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Energy-saving design and optimization of pressure-swing-assisted ternary heterogenous azeotropic distillations
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作者 Lianjie Wu Kun Lu +3 位作者 Qirui Li Lianghua Xu Yiqing Luo Xigang Yuan 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第4期1-7,共7页
A huge amount of energy is always consumed to separate the ternary azeotropic mixtures by distillations.The heterogeneous azeotropic distillation and the pressure-swing distillation are two kinds of effective technolo... A huge amount of energy is always consumed to separate the ternary azeotropic mixtures by distillations.The heterogeneous azeotropic distillation and the pressure-swing distillation are two kinds of effective technologies to separate heterogeneous azeotropes without entrainer addition.To give better play to the synergistic energy-saving effect of these two processes,a novel pressure-swing-assisted ternary heterogeneous azeotropic distillation(THAD)process is proposed firstly.In this process,the ternary heterogeneous azeotrope is decanted into two liquid phases before being refluxed into the azeotropic distillation column to avoid the aqueous phase remixing,and three columns'pressures are modified to decrease the flowrates of the recycle streams.Then the dividing wall column and heat integration technologies are introduced to further reduce its energy consumption,and the pressureswing-assisted ternary heterogeneous azeotropic dividing-wall column and its heat integration structure are achieved.A genetic algorithm procedure is used to optimize the proposed processes.The design results show that the proposed processes have higher energy efficiencies and lower CO_(2)emissions than the published THAD process. 展开更多
关键词 DISTILLATION SEPARATION Process control Process systems
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Reinforcement Learning in Process Industries:Review and Perspective
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作者 Oguzhan Dogru Junyao Xie +6 位作者 Om Prakash Ranjith Chiplunkar Jansen Soesanto Hongtian Chen Kirubakaran Velswamy Fadi Ibrahim Biao Huang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第2期283-300,共18页
This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control ... This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries. 展开更多
关键词 Process control process systems engineering reinforcement learning
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APPLICATION OF MVP IN REAL TIME IMAGE PROCESSING
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作者 戴擎宇 杨占昕 何佩琨 《Chinese Journal of Aeronautics》 SCIE EI CSCD 2000年第1期30-33,共4页
MVP is a digital signal processor, which is of MIMD structure and fit for multimedia application. MVP has several processors in it, and its operation is characteristic of parallelism and pipeline; therefore, real-time... MVP is a digital signal processor, which is of MIMD structure and fit for multimedia application. MVP has several processors in it, and its operation is characteristic of parallelism and pipeline; therefore, real-time signal processing can be done on it. This paper presents the image processing system based on MVP, explains the principles of parallel task assignment and hardware pipeline design, and gives out the example of target tracking and edge detection. 展开更多
关键词 Computer hardware Edge detection Image processing MIM devices Multimedia systems Parallel processing systems Random access storage
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FUNDAMENTAL COMMUNICATIONS THEORIES AND SIGNAL PROCESSING TECHNIQUES FOR AMORPHOUS CELLULAR SYSTEMS
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作者 Shi Jin Feifei Gao +2 位作者 Kai Luo Yongming Huang Wei Peng 《China Communications》 SCIE CSCD 2016年第12期I0002-I0003,共2页
The rapid developing of the fourth generation(4G)wireless communications has aroused tremendous demands for high speed data transmission due to the dissemination of various types of the intelligent user terminals as w... The rapid developing of the fourth generation(4G)wireless communications has aroused tremendous demands for high speed data transmission due to the dissemination of various types of the intelligent user terminals as well as the wireless multi-media services.It is predicted that the network throughput will increase 展开更多
关键词 IEEE FBMC FUNDAMENTAL COMMUNICATIONS THEORIES AND SIGNAL processing TECHNIQUES FOR AMORPHOUS CELLULAR SYSTEMS MIMO FIR
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Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability
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作者 张弛 刘利伟 +2 位作者 王龙飞 岳园 俞连春 《Chinese Physics Letters》 SCIE CAS CSCD 2015年第11期5-8,共4页
Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biolo... Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array's energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection. 展开更多
关键词 In Optimal Size for Maximal Energy Efficiency in Information processing of Biological Systems Due to Bistability
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Attention-based long short-term memory fully convolutional network for chemical process fault diagnosis 被引量:4
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作者 Shanwei Xiong Li Zhou +1 位作者 Yiyang Dai Xu Ji 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2023年第4期1-14,共14页
A correct and timely fault diagnosis is important for improving the safety and reliability of chemical processes. With the advancement of big data technology, data-driven fault diagnosis methods are being extensively ... A correct and timely fault diagnosis is important for improving the safety and reliability of chemical processes. With the advancement of big data technology, data-driven fault diagnosis methods are being extensively used and still have considerable potential. In recent years, methods based on deep neural networks have made significant breakthroughs, and fault diagnosis methods for industrial processes based on deep learning have attracted considerable research attention. Therefore, we propose a fusion deeplearning algorithm based on a fully convolutional neural network(FCN) to extract features and build models to correctly diagnose all types of faults. We use long short-term memory(LSTM) units to expand our proposed FCN so that our proposed deep learning model can better extract the time-domain features of chemical process data. We also introduce the attention mechanism into the model, aimed at highlighting the importance of features, which is significant for the fault diagnosis of chemical processes with many features. When applied to the benchmark Tennessee Eastman process, our proposed model exhibits impressive performance, demonstrating the effectiveness of the attention-based LSTM FCN in chemical process fault diagnosis. 展开更多
关键词 Safety Fault diagnosis Process systems Long short-term memory Attention mechanism Neural networks
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Data-driven intelligent modeling framework for the steam cracking process 被引量:1
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作者 Qiming Zhao Kexin Bi Tong Qiu 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2023年第9期237-247,共11页
Steam cracking is the dominant technology for producing light olefins,which are believed to be the foundation of the chemical industry.Predictive models of the cracking process can boost production efficiency and prof... Steam cracking is the dominant technology for producing light olefins,which are believed to be the foundation of the chemical industry.Predictive models of the cracking process can boost production efficiency and profit margin.Rapid advancements in machine learning research have recently enabled data-driven solutions to usher in a new era of process modeling.Meanwhile,its practical application to steam cracking is still hindered by the trade-off between prediction accuracy and computational speed.This research presents a framework for data-driven intelligent modeling of the steam cracking process.Industrial data preparation and feature engineering techniques provide computational-ready datasets for the framework,and feedstock similarities are exploited using k-means clustering.We propose LArge-Residuals-Deletion Multivariate Adaptive Regression Spline(LARD-MARS),a modeling approach that explicitly generates output formulas and eliminates potentially outlying instances.The framework is validated further by the presentation of clustering results,the explanation of variable importance,and the testing and comparison of model performance. 展开更多
关键词 Mathematical modeling Data-driven modeling Process systems Steam cracking CLUSTERING Multivariate adaptive regression spline
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Early identification of process deviation based on convolutional neural network
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作者 Fangyuan Ma Cheng Ji +1 位作者 Jingde Wang Wei Sun 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2023年第4期104-118,共15页
A novel process monitoring method based on convolutional neural network(CNN)is proposed and applied to detect faults in industrial process.By utilizing the CNN algorithm,cross-correlation and autocorrelation among var... A novel process monitoring method based on convolutional neural network(CNN)is proposed and applied to detect faults in industrial process.By utilizing the CNN algorithm,cross-correlation and autocorrelation among variables are captured to establish a prediction model for each process variable to approximate the first-principle of physical/chemical relationships among different variables under normal operating conditions.When the process is operated under pre-set operating conditions,prediction residuals can be assumed as noise if a proper model is employed.Once process faults occur,the residuals will increase due to the changes of correlation among variables.A principal component analysis(PCA)model based on the residuals is established to realize process monitoring.By monitoring the changes in main feature of prediction residuals,the faults can be promptly detected.Case studies on a numerical nonlinear example and data from two industrial processes are presented to validate the performance of process monitoring based on CNN. 展开更多
关键词 Process monitoring RESIDUAL Principal component analysis Process systems Systems engineering
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Cascade refrigeration system synthesis based on hybrid simulated annealing and particle swarm optimization algorithm
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作者 Danlei Chen Yiqing Luo Xigang Yuan 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2023年第6期244-255,共12页
Cascade refrigeration system(CRS)can meet a wider range of refrigeration temperature requirements and is more energy efficient than single-refrigerant refrigeration system,making it more widely used in low-temperature... Cascade refrigeration system(CRS)can meet a wider range of refrigeration temperature requirements and is more energy efficient than single-refrigerant refrigeration system,making it more widely used in low-temperature industry processes.The synthesis of a CRS with simultaneous consideration of heat integration between refrigerant and process streams is challenging but promising for significant cost saving and reduction of carbon emission.This study presented a stochastic optimization method for the synthesis of CRS.An MINLP model was formulated based on the superstructure developed for the CRS,and an optimization framework was proposed,where simulated annealing algorithm was used to evolve the numbers of pressure/temperature levels for all sub-refrigeration systems,and particle swarm optimization algorithm was employed to optimize the continuous variables.The effectiveness of the proposed methodology was verified by a case study of CRS optimization in an ethylene plant with 21.89%the total annual cost saving. 展开更多
关键词 Optimal design Process systems Particle swarm optimization Simulated annealing Mathematical modeling
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A dynamic-inner LSTM prediction method for key alarm variables forecasting in chemical process
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作者 Yiming Bai Shuaiyu Xiang +1 位作者 Feifan Cheng Jinsong Zhao 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2023年第3期266-276,共11页
With the increase in the complexity of industrial system, simply detecting and diagnosing a fault may be insufficient in some cases, and prognosing the fault ahead of time could have a certain necessity. Accurate pred... With the increase in the complexity of industrial system, simply detecting and diagnosing a fault may be insufficient in some cases, and prognosing the fault ahead of time could have a certain necessity. Accurate prediction of key alarm variables in chemical process can indicate the possible change to reduce the probability of abnormal conditions. According to the characteristics of chemical process data, this work proposed a key alarm variables prediction model in chemical process based on dynamic-inner principal component analysis(DiPCA) and long short-term memory(LSTM). DiPCA is used to extract the most dynamic components for prediction. While LSTM is used to learn the relationship and predict the key alarm variables. This work used a simulation data set and a real hydrogenation process data set for applications and explained the model validity from the essential characteristics. Comparison of results with different models shows that our model has better prediction accuracy and performance, which can provide the basis for fault prognosis and health management. 展开更多
关键词 Fault prognosis Process systems SAFETY PREDICTION Principal component analysis Long short term memory
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Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectives in the Big Data Era 被引量:19
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作者 Chao Shang Fengqi You 《Engineering》 SCIE EI 2019年第6期1010-1016,共7页
Safe, ef cient, and sustainable operations and control are primary objectives in industrial manufacturing processes. State-of-the-art technologies heavily rely on human intervention, thereby showing apparent limitatio... Safe, ef cient, and sustainable operations and control are primary objectives in industrial manufacturing processes. State-of-the-art technologies heavily rely on human intervention, thereby showing apparent limitations in practice. The burgeoning era of big data is in uencing the process industries tremendously, providing unprecedented opportunities to achieve smart manufacturing. This kind of manufacturing requires machines to not only be capable of relieving humans from intensive physical work, but also be effective in taking on intellectual labor and even producing innovations on their own. To attain this goal, data analytics and machine learning are indispensable. In this paper, we review recent advances in data analytics and machine learning applied to the monitoring, control, and optimization of industrial processes, paying particular attention to the interpretability and functionality of machine learning mod- els. By analyzing the gap between practical requirements and the current research status, promising future research directions are identi ed. 展开更多
关键词 Big data Machine learning Smart manufacturing Process systems engineering
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Design of heat exchanger network based on entransy theory 被引量:5
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作者 Li Xia Yuanli Feng +1 位作者 Xiaoyan Sun Shuguang Xiang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2018年第8期1692-1699,共8页
The heat exchanger network(HEN) synthesis problem based on entransy theory is analyzed. According to the characteristics of entransy representation of thermal potential energy, the entransy dissipation represents the ... The heat exchanger network(HEN) synthesis problem based on entransy theory is analyzed. According to the characteristics of entransy representation of thermal potential energy, the entransy dissipation represents the irreversibility of the heat transfer process, the temperature difference determines the entransy dissipation, and four HEN design steps based on entransy theory are put forward. The present study shows how it is possible to set energy targets based on entransy and achieve them with a network of heat exchangers by an example of heat exchanger network design for four streams. In order to verify the correctness of the heat exchanger networks design method based on entransy theory, the synthesis of the HEN for the diesel hydrogenation unit is studied. Using the heat exchange networks design method based on entransy theory, the HEN obtained is consistent with energy targets. The entransy transfer efficiency of HEN based on entransy theory is 92.29%, higher than the entransy transfer efficiency of the maximum heat recovery network based on pinch technology. 展开更多
关键词 Process systems Heat exchanger network synthesis Heat transfer Entransy Energy target PINCH
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Multimodal process monitoring based on transition-constrained Gaussian mixture model 被引量:4
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作者 Shutian Chen Qingchao Jiang Xuefeng Yan 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2020年第12期3070-3078,共9页
Reliable process monitoring is important for ensuring process safety and product quality.A production process is generally characterized bymultiple operation modes,and monitoring thesemultimodal processes is challengi... Reliable process monitoring is important for ensuring process safety and product quality.A production process is generally characterized bymultiple operation modes,and monitoring thesemultimodal processes is challenging.Most multimodal monitoring methods rely on the assumption that the modes are independent of each other,which may not be appropriate for practical application.This study proposes a transition-constrained Gaussian mixture model method for efficient multimodal process monitoring.This technique can reduce falsely and frequently occurring mode transitions by considering the time series information in the mode identification of historical and online data.This process enables the identified modes to reflect the stability of actual working conditions,improve mode identification accuracy,and enhance monitoring reliability in cases of mode overlap.Case studies on a numerical simulation example and simulation of the penicillin fermentation process are provided to verify the effectiveness of the proposed approach inmultimodal process monitoring with mode overlap. 展开更多
关键词 Multimodal process monitoring Gaussian mixture model State transition matrix Process control Process systems Systems engineering
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Dynamic soft sensor development based on Gaussian mixture regression for fermentation processes 被引量:9
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作者 Congli Mei Yong Su +2 位作者 Guohai Liu Yuhan Ding Zhiling Liao 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2017年第1期116-122,共7页
The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation proce... The dynamic soft sensor based on a single Gaussian process regression(GPR) model has been developed in fermentation processes.However,limitations of single regression models,for multiphase/multimode fermentation processes,may result in large prediction errors and complexity of the soft sensor.Therefore,a dynamic soft sensor based on Gaussian mixture regression(GMR) was proposed to overcome the problems.Two structure parameters,the number of Gaussian components and the order of the model,are crucial to the soft sensor model.To achieve a simple and effective soft sensor,an iterative strategy was proposed to optimize the two structure parameters synchronously.For the aim of comparisons,the proposed dynamic GMR soft sensor and the existing dynamic GPR soft sensor were both investigated to estimate biomass concentration in a Penicillin simulation process and an industrial Erythromycin fermentation process.Results show that the proposed dynamic GMR soft sensor has higher prediction accuracy and is more suitable for dynamic multiphase/multimode fermentation processes. 展开更多
关键词 Dynamic modeling Process systems Instrumentation Gaussian mixture regression Fermentation processes
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Data-driven optimal operation of the industrial methanol to olefin process based on relevance vector machine 被引量:2
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作者 Zhiquan Wang Liang Wang +1 位作者 Zhihong Yuan Bingzhen Chen 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2021年第6期106-115,共10页
Methanol to olefin(MTO)technology provides the opportunity to produce olefins from nonpetroleum sources such as coal,biomass and natural gas.More than 20 commercial MTO plants have been put into operation.Till now,con... Methanol to olefin(MTO)technology provides the opportunity to produce olefins from nonpetroleum sources such as coal,biomass and natural gas.More than 20 commercial MTO plants have been put into operation.Till now,contributions on optimal operation of industrial MTO plants from a process systems engineering perspective are rare.Based on relevance vector machine(RVM),a data-driven framework for optimal operation of the industrial MTO process is established to fully utilize the plentiful industrial data sets.RVM correlates the yield distribution prediction of main products and the operation conditions.These correlations then serve as the constraints for the multi-objective optimization model to pursue the optimal operation of the plant.Nondominated sorting genetic algorithmⅡis used to solve the optimization problem.Comprehensive tests demonstrate that the ethylene yield is effectively improved based on the proposed framework.Since RVM does provide the distribution prediction instead of point estimation,the established model is expected to provide guidance for actual production operations under uncertainty. 展开更多
关键词 Methanol to olefins Relevance vector machine Genetic algorithm Operation optimization Systems engineering Process systems
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Two-stage approach to full Chinese parsing 被引量:3
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作者 曹海龙 Zhao Tiejun Yang Muyun Li Sheng 《High Technology Letters》 EI CAS 2005年第4期359-363,共5页
Natural language parsing is a task of great importance and extreme difficulty. In this paper, we present a full Chinese parsing system based on a two-stage approach. Rather than identifying all phrases by a uniform mo... Natural language parsing is a task of great importance and extreme difficulty. In this paper, we present a full Chinese parsing system based on a two-stage approach. Rather than identifying all phrases by a uniform model, we utilize a divide and conquer strategy. We propose an effective and fast method based on Markov model to identify the base phrases. Then we make the first attempt to extend one of the best English parsing models i.e. the head-driven model to recognize Chinese complex phrases. Our two-stage approach is superior to the uniform approach in two aspects. First, it creates synergy between the Markov model and the head-driven model. Second, it reduces the complexity of full Chinese parsing and makes the parsing system space and time efficient. We evaluate our approach in PARSEVAL measures on the open test set, the parsing system performances at 87.53% precision, 87.95% recall. 展开更多
关键词 natural language processing systems PARSING markov model pattern recognition
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A novel method based on entransy theory for setting energy targets of heat exchanger network 被引量:5
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作者 Li Xia Yuanli Feng +1 位作者 Xiaoyan Sun Shuguang Xiang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2017年第8期1037-1042,共6页
A T-Q diagram based on entransy theory is applied to graphically and quantitatively describe the irreversibility of the heat transfer processes.The hot and cold composite curves can be obtained in the T-Q diagram.The ... A T-Q diagram based on entransy theory is applied to graphically and quantitatively describe the irreversibility of the heat transfer processes.The hot and cold composite curves can be obtained in the T-Q diagram.The entransy recovery and entransy dissipation that are affected by temperature differences can be obtained through the shaded area under the composite curves.The method for setting the energy target of the HENs in T-Q diagram based on entransy theory is proposed.A case study of the diesel oil hydrogenation unit is used to illustrate the application of the method.The results show that three different heat transfer temperature differences is 10 K,15 K and 20 K,and the entransy recovery is 5.498×10~7k W·K,5.377×10~7k W·K,5.257×10~7k W·K,respectively.And the entransy transfer efficiency is 92.29%,91.63%,90.99%.Thus,the energy-saving potential of the HENs is obtained by setting the energy target based on the entransy transfer efficiency. 展开更多
关键词 Heat transfer Process systems Entransy Energy target T-Qdiagram
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A comparative process simulation study of Ca-Cu looping involving post-combustion CO2 capture 被引量:1
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作者 Xiaoyu Wang Haibo Zhao Mingze Su 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2020年第9期2382-2390,共9页
This work presents a simulation study of several Ca-Cu looping variants with CO(2)capture,aiming at both parameter optimization and exergy analysis of these Ca-Cu looping systems.Three kinds of Ca-Cu looping are consi... This work presents a simulation study of several Ca-Cu looping variants with CO(2)capture,aiming at both parameter optimization and exergy analysis of these Ca-Cu looping systems.Three kinds of Ca-Cu looping are considered:(1)carbonation-calcination/reduction-oxidation;(2)carbonation-oxidation-calcination/reduction and (3)carbona tion/oxidation-calcination/reduction.A conventional Ca looping is also simulated for comparison.The influences of the calcination temperature on the mole fractions of CO(2)and CaO at the calciner outlet,the CaCO3 flow rate on the carbonator performance and the Cu/Ca ratio on the calciner performance are analyzed.The second kind of Ca-Cu looping has the highest carbonation conversion.At 1×10^5 Pa and 820℃,complete decomposition of CaCO3 can be achieved in three Ca-Cu looping systems,while the operation condition of 1×10^5 Pa,840℃is required for the conventional Ca looping system.Furthermore,the Cu/Ca molar ratio of 5.13-5.19 is required for the Ca-Cu looping.Exergy analyses show that the maximum exergy destruction occurs in the calciner for the four modes and the second Ca-Cu looping system(i.e.,carbonation-oxidation-calcination/reduction)performs the highest exergy efficiency,up to 65.04%,which is about 30%higher than that of the conventional Ca looping. 展开更多
关键词 Ca-Cu looping CO2 capture Process systems Numerical simulation EXERGY
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Optimal synthesis of compression refrigeration system using a novel MINLP approach 被引量:1
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作者 Tao Yang Yiqing Luo +1 位作者 Yingjie Ma Xigang Yuan 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2018年第8期1662-1669,共8页
The optimal design of a compression refrigeration system(CRS) with multiple temperature levels is very important to chemical process industries and also represents considerable challenges in process systems engineerin... The optimal design of a compression refrigeration system(CRS) with multiple temperature levels is very important to chemical process industries and also represents considerable challenges in process systems engineering. In this paper, a general methodology for the optimal synthesis of the CRS, which simultaneously integrates CRS and Heat Exchanger Networks(HEN) to minimize the total compressor shaft work consumption based on an MINLP model, has been proposed. The major contribution of this method is in addressing the optimal design of refrigeration cycle with variable refrigeration temperature levels. The method can be used to make major decisions in the CRS design, such as the number of levels, temperature levels, and heat transfer duties. The performance of the developed methodology has been illustrated with a case study of an ethylene CRS in an industrial ethylene plant, and the optimal solution has been examined by rigorous simulations in Aspen Plus to verify its feasibility and consistency. 展开更多
关键词 Optimal design Compression refrigeration system (CRS) Chemical process Process systems Compressor shaft work Mixed Integer Nonlinear Programming (MINLP)
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Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance 被引量:2
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作者 Baocang Ding Hongguang Pan 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2016年第10期1431-1441,共11页
The output feedback model predictive control(MPC),for a linear parameter varying(LPV) process system including unmeasurable model parameters and disturbance(all lying in known polytopes),is considered.Some previously ... The output feedback model predictive control(MPC),for a linear parameter varying(LPV) process system including unmeasurable model parameters and disturbance(all lying in known polytopes),is considered.Some previously developed tools,including the norm-bounding technique for relaxing the disturbance-related constraint handling,the dynamic output feedback law,the notion of quadratic boundedness for specifying the closed-loop stability,and the ellipsoidal state estimation error bound for guaranteeing the recursive feasibility,are merged in the control design.Some previous approaches are shown to be the special cases.An example of continuous stirred tank reactor(CSTR) is given to show the effectiveness of the proposed approaches. 展开更多
关键词 Model predictive control Process systems Stability Recursive feasibility Uncertainty Norm-bounding technique
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