrated soil–crop system management(T4).As the IAO modes,T2 and T4 were characterized by denser planting,reduced nitrogen(N)fertilizer application rates,and delayed sowing compared to T1 and T3,respectively.In this long-term experiment,IAO was found to maintain aggregate stability,increase SOM content(by increasing organic carbon and total nitrogen of the light fraction(LF)and the particulate organic matter fraction(POM)),and improve SOM quality(by increasing the proportions of LF and POM and the ratio of organic carbon to total nitrogen in SOM).Compared to T1,the IFI values of T2,T3,and T4 increased by 10.91,23.38,and 25.55%,and by 17.78,6.41,and 28.94%in the 0–20 and 20–40 cm soil layers,respectively.The grain yield of T4 was 22.52%higher than that of T1,and reached 95.98%of that in T3.Furthermore,the NUE of T4 was 35.61%higher than those of T1 and T3.In conclusion,our results suggest that the IAO mode T4 synergistically increases grain yield and NUE in winter wheat,while maximizing soil quality.
基金Under the auspices of National Natural Science Foundation of China(No.41501090,41501105)Fundamental Research Funds for Central Universities(No.2412015KJ023)
文摘In order to study the diurnal variation of soil CO2 effiux from temperate meadow steppes in Northeast China, and determine the best time for observation, a field experiment was conducted with a LI-6400 soil CO2 flux system under five typical plant communi- ties （Suaeda glauca （Sg）, Chloris virgata （Cv）, Puecinellia distans （Pd）, Leymus chinensis （Lc） and Phragmites australis （Pa）） and an alkali-spot land （As） at the meadow steppe of western Songnen Plain. The results showed that the diurnal variation of soil CO2 effiux exhibited a single peak curve in the growing season. Diurnal maximum soil respiration （Rs） often appeared between 1 1：00 and 13：00, while the minimum occurred at 21：00-23：00 or before dawn. Air temperature near the soil surface （Ta） and soil temperature at 10 cm depth （Tlo） exerted dominant control on the diurnal variations of soil respiration. The time-windows 7：00-9：00 could be used as the optimal measuring time to represent the daily mean soil CO2 effiux at the Cv, Pd, Lc and Pa sites. The daily mean soil CO2 effiux was close to the soil COz effiux from 15：00 to 17：00 and the mean of 2 individual soil CO2 effiux from 15：00 to 19：00 at the As and Sg sites, respectively. During nocturnal hours, negative soil CO2 fluxes （CO2 downwards into the soil） were frequently observed at the As and Sg sites, the magnitude of the negative CO2 fluxes were 0.10-1.55 gmol/（m2.s） and 0.10-0.69 gmol/（m2.s）at the two sites. The results im- plied that alkaline soils could absorb CO2 under natural condition, which might have significant implications to the global carbon budget accounting.
基金the Talent Scientific Research Fund of LSHU (No. 2016XJJ-015)the fund of the Liaoning Provincial Department of Education (No. L2017LQN005)the National Natural Science Foundation of China (No. 21606120)
文摘Seven types of activated carbon were used to investigate the effect of their structure on separation of CO2 from（H2 ＋ CO2） gas mixture by the adsorption method at ambient temperature and higher pressures. The results showed that the limiting factors for separation of CO2 from 53.6 mol% H2 ＋ 46.4 mol% CO2 mixture and from 85.1 mol% H2 ＋ 14.9 mol% CO2 mixture were different at 20 °C and about 2 MPa. The best separation result could be achieved when the pore diameter of the activated carbon ranged from 0.77 to 1.20 nm, and the median particle size was about2.07 lm for 53.6 mol% H2 ＋ 46.4 mol% CO2 mixture and 1.41 lm for 85.1 mol% H2 ＋ 14.9 mol% CO2 mixture. The effect of specific area and pore diameter of activated carbon on separation CO2 from 53.6 mol% H2 ＋ 46.4 mol% CO2 mixture was more significant than that from 85.1 mol% H2 ＋ 14.9 mol% CO2 mixture. CO2 in the gas phase can be decreased from 46.4 mol% to 2.3 mol%–4.3 mol% with a two-stage separation process.
文摘In Intelligent Transportation Systems(ITS),controlling the trafficflow of a region in a city is the major challenge.Particularly,allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control the trafficflow.So,in this paper,the route between the taxi driver and pickup location or hotspot with the spatial-temporal dependencies is optimized.Initially,the hotspots in a region are clustered using the density-based spatial clustering of applications with noise(DBSCAN)algorithm tofind the hot spots at the peak hours in an urban area.Then,the optimal route is allocated to the taxi driver to pick up the customer in the hotspot.Before allocating the optimal route,each route between the taxi driver and the hot spot is mapped to the number of taxi drivers.Among the map function,the optimal map is selected using the rain opti-mization algorithm(ROA).If more than one map function is obtained as the opti-mal solution,the map between the route and the taxi driver who has done the least number of trips in the day is chosen as thefinal solution This optimal route selec-tion leads to control of the trafficflow at peak hours.Evaluation of the approach depicts that the proposed trafficflow control scheme reduces traveling time,wait-ing time,fuel consumption,and emission.
基金Supported by the High-tech Research and Development Program of China(2014AA041802)
文摘It is a challenge to conserve energy for the large-scale petrochemical enterprises due to complex production process and energy diversification. As critical energy consumption equipment of atmospheric distillation oil refining process, the atmospheric distillation column is paid more attention to save energy. In this paper, the optimal problem of energy utilization efficiency of the atmospheric distillation column is solved by defining a new energy efficiency indicator - the distillation yield rate of unit energy consumption from the perspective of material flow and energy flow, and a soft-sensing model for this new energy efficiency indicator with respect to the multiple working conditions and intelligent optimizing control strategy are suggested for both increasing distillation yield and decreasing energy consumption in oil refining process. It is found that the energy utilization efficiency level of the atmospheric distillation column depends closely on the typical working conditions of the oil refining process, which result by changing the outlet temperature, the overhead temperature, and the bottom liquid level of the atmospheric pressure tower. The fuzzy C-means algorithm is used to classify the typical operation conditions of atmospheric distillation in oil refining process. Furthermore, the LSSVM method optimized with the improved particle swarm optimization is used to model the distillation rate of unit energy consumption. Then online optimization of oil refining process is realized by optimizing the outlet temperature, the overhead temperature with IPSO again. Simulation comparative analyses are made by empirical data to verify the effectiveness of the proposed solution.
文摘A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably mixed with fluctuant and abnormal values. Models established on the basis of the data without data processing can cause misleading results, which cannot be used for the optimal design of hot rolling process. Thus, a method of industrial data processing of C-Mn steel was proposed based on the data analysis. The Bayesian neural network was employed to establish the reliable mechanical property prediction models for the optimal design of hot rolling process. By using the multi-objective optimization algorithm and considering the individual requirements of costumers and the constraints of the equipment, the optimal design of hot rolling process was successfully applied to the rolling process design for Q345B steel with 0.017% Nb and 0.046% Ti content removed. The optimal process design results were in good agreement with the industrial trials results, which verify the effectiveness of the optimal design of hot rolling process.
基金Supported by the National Natural Science Foundation of China(21776074,21576081,2181101120).
文摘The dynamic analysis and optimal design of reactive extraction are challenging due to high nonlinearity of model equations and tough decision of judging criteria. In this work, a dynamic rate-based method is developed on g PROMS platform to get easy access to the solutions of reactive extraction with phase splitting. Based on rigorous criteria, dynamic analysis from initial state to final equilibrium(e.g., evolution of phase composition, mass transfer rate and reaction rate) and optimal design of operating conditions(e.g., extractant dosage and feed molar ratio) are achieved. To illustrate the method, the esterification of n-hexyl acetate is taken as an example. The approach proves to be reliable in the analysis and optimization of the exemplified system, which provides instructive reference for further process design and simulation of reactive extraction.
文摘In this paper, a reinforcement learning （RL）-based Sarsa temporal-difference （TD） algorithm is applied tosearch for a unified bidding and operation strategy for a coal-fired power plant with monoethanolamine（MEA）-based post-combustion carbon capture under different carbon dioxide （CO2） allowance market con-ditions. The objective of the decision maker for the power plant is to maximize the discounted cumulativeprofit during the power plant lifetime. Two constraints are considered for the objective formulation. Firstly,the tradeoff between the energy-intensive carbon capture and the electricity generation should be made un-der presumed fixed fuel consumption. Secondly, the CO2 allowances purchased from the CO2 allowance mar-ket should be approximately equal to the quantity of COs emission from power generation. Three case stud-ies are demonstrated thereafter. In the first case, we show the convergence of the Sarsa TD algorithm andfind a deterministic optimal bidding and operation strategy. In the second case, compared with the inde-pendently designed operation and bidding strategies discussed in most of the relevant literature, the SarsaTD-based unified bidding and operation strategy with time-varying flexible market-oriented CO2 capturelevels is demonstrated to help the power plant decision maker gain a higher discounted cumulative profit.In the third case, a competitor operating another power plant identical to the preceding plant is consideredunder the same CO2 allowance market. The competitor also has carbon capture facilities but applies a differ-ent strategy to earn profits. The discounted cumulative profits of the two power plants are then compared,thus exhibiting the competitiveness of the power plant that is using the unified bidding and operation strat-egy explored by the Sarsa TD algorithm.
