基于Teamcenter Process Simulate进行了印章定制生产线仿真设计。本设计是完成印章的组装和包装工作,模拟实际生产过程。整个生产过程是由仓储供料站提供原料,运输站将其送至加工站加工,送至装配站进行组装,组装完后经过机器进行检测,...基于Teamcenter Process Simulate进行了印章定制生产线仿真设计。本设计是完成印章的组装和包装工作,模拟实际生产过程。整个生产过程是由仓储供料站提供原料,运输站将其送至加工站加工,送至装配站进行组装,组装完后经过机器进行检测,然后送至包装台进行产品包装,最后由AGV小车运输至仓储放料台进行产品入库。设计以出料、运送物料、产品加工、组装、检测、包装、运送、入库等执行单元作为自动生产线的整体设计,组成了自动生产线的生产平台。系统的总控是由一台PLC承担其控制任务。结合工作中的经验,通过机电一体化设计将生产流水线设计方案嵌入到具体的Process Simulate虚拟仿真中,通过PLCSIM Advanced软件创建虚拟PLC,同时构建PLC与Process Simulate通信的桥梁,进而通过编程控制实现印章定制化生产实训系统自动化产线的仿真调试。通过仿真测试,能大大提高实际生产效率。展开更多
Sequential-modular-based process flowsheeting software remains an indispensable tool for process design,control,and optimization.Yet,as the process industry advances in intelligent operation and maintenance,convention...Sequential-modular-based process flowsheeting software remains an indispensable tool for process design,control,and optimization.Yet,as the process industry advances in intelligent operation and maintenance,conventional sequential-modular-based process-simulation techniques present challenges regarding computationally intensive calculations and significant central processing unit(CPU)time requirements,particularly in large-scale design and optimization tasks.To address these challenges,this paper proposes a novel process-simulation parallel computing framework(PSPCF).This framework achieves layered parallelism in recycling processes at the unit operation level.Notably,PSPCF introduces a groundbreaking concept of formulating simulation problems as task graphs and utilizes Taskflow,an advanced task graph computing system,for hierarchical parallel scheduling and the execution of unit operation tasks.PSPCF also integrates an advanced work-stealing scheme to automatically balance thread resources with the demanding workload of unit operation tasks.For evaluation,both a simpler parallel column process and a more complex cracked gas separation process were simulated on a flowsheeting platform using PSPCF.The framework demonstrates significant time savings,achieving over 60%reduction in processing time for the simpler process and a 35%–40%speed-up for the more complex separation process.展开更多
Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured a...Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.展开更多
Ammonia(NH_(3))emission has caused serious environment issues and aroused worldwide concern.The emerging ionic liquid(IL)provides a greener way to efficiently capture NH_(3).This paper provides rigorous process simula...Ammonia(NH_(3))emission has caused serious environment issues and aroused worldwide concern.The emerging ionic liquid(IL)provides a greener way to efficiently capture NH_(3).This paper provides rigorous process simulation,optimization and assessment for a novel NH_(3)deep purification process using IL.The process was designed and investigated by simulation and optimization using ionic liquid[C_(4)im][NTF_(2)]as absorbent.Three objective functions,total purification cost(TPC),total process CO_(2)emission(TPCOE)and thermal efficiency(ηeff)were employed to optimize the absorption process.Process simulation and optimization results indicate that at same purification standard and recovery rate,the novel process can achieve lower cost and CO_(2)emission compared to benchmark process.After process optimization,the optimal functions can achieve 0.02726$/Nm~3(TPC),311.27 kg CO_(2)/hr(TP-COE),and 52.21%(ηeff)for enhanced process.Moreover,compared with conventional process,novel process could decrease over$3 million of purification cost and 10000 tons of CO_(2)emission during the life cycle.The results provide a novel strategy and guidance for deep purification of NH_(3)capture.展开更多
Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However...Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.展开更多
In response to the lack of reliable physical parameters in the process simulation of the butadiene extraction,a large amount of phase equilibrium data were collected in the context of the actual process of butadiene p...In response to the lack of reliable physical parameters in the process simulation of the butadiene extraction,a large amount of phase equilibrium data were collected in the context of the actual process of butadiene production by acetonitrile.The accuracy of five prediction methods,UNIFAC(UNIQUAC Functional-group Activity Coefficients),UNIFAC-LL,UNIFAC-LBY,UNIFAC-DMD and COSMO-RS,applied to the butadiene extraction process was verified using partial phase equilibrium data.The results showed that the UNIFAC-DMD method had the highest accuracy in predicting phase equilibrium data for the missing system.COSMO-RS-predicted multiple systems showed good accuracy,and a large number of missing phase equilibrium data were estimated using the UNIFAC-DMD method and COSMO-RS method.The predicted phase equilibrium data were checked for consistency.The NRTL-RK(non-Random Two Liquid-Redlich-Kwong Equation of State)and UNIQUAC thermodynamic models were used to correlate the phase equilibrium data.Industrial device simulations were used to verify the accuracy of the thermodynamic model applied to the butadiene extraction process.The simulation results showed that the average deviations of the simulated results using the correlated thermodynamic model from the actual values were less than 2%compared to that using the commercial simulation software,Aspen Plus and its database.The average deviation was much smaller than that of the simulations using the Aspen Plus database(>10%),indicating that the obtained phase equilibrium data are highly accurate and reliable.The best phase equilibrium data and thermodynamic model parameters for butadiene extraction are provided.This improves the accuracy and reliability of the design,optimization and control of the process,and provides a basis and guarantee for developing a more environmentally friendly and economical butadiene extraction process.展开更多
Simulations of photoresist etching,aerial image,exposure,and post-bake processes are integrated to obtain a photolithography process simulation for microelectromechanical system（MEMS） and integrated circuit（IC） fa...Simulations of photoresist etching,aerial image,exposure,and post-bake processes are integrated to obtain a photolithography process simulation for microelectromechanical system（MEMS） and integrated circuit（IC） fabrication based on three-dimensional （3D） cellular automata（CA）. The simulation results agree well with available experimental results. This indicates that the 3D dynamic CA model for the photoresist etching simulation and the 3D CA model for the post-bake simulation could be useful for the monolithic simulation of various lithography processes. This is determined to be useful for the device-sized fabrication process simulation of IC and MEMS.展开更多
Catalytic amine-solvent regeneration has been validated as an energy-saving strategy for CO_(2) chemisorption by boosting reaction kinetics under mild conditions.The upscale performance evaluation and longterm durabil...Catalytic amine-solvent regeneration has been validated as an energy-saving strategy for CO_(2) chemisorption by boosting reaction kinetics under mild conditions.The upscale performance evaluation and longterm durability are indispensable steps for industrial application but have been scarcely reported thus far.Here,we report a ZrO_(2)/Al_(2)O_(3) pack catalyst that possesses strong metal oxide-support interactions,a porous structure,active and stable Zr-O-Al coordination,promoted proton transfer and a 40.7% decrease in the energy activation of carbamate decomposition,which significantly accelerates CO_(2) desorption kinetics.The upscale experiment and cost evaluation based on industrial flue gas revealed that the use of packing catalysts can reduce energy consumption by 27.56% and optimize the overall cost by 10.49%.The active sites present excellent stability in alkaline solvents.This work is the first to investigate the ability of high-technology readiness(technology readiness level at 6(TRL 6))for catalytic aminesolvent regeneration,providing valuable insights for potential applications involving efficient CO_(2) capture with catalyst assistance.展开更多
基金supported by the National Key Research and Development Program of China(2022YFB3305900)the National Natural Science Foundation of China(Key Program)(62136003)+2 种基金the National Natural Science Foundation of China(62394345)the Major Science and Technology Projects of Longmen Laboratory(LMZDXM202206)the Fundamental Research Funds for the Central Universities.
文摘Sequential-modular-based process flowsheeting software remains an indispensable tool for process design,control,and optimization.Yet,as the process industry advances in intelligent operation and maintenance,conventional sequential-modular-based process-simulation techniques present challenges regarding computationally intensive calculations and significant central processing unit(CPU)time requirements,particularly in large-scale design and optimization tasks.To address these challenges,this paper proposes a novel process-simulation parallel computing framework(PSPCF).This framework achieves layered parallelism in recycling processes at the unit operation level.Notably,PSPCF introduces a groundbreaking concept of formulating simulation problems as task graphs and utilizes Taskflow,an advanced task graph computing system,for hierarchical parallel scheduling and the execution of unit operation tasks.PSPCF also integrates an advanced work-stealing scheme to automatically balance thread resources with the demanding workload of unit operation tasks.For evaluation,both a simpler parallel column process and a more complex cracked gas separation process were simulated on a flowsheeting platform using PSPCF.The framework demonstrates significant time savings,achieving over 60%reduction in processing time for the simpler process and a 35%–40%speed-up for the more complex separation process.
文摘Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.
基金supported by the National Natural Science Foundation of China (Nos.21890760 and 21838010)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (No.21921005)the International (Regional)Cooperation and Exchange of the National Natural Science Foundation of China (No.21961160744)。
文摘Ammonia(NH_(3))emission has caused serious environment issues and aroused worldwide concern.The emerging ionic liquid(IL)provides a greener way to efficiently capture NH_(3).This paper provides rigorous process simulation,optimization and assessment for a novel NH_(3)deep purification process using IL.The process was designed and investigated by simulation and optimization using ionic liquid[C_(4)im][NTF_(2)]as absorbent.Three objective functions,total purification cost(TPC),total process CO_(2)emission(TPCOE)and thermal efficiency(ηeff)were employed to optimize the absorption process.Process simulation and optimization results indicate that at same purification standard and recovery rate,the novel process can achieve lower cost and CO_(2)emission compared to benchmark process.After process optimization,the optimal functions can achieve 0.02726$/Nm~3(TPC),311.27 kg CO_(2)/hr(TP-COE),and 52.21%(ηeff)for enhanced process.Moreover,compared with conventional process,novel process could decrease over$3 million of purification cost and 10000 tons of CO_(2)emission during the life cycle.The results provide a novel strategy and guidance for deep purification of NH_(3)capture.
基金the financial support from the Strategic Priority Research Program of Chinese Academy of Sciences(XDA21010100)。
文摘Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.
基金supported by the National Natural Science Foundation of China(22178190)。
文摘In response to the lack of reliable physical parameters in the process simulation of the butadiene extraction,a large amount of phase equilibrium data were collected in the context of the actual process of butadiene production by acetonitrile.The accuracy of five prediction methods,UNIFAC(UNIQUAC Functional-group Activity Coefficients),UNIFAC-LL,UNIFAC-LBY,UNIFAC-DMD and COSMO-RS,applied to the butadiene extraction process was verified using partial phase equilibrium data.The results showed that the UNIFAC-DMD method had the highest accuracy in predicting phase equilibrium data for the missing system.COSMO-RS-predicted multiple systems showed good accuracy,and a large number of missing phase equilibrium data were estimated using the UNIFAC-DMD method and COSMO-RS method.The predicted phase equilibrium data were checked for consistency.The NRTL-RK(non-Random Two Liquid-Redlich-Kwong Equation of State)and UNIQUAC thermodynamic models were used to correlate the phase equilibrium data.Industrial device simulations were used to verify the accuracy of the thermodynamic model applied to the butadiene extraction process.The simulation results showed that the average deviations of the simulated results using the correlated thermodynamic model from the actual values were less than 2%compared to that using the commercial simulation software,Aspen Plus and its database.The average deviation was much smaller than that of the simulations using the Aspen Plus database(>10%),indicating that the obtained phase equilibrium data are highly accurate and reliable.The best phase equilibrium data and thermodynamic model parameters for butadiene extraction are provided.This improves the accuracy and reliability of the design,optimization and control of the process,and provides a basis and guarantee for developing a more environmentally friendly and economical butadiene extraction process.
文摘Simulations of photoresist etching,aerial image,exposure,and post-bake processes are integrated to obtain a photolithography process simulation for microelectromechanical system（MEMS） and integrated circuit（IC） fabrication based on three-dimensional （3D） cellular automata（CA）. The simulation results agree well with available experimental results. This indicates that the 3D dynamic CA model for the photoresist etching simulation and the 3D CA model for the post-bake simulation could be useful for the monolithic simulation of various lithography processes. This is determined to be useful for the device-sized fabrication process simulation of IC and MEMS.
基金supported by the National Natural Science Foundation of China(52300134 and 22106084)the China Postdoctoral Science Foundation(2022TQ0175,2023M741931,and 2022T150350).
文摘Catalytic amine-solvent regeneration has been validated as an energy-saving strategy for CO_(2) chemisorption by boosting reaction kinetics under mild conditions.The upscale performance evaluation and longterm durability are indispensable steps for industrial application but have been scarcely reported thus far.Here,we report a ZrO_(2)/Al_(2)O_(3) pack catalyst that possesses strong metal oxide-support interactions,a porous structure,active and stable Zr-O-Al coordination,promoted proton transfer and a 40.7% decrease in the energy activation of carbamate decomposition,which significantly accelerates CO_(2) desorption kinetics.The upscale experiment and cost evaluation based on industrial flue gas revealed that the use of packing catalysts can reduce energy consumption by 27.56% and optimize the overall cost by 10.49%.The active sites present excellent stability in alkaline solvents.This work is the first to investigate the ability of high-technology readiness(technology readiness level at 6(TRL 6))for catalytic aminesolvent regeneration,providing valuable insights for potential applications involving efficient CO_(2) capture with catalyst assistance.
