The formation of methane hydrate was undertaken in this research. The purpose of this work was to model the methane hydrate formation with a hydrate-water–methane system in a semi-batch reactor under steady–state, i...The formation of methane hydrate was undertaken in this research. The purpose of this work was to model the methane hydrate formation with a hydrate-water–methane system in a semi-batch reactor under steady–state, isothermal and isobaric conditions. Obtained results were validated with experiments conducted in a semi-batch spray reactor at low temperatures and high pressures. The investigated formation of gas hydrate from pure methane required physical constants of these materials which were determined through experimental data. The experiments hence, the theoretical calculations were conducted with pure methane and carried out in a spray reactor at 273.95K and 8705kPa to determine the actual amount of hydrate formation in such reactor. Ultimately;the comparison of the results generated from the developed mathematical model with those of experimental data of others indicated a very satisfactory agreement obtained.展开更多
This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network,...This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.展开更多
This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary erro...This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary error model and the identification principle based on the probability density function(PDF). The main contribution is that the NFM parameter updating approach is transformed into the shape control for the PDF of modeling error. More specifically, a virtual adaptive control system is constructed with the aid of the auxiliary error model and then the PDF shape control idea is used to tune NFM parameters so that the PDF of modeling error is controlled to follow a targeted PDF, which is in Gaussian or uniform distribution. Examples are used to validate the applicability of the proposed method and comparisons are made with the minimum mean square error based approaches.展开更多
In the manufacturing processes of high value-added products in the pharmaceutical, fine chemical polymer and food industry, insufficient control might produce off-grade products. This can cause significant financial l...In the manufacturing processes of high value-added products in the pharmaceutical, fine chemical polymer and food industry, insufficient control might produce off-grade products. This can cause significant financial losses, or in the pharmaceutical industry, it can result in an unusable batch. In these industries, batch reactors are commonly used, the control of which is essentially a problem of temperature control. In the industry, an increasing number of heating-cooling systems utilising three different temperature levels can be found, which are advantageous from an economic point of view. However, it makes the control more complicated. This paper presents a split-range designing technique using the model of the controlled system with the aim to design a split-range algorithm more specific to the actual sys- tem. The algorithm described provides high control performance when using it with classical PID-based cascade temperature control of jacketed batch reactors;however, it can be used with or as part of other types of controllers, for ex- ample, model-based temperature controllers. The algorithm can be used in the case of systems where only two as well as where three temperature levels are used for temperature control. Besides the switching between the modes of opera- tion and calculating the value of the manipulated variable, one of the most important functions of the split-range algo- rithm is to keep the sign of the gain of the controlled system unchanged. However, with a more system-specific split-range solution, not only can the sign of the gain be kept unchanged, but the gain can also be constant or less de- pendent on the state of the system. Using this solution, the design of the PID controller becomes simpler and can be implemented in existing systems without serious changes.展开更多
This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. ...This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.展开更多
This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air qua...This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM<sub>10</sub>) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM<sub>10</sub> released from the cement silos into the air. Simulations were carried out for PM<sub>10</sub> emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM<sub>10</sub> emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m<sup>3</sup>, and the highest daily emission value is 0.6 μg/m<sup>3</sup>;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m<sup>3</sup>. The highest daily emission average value was 1250.09 μg/m<sup>3</sup>;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM<sub>10</sub> pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.展开更多
The population balance modeling is regarded as a universally accepted mathematical framework for dynamic simulation of various particulate processes, such as crystallization, granulation and polymerization. This artic...The population balance modeling is regarded as a universally accepted mathematical framework for dynamic simulation of various particulate processes, such as crystallization, granulation and polymerization. This article is concerned with the application of the method of characteristics (MOC) for solving population balance models describing batch crystallization process. The growth and nucleation are considered as dominant phenomena, while the breakage and aggregation are neglected. The numerical solutions of such PBEs require high order accuracy due to the occurrence of steep moving fronts and narrow peaks in the solutions. The MOC has been found to be a very effective technique for resolving sharp discontinuities. Different case studies are carried out to analyze the accuracy of proposed algorithm. For validation, the results of MOC are compared with the available analytical solutions and the results of finite volume schemes. The results of MOC were found to be in good agreement with analytical solutions and superior than those obtained by finite volume schemes.展开更多
文摘The formation of methane hydrate was undertaken in this research. The purpose of this work was to model the methane hydrate formation with a hydrate-water–methane system in a semi-batch reactor under steady–state, isothermal and isobaric conditions. Obtained results were validated with experiments conducted in a semi-batch spray reactor at low temperatures and high pressures. The investigated formation of gas hydrate from pure methane required physical constants of these materials which were determined through experimental data. The experiments hence, the theoretical calculations were conducted with pure methane and carried out in a spray reactor at 273.95K and 8705kPa to determine the actual amount of hydrate formation in such reactor. Ultimately;the comparison of the results generated from the developed mathematical model with those of experimental data of others indicated a very satisfactory agreement obtained.
基金Supported by UK EPSRC (grants GR/N13319 and GR/R 10875)
文摘This paper presents several neural network based modelling, reliable optimal control, and iterative learning control methods for batch processes. In order to overcome the lack of robustness of a single neural network, bootstrap aggregated neural networks are used to build reliable data based empirical models. Apart from improving the model generalisation capability, a bootstrap aggregated neural network can also provide model prediction confidence bounds. A reliable optimal control method by incorporating model prediction confidence bounds into the optimisation objective function is presented. A neural network based iterative learning control strategy is presented to overcome the problem due to unknown disturbances and model-plant mismatches. The proposed methods are demonstrated on a simulated batch polymerisation process.
基金Supported by the National Natural Science Foundation of China(61374044)Shanghai Science Technology Commission(12510709400)+1 种基金Shanghai Municipal Education Commission(14ZZ088)Shanghai Talent Development Plan
文摘This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary error model and the identification principle based on the probability density function(PDF). The main contribution is that the NFM parameter updating approach is transformed into the shape control for the PDF of modeling error. More specifically, a virtual adaptive control system is constructed with the aid of the auxiliary error model and then the PDF shape control idea is used to tune NFM parameters so that the PDF of modeling error is controlled to follow a targeted PDF, which is in Gaussian or uniform distribution. Examples are used to validate the applicability of the proposed method and comparisons are made with the minimum mean square error based approaches.
文摘In the manufacturing processes of high value-added products in the pharmaceutical, fine chemical polymer and food industry, insufficient control might produce off-grade products. This can cause significant financial losses, or in the pharmaceutical industry, it can result in an unusable batch. In these industries, batch reactors are commonly used, the control of which is essentially a problem of temperature control. In the industry, an increasing number of heating-cooling systems utilising three different temperature levels can be found, which are advantageous from an economic point of view. However, it makes the control more complicated. This paper presents a split-range designing technique using the model of the controlled system with the aim to design a split-range algorithm more specific to the actual sys- tem. The algorithm described provides high control performance when using it with classical PID-based cascade temperature control of jacketed batch reactors;however, it can be used with or as part of other types of controllers, for ex- ample, model-based temperature controllers. The algorithm can be used in the case of systems where only two as well as where three temperature levels are used for temperature control. Besides the switching between the modes of opera- tion and calculating the value of the manipulated variable, one of the most important functions of the split-range algo- rithm is to keep the sign of the gain of the controlled system unchanged. However, with a more system-specific split-range solution, not only can the sign of the gain be kept unchanged, but the gain can also be constant or less de- pendent on the state of the system. Using this solution, the design of the PID controller becomes simpler and can be implemented in existing systems without serious changes.
文摘This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.
文摘This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM<sub>10</sub>) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM<sub>10</sub> released from the cement silos into the air. Simulations were carried out for PM<sub>10</sub> emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM<sub>10</sub> emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m<sup>3</sup>, and the highest daily emission value is 0.6 μg/m<sup>3</sup>;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m<sup>3</sup>. The highest daily emission average value was 1250.09 μg/m<sup>3</sup>;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM<sub>10</sub> pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.
文摘The population balance modeling is regarded as a universally accepted mathematical framework for dynamic simulation of various particulate processes, such as crystallization, granulation and polymerization. This article is concerned with the application of the method of characteristics (MOC) for solving population balance models describing batch crystallization process. The growth and nucleation are considered as dominant phenomena, while the breakage and aggregation are neglected. The numerical solutions of such PBEs require high order accuracy due to the occurrence of steep moving fronts and narrow peaks in the solutions. The MOC has been found to be a very effective technique for resolving sharp discontinuities. Different case studies are carried out to analyze the accuracy of proposed algorithm. For validation, the results of MOC are compared with the available analytical solutions and the results of finite volume schemes. The results of MOC were found to be in good agreement with analytical solutions and superior than those obtained by finite volume schemes.
