Accurate prediction of chemical composition of vacuum gas oil （VGO） is essential for the routine operation of refineries. In this work, a new approach for auto-design of artificial neural networks （ANN） based on a...Accurate prediction of chemical composition of vacuum gas oil （VGO） is essential for the routine operation of refineries. In this work, a new approach for auto-design of artificial neural networks （ANN） based on a genetic algorithm （GA） is developed for predicting VGO saturates. The number of neurons in the hidden layer, the momentum and the learning rates are determined by using the genetic algorithm. The inputs for the artificial neural networks model are five physical properties, namely, average boiling point, density, molecular weight, viscosity and refractive index. It is verified that the genetic algorithm could find the optimal structural parameters and training parameters of ANN. In addition, an artificial neural networks model based on a genetic algorithm was tested and the results indicated that the VGO saturates can be efficiently predicted. Compared with conventional artificial neural networks models, this approach can improve the prediction accuracy.展开更多
Great volumes of shallow-buried （〈2,000 m） natural gases which are mainly composed of biogases and low-mature gases have been found in the Mesozoic-Cenozoic sedimentary basins in China. Many shallow gas reservoirs ...Great volumes of shallow-buried （〈2,000 m） natural gases which are mainly composed of biogases and low-mature gases have been found in the Mesozoic-Cenozoic sedimentary basins in China. Many shallow gas reservoirs in China are characterized by coexistence of biogas and low-mature gas, so identifying the genetic types of shallow gases is important for exploration and development in sedimentary basins. In this paper, we study the gas geochemistry characteristics and distribution in different basins, and classify the shallow gas into two genetic types, biogas and low-mature gas. The biogases are subdivided further into two subtypes by their sources, the source rock-derived biogas and hydrocarbon-derived biogas. Based on the burial history of the source rocks, the source rock-derived biogases are divided into primary and secondary biogas. The former is generated from the source rocks in the primary burial stage, and the latter is from uplifted source rocks or those in a secondary burial stage. In addition, the identifying parameters of each type of shallow gas are given. Based on the analysis above, the distributions of each type of shallow gas are studied. The primary biogases generated from source rocks are mostly distributed in Quaternary basins or modem deltas. Most of them migrate in watersoluble or diffused mode, and their migration distance is short. Reservoir and caprock assemblages play an important role in primary biogas accumulation. The secondary biogases are distributed in a basin with secondary burial history. The oil-degraded biogases are distributed near heavy oil pools. The low-mature gases are widely distributed in shallow-buried reservoirs in the Meso-Cenozoic basins.展开更多
CO2 gas is a nonhydrocarbon gas, with a high economic value and a broad prospect for application. In the Huanghua Depression, there exist many genetic types of CO2 gases, i.e. organic CO2, thermal metamorphic CO2 and ...CO2 gas is a nonhydrocarbon gas, with a high economic value and a broad prospect for application. In the Huanghua Depression, there exist many genetic types of CO2 gases, i.e. organic CO2, thermal metamorphic CO2 and crust-mantle mixed CO2. The distribution of different types of CO2 gases is controlled by different factors. Organic CO2 that occurs mainly around the oil-generating center is associated with hydrocarbon gases as a secondary product and commonly far away from large faults. Thermal metamorphic CO2 occurs mainly in areas where carbonate strata are developed and igneous activity is strong, and tends to accumulate near large faults. CO2 of such an origin is higher in concentration than organic CO2, but lower than crust-mantle mixed CO2. Crust-mantle mixed CO2 occurs mainly along large faults. Its distribution is limited, but its purity is the highest.展开更多
Natural gas has been discovered in many anticlines in the southern margin of the Junggar Basin. However, the geochemical characteristics of natural gas in different anticlines haven’t been compared systematically, pa...Natural gas has been discovered in many anticlines in the southern margin of the Junggar Basin. However, the geochemical characteristics of natural gas in different anticlines haven’t been compared systematically, particularly, the type and source of natural gas discovered recently in Well Gaotan-1 at the Gaoquan anticline remain unclear. The gas composition characteristics and carbon and hydrogen isotope compositions in different anticlines were compared and sorted systematically to identify genetic types and source of the natural gas. The results show that most of the gas samples are wet gas, and a few are dry gas;the gas samples from the western and middle parts have relatively heavier carbon isotope composition and lighter hydrogen isotope composition, while the gas samples from the eastern part of southern basin have lighter carbon and hydrogen isotope compositions. The natural gas in the southern margin is thermogenic gas generated by freshwater-brackish water sedimentary organic matter, which can be divided into three types, coal-derived gas, mixed gas and oil-associated gas, in which coal-derived gas and mixed gas take dominance. The Jurassic coal measures is the main natural gas source rock in the southern margin, and the Permian lacustrine and the Upper Triassic lacustrine-limnetic facies source rocks are also important natural gas source rocks. The natural gas in the western part of the southern margin is derived from the Jurassic coal measures and the Permian lacustrine source rock, while the natural gas in the middle part of the southern margin is mainly derived from the Jurassic coal measures, partly from the Permian and/or the Upper Triassic source rocks, and the natural gas in the eastern part of the southern margin is originated from the Permian lacustrine source rock. The natural gas in the Qingshuihe oil and gas reservoir of Well Gaotan-1 is a mixture of coal-derived gas and oil-associated gas, of which the Jurassic and Permian source rocks contribute about half each.展开更多
Proper fixture design is crucial to obtain the better product quality according to the design specification during the workpiece fabrication. Locator layout planning is one of the most important tasks in the fixture ...Proper fixture design is crucial to obtain the better product quality according to the design specification during the workpiece fabrication. Locator layout planning is one of the most important tasks in the fixture design process. However, the design of a fixture relies heavily on the designerts expertise and experience up to now. Therefore, a new approach to loeator layout determination for workpieces with arbitrary complex surfaces is pro- posed for the first time. Firstly, based on the fuzzy judgment method, the proper locating reference and locator - numbers are determined with consideration of surface type, surface area and position tolerance. Secondly, the lo- cator positions are optimized by genetic algorithm（GA）. Finally, a typical example shows that the approach is su- perior to the experiential method and can improve positioning accuracy effectively.展开更多
A neural network model of key process parameters and forming quality is developed based on training samples which are obtained from the orthogonal experiment and the finite element numerical simulation. Optimization o...A neural network model of key process parameters and forming quality is developed based on training samples which are obtained from the orthogonal experiment and the finite element numerical simulation. Optimization of the process parameters is conducted using the genetic algorithm (GA). The experimental results have shown that a surface model of the neural network can describe the nonlinear implicit relationship between the parameters of the power spinning process:the wall margin and amount of expansion. It has been found that the process of determining spinning technological parameters can be accelerated using the optimization method developed based on the BP neural network and the genetic algorithm used for the process parameters of power spinning formation. It is undoubtedly beneficial towards engineering applications.展开更多
The reaction kinetics of oxidative coupling of methane catalyzed by perovskite was studied in a fixed bed flow reactor.At atmospheric pressure,the reactions were carried out at 725,750 and 775℃,inlet methane to oxyge...The reaction kinetics of oxidative coupling of methane catalyzed by perovskite was studied in a fixed bed flow reactor.At atmospheric pressure,the reactions were carried out at 725,750 and 775℃,inlet methane to oxygen ratios of 2 to 4.5 and gas hourly space velocity （GHSV） of 100 min^-1.Correlation of the kinetic data has been performed with the proposed mechanisms.The selected equations have been regressed with experimental data accompanied by genetic algorithm （GA） in order to obtain optimized parameters.After investigation the Langmuir-Hinshelwood mechanism was selected as the best mechanism,and Arrhenius and adsorption parameters of this model were obtained by linear regression.In this research the Marquardt algorithm was also used and its results were compared with those of genetic algorithm.It should be noted that the Marquardt algorithm is sensitive to the selection of initial values and there is possibility to trap in a local minimum.展开更多
The performance of deep learning(DL)networks has been increased by elaborating the network structures. However, the DL netowrks have many parameters, which have a lot of influence on the performance of the network. We...The performance of deep learning(DL)networks has been increased by elaborating the network structures. However, the DL netowrks have many parameters, which have a lot of influence on the performance of the network. We propose a genetic algorithm(GA) based deep belief neural network(DBNN) method for robot object recognition and grasping purpose. This method optimizes the parameters of the DBNN method, such as the number of hidden units, the number of epochs, and the learning rates, which would reduce the error rate and the network training time of object recognition. After recognizing objects, the robot performs the pick-andplace operations. We build a database of six objects for experimental purpose. Experimental results demonstrate that our method outperforms on the optimized robot object recognition and grasping tasks.展开更多
Frequency selective surface （FSS） is a two-dimensional periodic structure which has promiaent characteristics of bandpass or bandbloek when interacting with electromagnetic waves. In this paper, the thickness, the d...Frequency selective surface （FSS） is a two-dimensional periodic structure which has promiaent characteristics of bandpass or bandbloek when interacting with electromagnetic waves. In this paper, the thickness, the dielectric constant, the element graph and the arrangement periodicity of an FSS medium are investigated by Genetic Algorithm （GA） when an electromagnetic wave is incident on the FSS at a wide angle, and an optimized FSS structure and transmission characteristics are obtained. The results show that the optimized structure has better stability in relation to incident angle of electromagnetic wave and preserves the stability of centre frequency even at an incident angle as large as 80°, thereby laying the foundation for the application of FSS to curved surfaces at wide angles.展开更多
Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a ...Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras＇ parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion （DLT）, GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation.展开更多
文摘Accurate prediction of chemical composition of vacuum gas oil （VGO） is essential for the routine operation of refineries. In this work, a new approach for auto-design of artificial neural networks （ANN） based on a genetic algorithm （GA） is developed for predicting VGO saturates. The number of neurons in the hidden layer, the momentum and the learning rates are determined by using the genetic algorithm. The inputs for the artificial neural networks model are five physical properties, namely, average boiling point, density, molecular weight, viscosity and refractive index. It is verified that the genetic algorithm could find the optimal structural parameters and training parameters of ANN. In addition, an artificial neural networks model based on a genetic algorithm was tested and the results indicated that the VGO saturates can be efficiently predicted. Compared with conventional artificial neural networks models, this approach can improve the prediction accuracy.
文摘Great volumes of shallow-buried （〈2,000 m） natural gases which are mainly composed of biogases and low-mature gases have been found in the Mesozoic-Cenozoic sedimentary basins in China. Many shallow gas reservoirs in China are characterized by coexistence of biogas and low-mature gas, so identifying the genetic types of shallow gases is important for exploration and development in sedimentary basins. In this paper, we study the gas geochemistry characteristics and distribution in different basins, and classify the shallow gas into two genetic types, biogas and low-mature gas. The biogases are subdivided further into two subtypes by their sources, the source rock-derived biogas and hydrocarbon-derived biogas. Based on the burial history of the source rocks, the source rock-derived biogases are divided into primary and secondary biogas. The former is generated from the source rocks in the primary burial stage, and the latter is from uplifted source rocks or those in a secondary burial stage. In addition, the identifying parameters of each type of shallow gas are given. Based on the analysis above, the distributions of each type of shallow gas are studied. The primary biogases generated from source rocks are mostly distributed in Quaternary basins or modem deltas. Most of them migrate in watersoluble or diffused mode, and their migration distance is short. Reservoir and caprock assemblages play an important role in primary biogas accumulation. The secondary biogases are distributed in a basin with secondary burial history. The oil-degraded biogases are distributed near heavy oil pools. The low-mature gases are widely distributed in shallow-buried reservoirs in the Meso-Cenozoic basins.
文摘CO2 gas is a nonhydrocarbon gas, with a high economic value and a broad prospect for application. In the Huanghua Depression, there exist many genetic types of CO2 gases, i.e. organic CO2, thermal metamorphic CO2 and crust-mantle mixed CO2. The distribution of different types of CO2 gases is controlled by different factors. Organic CO2 that occurs mainly around the oil-generating center is associated with hydrocarbon gases as a secondary product and commonly far away from large faults. Thermal metamorphic CO2 occurs mainly in areas where carbonate strata are developed and igneous activity is strong, and tends to accumulate near large faults. CO2 of such an origin is higher in concentration than organic CO2, but lower than crust-mantle mixed CO2. Crust-mantle mixed CO2 occurs mainly along large faults. Its distribution is limited, but its purity is the highest.
基金Supported by the PetroChina Science and Technology Project(06-01A-01-02,2016A-0202)
文摘Natural gas has been discovered in many anticlines in the southern margin of the Junggar Basin. However, the geochemical characteristics of natural gas in different anticlines haven’t been compared systematically, particularly, the type and source of natural gas discovered recently in Well Gaotan-1 at the Gaoquan anticline remain unclear. The gas composition characteristics and carbon and hydrogen isotope compositions in different anticlines were compared and sorted systematically to identify genetic types and source of the natural gas. The results show that most of the gas samples are wet gas, and a few are dry gas;the gas samples from the western and middle parts have relatively heavier carbon isotope composition and lighter hydrogen isotope composition, while the gas samples from the eastern part of southern basin have lighter carbon and hydrogen isotope compositions. The natural gas in the southern margin is thermogenic gas generated by freshwater-brackish water sedimentary organic matter, which can be divided into three types, coal-derived gas, mixed gas and oil-associated gas, in which coal-derived gas and mixed gas take dominance. The Jurassic coal measures is the main natural gas source rock in the southern margin, and the Permian lacustrine and the Upper Triassic lacustrine-limnetic facies source rocks are also important natural gas source rocks. The natural gas in the western part of the southern margin is derived from the Jurassic coal measures and the Permian lacustrine source rock, while the natural gas in the middle part of the southern margin is mainly derived from the Jurassic coal measures, partly from the Permian and/or the Upper Triassic source rocks, and the natural gas in the eastern part of the southern margin is originated from the Permian lacustrine source rock. The natural gas in the Qingshuihe oil and gas reservoir of Well Gaotan-1 is a mixture of coal-derived gas and oil-associated gas, of which the Jurassic and Permian source rocks contribute about half each.
基金Supported by the Natural Science Foundation of Jiangxi Province(2009GZC0104)the Science and Technology Research Project of Jiangxi Provincial Department of Education(GJJ10521)~~
文摘Proper fixture design is crucial to obtain the better product quality according to the design specification during the workpiece fabrication. Locator layout planning is one of the most important tasks in the fixture design process. However, the design of a fixture relies heavily on the designerts expertise and experience up to now. Therefore, a new approach to loeator layout determination for workpieces with arbitrary complex surfaces is pro- posed for the first time. Firstly, based on the fuzzy judgment method, the proper locating reference and locator - numbers are determined with consideration of surface type, surface area and position tolerance. Secondly, the lo- cator positions are optimized by genetic algorithm（GA）. Finally, a typical example shows that the approach is su- perior to the experiential method and can improve positioning accuracy effectively.
基金Supported by the Natural Science Foundation of Shanxi Province Project(2012011023-2)
文摘A neural network model of key process parameters and forming quality is developed based on training samples which are obtained from the orthogonal experiment and the finite element numerical simulation. Optimization of the process parameters is conducted using the genetic algorithm (GA). The experimental results have shown that a surface model of the neural network can describe the nonlinear implicit relationship between the parameters of the power spinning process:the wall margin and amount of expansion. It has been found that the process of determining spinning technological parameters can be accelerated using the optimization method developed based on the BP neural network and the genetic algorithm used for the process parameters of power spinning formation. It is undoubtedly beneficial towards engineering applications.
基金supported by the Iran Polymer and Petrochemical Institute (IPPI)
文摘The reaction kinetics of oxidative coupling of methane catalyzed by perovskite was studied in a fixed bed flow reactor.At atmospheric pressure,the reactions were carried out at 725,750 and 775℃,inlet methane to oxygen ratios of 2 to 4.5 and gas hourly space velocity （GHSV） of 100 min^-1.Correlation of the kinetic data has been performed with the proposed mechanisms.The selected equations have been regressed with experimental data accompanied by genetic algorithm （GA） in order to obtain optimized parameters.After investigation the Langmuir-Hinshelwood mechanism was selected as the best mechanism,and Arrhenius and adsorption parameters of this model were obtained by linear regression.In this research the Marquardt algorithm was also used and its results were compared with those of genetic algorithm.It should be noted that the Marquardt algorithm is sensitive to the selection of initial values and there is possibility to trap in a local minimum.
文摘The performance of deep learning(DL)networks has been increased by elaborating the network structures. However, the DL netowrks have many parameters, which have a lot of influence on the performance of the network. We propose a genetic algorithm(GA) based deep belief neural network(DBNN) method for robot object recognition and grasping purpose. This method optimizes the parameters of the DBNN method, such as the number of hidden units, the number of epochs, and the learning rates, which would reduce the error rate and the network training time of object recognition. After recognizing objects, the robot performs the pick-andplace operations. We build a database of six objects for experimental purpose. Experimental results demonstrate that our method outperforms on the optimized robot object recognition and grasping tasks.
基金Project supported by the National Natural Science Foundation of China (Grant No 10647105)
文摘Frequency selective surface （FSS） is a two-dimensional periodic structure which has promiaent characteristics of bandpass or bandbloek when interacting with electromagnetic waves. In this paper, the thickness, the dielectric constant, the element graph and the arrangement periodicity of an FSS medium are investigated by Genetic Algorithm （GA） when an electromagnetic wave is incident on the FSS at a wide angle, and an optimized FSS structure and transmission characteristics are obtained. The results show that the optimized structure has better stability in relation to incident angle of electromagnetic wave and preserves the stability of centre frequency even at an incident angle as large as 80°, thereby laying the foundation for the application of FSS to curved surfaces at wide angles.
文摘Accurate stereo vision calibration is a preliminary step towards high-precision visual posi- tioning of robot. Combining with the characteristics of genetic algorithm （GA） and particle swarm optimization （PSO）, a three-stage calibration method based on hybrid intelligent optimization is pro- posed for nonlinear camera models in this paper. The motivation is to improve the accuracy of the calibration process. In this approach, the stereo vision calibration is considered as an optimization problem that can be solved by the GA and PSO. The initial linear values can be obtained in the frost stage. Then in the second stage, two cameras＇ parameters are optimized separately. Finally, the in- tegrated optimized calibration of two models is obtained in the third stage. Direct linear transforma- tion （DLT）, GA and PSO are individually used in three stages. It is shown that the results of every stage can correctly find near-optimal solution and it can be used to initialize the next stage. Simula- tion analysis and actual experimental results indicate that this calibration method works more accu- rate and robust in noisy environment compared with traditional calibration methods. The proposed method can fulfill the requirements of robot sophisticated visual operation.
