Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary a...Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.展开更多
In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model f...In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model function, the collinear scaling formula, quadratic approximation and interpolation. All the parameters in this model are determined by objective function interpolation condition. A new derivative free method is developed based upon this model and the global convergence of this new method is proved without any information on gradient.展开更多
In this paper,a passive muzzle arc control device(PMACD)of the augmented railguns is studied.By discussing its performance at different numbers of extra rails,a parameter optimization model is proposed.Through the cal...In this paper,a passive muzzle arc control device(PMACD)of the augmented railguns is studied.By discussing its performance at different numbers of extra rails,a parameter optimization model is proposed.Through the calculation model,it is found that the PMACD works well in the simple railgun,which refers to the gun that there is only one pair of rails in the inner bore.The PMACD may decrease the simple railgun’s armature peak current and muzzle arc,but affect its muzzle velocity not much.However,in the augmented railguns it has different characteristics.If the parameters of the PMACD are not selected suitable.It may increase the armature peak current and muzzle arc,but greatly decrease the velocity.The reason for this problem is that the extra rails generate a strong magnetic field in front of the armature,which induces a large current to change the armature current.It is also found that when the resistance and inductance parameters of the PMACD satisfy with the optimization formula,the PMACD can also play a good role in arc suppression in the augmented railguns.Experiments of an augmented railgun with a stainless steel PMACD are carried out to verify this optimization method.Results show that the muzzle arc is obviously controlled.This work may provide a reference for the design of the muzzle arc control device.展开更多
The paper presents a new solution of inverse displacement analysis of the general six degree-of-freedom serial robot.The inverse displacement analysis of the general serial robot is transformed into a minimization pro...The paper presents a new solution of inverse displacement analysis of the general six degree-of-freedom serial robot.The inverse displacement analysis of the general serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least squares problem with the analytic form of new Jacobian matrix.In this way,joint variables of the general serial robot can be searched out quickly under the desired precision when positions of the three non-collinear end effector points are given.Compared with the general Newton iterative method,the proposed algorithm can search out the solution when the robot is at the singular configuration and the initial configuration used in the optimization method may also be the singular configuration.So the convergence domain is bigger than that of the general Newton iterative method.Another advantage of the proposed algorithm is that positions of the three non-collinear end effector points are usually much easier to be measured than the orientation of the end effector.The inverse displacement analysis of the general 6R(six-revolute-joint) serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.Because the three non-collinear points can be selected at random,the method can be applied to any other types of serial robots.展开更多
This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method fo...This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method for the discussed problem is proposed.First,we consider the problem of quadratic optimal(QO)approximation associated with the current feasible iteration point,and we split the QO into two small-scale QOs which can be solved in parallel.Second,a feasible descent direction for the problem is obtained and a new SQO-type method is proposed,namely,splitting feasible SQO(SF-SQO)method.Moreover,under suitable conditions,we analyse the global convergence,strong convergence and rate of superlinear convergence of the SF-SQO method.Finally,preliminary numerical experiments regarding the economic dispatch of a power system are carried out,and these show that the SF-SQO method is promising.展开更多
A topology optimization method based on the solid isotropic material with penalization interpolation scheme is utilized for designing gradient coils for use in magnetic resonance microscopy.Unlike the popular stream f...A topology optimization method based on the solid isotropic material with penalization interpolation scheme is utilized for designing gradient coils for use in magnetic resonance microscopy.Unlike the popular stream function method,the proposed method has design variables that are the distribution of conductive material.A voltage-driven transverse gradient coil is proposed to be used as micro-scale magnetic resonance imaging(MRI)gradient coils,thus avoiding introducing a coil-winding pattern and simplifying the coil configuration.The proposed method avoids post-processing errors that occur when the continuous current density is approximated by discrete wires in the stream function approach.The feasibility and accuracy of the method are verified through designing the z-gradient and y-gradient coils on a cylindrical surface.Numerical design results show that the proposed method can provide a new coil layout in a compact design space.展开更多
In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an intera...In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an interactive numerical calculation platform which includes the functions of numerical simulation and optimization is established. The artificial neural network （ANN） and the greedy strategy are introduced into the hill-climbing pattern heuristic search process, and the optimizing search direction can be predicted by using small samples; when searching along the direction using the greedy strategy, the optimal values can be quickly approached. Therefore, excessive external calling of the numerical modeling process can be avoided, and the optimization time is decreased obviously. The experimental results indicate that the satisfied output parameters of air conditioning can be quickly given out based on the interactive numerical calculation platform and the improved search method, and the optimization for indoor thermal comfort can be completed.展开更多
The present work dealt with the preconcentration of rare earth elements in Saghand ore(Yazd province,Iran)which was achieved by Humphrey spiral using orthogonal optimization method after scrubbing the sample at 45%sol...The present work dealt with the preconcentration of rare earth elements in Saghand ore(Yazd province,Iran)which was achieved by Humphrey spiral using orthogonal optimization method after scrubbing the sample at 45%solid pulp density for 30 min.The pulp was diluted and was fed to a Humphrey spiral for upgrading.The process parameters considered were feed size,feed solids and feed rate,and Taguchi’s L9(34)orthogonal array(OA)was selected for optimization of the process.The results show that the feed rate and feed size were more significant than the other operation parameters of the process.It was also found that under optimal conditions,the concentrate grade of rare earth elements increased from2860 10 6to 6050 10 6and recovery reached to 58%.展开更多
The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And...The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.展开更多
In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is...In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.展开更多
Spectral and directional control of thermal emission based on excitation of confined electromagnetic resonant modes paves a viable way for the design and construction of microscale thermal emitters/absorbers. In this ...Spectral and directional control of thermal emission based on excitation of confined electromagnetic resonant modes paves a viable way for the design and construction of microscale thermal emitters/absorbers. In this paper, we present numerical simulation results of the thermal radiative properties of a silicon carbide（Si C） thermal emitter/absorber composed of periodic microstructures. We illustrate different electromagnetic resonant modes which can be excited with the structure,such as surface phonon polaritons, magnetic polaritons and photonic crystal modes, and the process of radiation spectrum optimization based on a non-linear optimization algorithm. We show that the spectral and directional control of thermal emission/absorption can be efficiently achieved by adjusting the geometrical parameters of the structure. Moreover, the optimized spectrum is insensitive to 3% dimension modification.展开更多
The basic configuration of a new type of subsea pipeline connector was proposed based on the press-fitting principle, and a parametric finite element model was created using APDL language in ANSYS. Combining the finit...The basic configuration of a new type of subsea pipeline connector was proposed based on the press-fitting principle, and a parametric finite element model was created using APDL language in ANSYS. Combining the finite element model and optimization technology, the dimension optimization aiming at obtaining the minimum loading force and the optimum sealing performance was designed by the zero order optimization method. Experiments of the optimized connector were carried out. The results indicate that the optimum structural design significantly improved the indicators of the minimum loading force and sealing performance of the connector.展开更多
The prediction process often runs with small samples and under-sufficient information.To target this problem,we propose a performance comparison study that combines prediction and optimization algorithms based on expe...The prediction process often runs with small samples and under-sufficient information.To target this problem,we propose a performance comparison study that combines prediction and optimization algorithms based on experimental data analysis.Through a large number of prediction and optimization experiments,the accuracy and stability of the prediction method and the correction ability of the optimization method are studied.First,five traditional single-item prediction methods are used to process small samples with under-sufficient information,and the standard deviation method is used to assign weights on the five methods for combined forecasting.The accuracy of the prediction results is ranked.The mean and variance of the rankings reflect the accuracy and stability of the prediction method.Second,the error elimination prediction optimization method is proposed.To make,the prediction results are corrected by error elimination optimization method(EEOM),Markov optimization and two-layer optimization separately to obtain more accurate prediction results.The degree improvement and decline are used to reflect the correction ability of the optimization method.The results show that the accuracy and stability of combined prediction are the best in the prediction methods,and the correction ability of error elimination optimization is the best in the optimization methods.The combination of the two methods can well solve the problem of prediction with small samples and under-sufficient information.Finally,the accuracy of the combination of the combined prediction and the error elimination optimization is verified by predicting the number of unsafe events in civil aviation in a certain year.展开更多
A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of ...A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore,the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship,suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.展开更多
In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization...In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis（ FEA） for remodeling. Design of experiments（ DOE） and response surface method（ RSM） are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm（ GA） are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems.展开更多
Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell s...Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization.Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states.展开更多
The design and fabrication method of magnetic field coils with high uniformity is essential for atomic magnetometers.In this paper,a novel design strategy for cylindrical uniform coils is first proposed,which combines...The design and fabrication method of magnetic field coils with high uniformity is essential for atomic magnetometers.In this paper,a novel design strategy for cylindrical uniform coils is first proposed,which combines the target-field method(TFM)with an optimized slime mold algorithm(SMA)to determine optimal structure parameters.Then,the realization method for the designed cylindrical coil by using the flexible printed circuit(FPC)technology is presented.Compared with traditional fabrication methods,this method has advantages in excellent flexibility and bending property,making the coils easier to be arranged in limited space.Moreover,the manufacturing process of the FPC technology via a specific cylindrical uniform magnetic field coil is discussed in detail,and the successfully realized coil is well tested in a verification system.By comparing the uniformity performance of the experimental coil with the simulation one,the effectiveness of the FPC technology in producing cylindrical coils has been well validated.展开更多
A novel data-driven, soft sensor based on support vector regression （SVR） integrated with a data compression technique was developed to predict the product quality for the hydrodesulfurization （HDS） process. A wid...A novel data-driven, soft sensor based on support vector regression （SVR） integrated with a data compression technique was developed to predict the product quality for the hydrodesulfurization （HDS） process. A wide range of experimental data was taken from a HDS setup to train and test the SVR model. Hyper-parameter tuning is one of the main challenges to improve predictive accuracy of the SVR model. Therefore, a hybrid approach using a combination of genetic algorithm （GA） and sequential quadratic programming （SQP） methods （GA-SQP） was developed. Performance of different optimization algorithms including GA-SQP, GA, pattern search （PS）, and grid search （GS） indicated that the best average absolute relative error （AARE）, squared correlation coefficient （R2）, and computation time （CT） （AARE = 0.0745, R2 = 0.997 and CT = 56 s） was accomplished by the hybrid algorithm. Moreover, to reduce the CT and improve the accuracy of the SVR model, the vector quantization （VQ） technique was used. The results also showed that the VQ technique can decrease the training time and improve prediction performance of the SVR model. The proposed method can provide a robust, soft sensor in a wide range of sulfur contents with good accuracy.展开更多
The Sulige tight gas reservoir is characterized by low-pressure, low-permeability and lowabundance. During production, gas flow rate and reservoir pressure decrease sharply; and in the shut- in period, reservoir press...The Sulige tight gas reservoir is characterized by low-pressure, low-permeability and lowabundance. During production, gas flow rate and reservoir pressure decrease sharply; and in the shut- in period, reservoir pressure builds up slowly. Many conventional methods, such as the indicative curve method, systematic analysis method and numerical simulation, are not applicable to determining an appropriate gas flow rate. Static data and dynamic performance show permeability capacity, kh is the most sensitive factor influencing well productivity, so criteria based on kh were proposed to classify vertical wells. All gas wells were classified into 4 groups. A multi-objective fuzzy optimization method, in which dimensionless gas flow rate, period of stable production, and recovery at the end of the stable production period were selected as optimizing objectives, was established to determine the reasonable range of gas flow rate. In this method, membership functions of above-mentioned optimizing factors and their weights were given. Moreover, to simplify calculation and facilitate field use, a simplified graphical illustration （or correlation） was given for the four classes of wells. Case study illustrates the applicability of the proposed method and graphical correlation, and an increase in cumulative gas production up to 37% is achieved and the well can produce at a constant flow rate for a long time.展开更多
Laser-induced breakdown spectroscopy(LIBS)has been applied to many fields for the quantitative analysis of diverse materials.Improving the prediction accuracy of LIBS regression models is still of great significance f...Laser-induced breakdown spectroscopy(LIBS)has been applied to many fields for the quantitative analysis of diverse materials.Improving the prediction accuracy of LIBS regression models is still of great significance for the Mars exploration in the near future.In this study,we explored the quantitative analysis of LIBS for the one-dimensional Chem Cam(an instrument containing a LIBS spectrometer and a Remote Micro-Imager)spectral data whose spectra are produced by the Chem Cam team using LIBS under the Mars-like atmospheric conditions.We constructed a convolutional neural network(CNN)regression model with unified parameters for all oxides,which is efficient and concise.CNN that has the excellent capability of feature extraction can effectively overcome the chemical matrix effects that impede the prediction accuracy of regression models.Firstly,we explored the effects of four activation functions on the performance of the CNN model.The results show that the CNN model with the hyperbolic tangent(tanh)function outperforms the CNN models with the other activation functions(the rectified linear unit function,the linear function and the Sigmoid function).Secondly,we compared the performance among the CNN models using different optimization methods.The CNN model with the stochastic gradient descent optimization and the initial learning rate?=?0.0005 achieves satisfactory performance compared to the other CNN models.Finally,we compared the performance of the CNN model,the model based on support vector regression(SVR)and the model based on partial least square regression(PLSR).The results exhibit the CNN model is superior to the SVR model and the PLSR model for all oxides.Based on the above analysis,we conclude the CNN regression model can effectively improve the prediction accuracy of LIBS.展开更多
文摘Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.
基金This work was supported by the National Natural Science Foundation of China(10071037)
文摘In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model function, the collinear scaling formula, quadratic approximation and interpolation. All the parameters in this model are determined by objective function interpolation condition. A new derivative free method is developed based upon this model and the global convergence of this new method is proved without any information on gradient.
基金acknowledge the Fundamental Research Funds for the Central Universities(Grants No 309190112102)the Natural Science Foundation of Jiangsu Province(Grants No BK20200493).
文摘In this paper,a passive muzzle arc control device(PMACD)of the augmented railguns is studied.By discussing its performance at different numbers of extra rails,a parameter optimization model is proposed.Through the calculation model,it is found that the PMACD works well in the simple railgun,which refers to the gun that there is only one pair of rails in the inner bore.The PMACD may decrease the simple railgun’s armature peak current and muzzle arc,but affect its muzzle velocity not much.However,in the augmented railguns it has different characteristics.If the parameters of the PMACD are not selected suitable.It may increase the armature peak current and muzzle arc,but greatly decrease the velocity.The reason for this problem is that the extra rails generate a strong magnetic field in front of the armature,which induces a large current to change the armature current.It is also found that when the resistance and inductance parameters of the PMACD satisfy with the optimization formula,the PMACD can also play a good role in arc suppression in the augmented railguns.Experiments of an augmented railgun with a stainless steel PMACD are carried out to verify this optimization method.Results show that the muzzle arc is obviously controlled.This work may provide a reference for the design of the muzzle arc control device.
基金Funded by National Natural Science Foundation of China (No. 50905102)the Natural Science Foundation of Guangdong Province (Nos. 10151503101000033 and 8351503101000001)the Building Fund for the Academic Innovation Team of Shantou University (No. ITC10003)
文摘The paper presents a new solution of inverse displacement analysis of the general six degree-of-freedom serial robot.The inverse displacement analysis of the general serial robot is transformed into a minimization problem and then the optimization method is adopted to solve the nonlinear least squares problem with the analytic form of new Jacobian matrix.In this way,joint variables of the general serial robot can be searched out quickly under the desired precision when positions of the three non-collinear end effector points are given.Compared with the general Newton iterative method,the proposed algorithm can search out the solution when the robot is at the singular configuration and the initial configuration used in the optimization method may also be the singular configuration.So the convergence domain is bigger than that of the general Newton iterative method.Another advantage of the proposed algorithm is that positions of the three non-collinear end effector points are usually much easier to be measured than the orientation of the end effector.The inverse displacement analysis of the general 6R(six-revolute-joint) serial robot is illustrated as an example and the simulation results verify the efficiency of the proposed algorithm.Because the three non-collinear points can be selected at random,the method can be applied to any other types of serial robots.
基金supported by the National Natural Science Foundation of China(12171106)the Natural Science Foundation of Guangxi Province(2020GXNSFDA238017 and 2018GXNSFFA281007)the Shanghai Sailing Program(21YF1430300)。
文摘This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method for the discussed problem is proposed.First,we consider the problem of quadratic optimal(QO)approximation associated with the current feasible iteration point,and we split the QO into two small-scale QOs which can be solved in parallel.Second,a feasible descent direction for the problem is obtained and a new SQO-type method is proposed,namely,splitting feasible SQO(SF-SQO)method.Moreover,under suitable conditions,we analyse the global convergence,strong convergence and rate of superlinear convergence of the SF-SQO method.Finally,preliminary numerical experiments regarding the economic dispatch of a power system are carried out,and these show that the SF-SQO method is promising.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51675506 and 51275504)the German Research Foundation(DFG)(Grant Nos.#ZA 422/5-1 and#ZA 422/6-1)
文摘A topology optimization method based on the solid isotropic material with penalization interpolation scheme is utilized for designing gradient coils for use in magnetic resonance microscopy.Unlike the popular stream function method,the proposed method has design variables that are the distribution of conductive material.A voltage-driven transverse gradient coil is proposed to be used as micro-scale magnetic resonance imaging(MRI)gradient coils,thus avoiding introducing a coil-winding pattern and simplifying the coil configuration.The proposed method avoids post-processing errors that occur when the continuous current density is approximated by discrete wires in the stream function approach.The feasibility and accuracy of the method are verified through designing the z-gradient and y-gradient coils on a cylindrical surface.Numerical design results show that the proposed method can provide a new coil layout in a compact design space.
基金Sponsored by the National Program"973"Project (2005CB623906)
文摘In order to implement the optimal design of the indoor thermal comfort based on the numerical modeling method, the numerical calculation platform is combined seamlessly with the data-processing platform, and an interactive numerical calculation platform which includes the functions of numerical simulation and optimization is established. The artificial neural network （ANN） and the greedy strategy are introduced into the hill-climbing pattern heuristic search process, and the optimizing search direction can be predicted by using small samples; when searching along the direction using the greedy strategy, the optimal values can be quickly approached. Therefore, excessive external calling of the numerical modeling process can be avoided, and the optimization time is decreased obviously. The experimental results indicate that the satisfied output parameters of air conditioning can be quickly given out based on the interactive numerical calculation platform and the improved search method, and the optimization for indoor thermal comfort can be completed.
基金the deputy director of Research and Development in Atomic Energy of Iran for financial support as well as Nuclear Science and Technology Research Institute for technical support
文摘The present work dealt with the preconcentration of rare earth elements in Saghand ore(Yazd province,Iran)which was achieved by Humphrey spiral using orthogonal optimization method after scrubbing the sample at 45%solid pulp density for 30 min.The pulp was diluted and was fed to a Humphrey spiral for upgrading.The process parameters considered were feed size,feed solids and feed rate,and Taguchi’s L9(34)orthogonal array(OA)was selected for optimization of the process.The results show that the feed rate and feed size were more significant than the other operation parameters of the process.It was also found that under optimal conditions,the concentrate grade of rare earth elements increased from2860 10 6to 6050 10 6and recovery reached to 58%.
文摘The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.
基金supported in part by the CNRST Morocco,the Volkswagen Foundation:Grant number I/79315Hydromed project
文摘In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.
基金Project supported by the National Natural Science Foundation of China(Grant No.51076002)the National Basis Research Program of China(Grant No.2013CA328900)the Key Project of Complicated Electromagnetic Environment Laboratory of CAEP,China(Grant No.2015E0-01-1)
文摘Spectral and directional control of thermal emission based on excitation of confined electromagnetic resonant modes paves a viable way for the design and construction of microscale thermal emitters/absorbers. In this paper, we present numerical simulation results of the thermal radiative properties of a silicon carbide（Si C） thermal emitter/absorber composed of periodic microstructures. We illustrate different electromagnetic resonant modes which can be excited with the structure,such as surface phonon polaritons, magnetic polaritons and photonic crystal modes, and the process of radiation spectrum optimization based on a non-linear optimization algorithm. We show that the spectral and directional control of thermal emission/absorption can be efficiently achieved by adjusting the geometrical parameters of the structure. Moreover, the optimized spectrum is insensitive to 3% dimension modification.
文摘The basic configuration of a new type of subsea pipeline connector was proposed based on the press-fitting principle, and a parametric finite element model was created using APDL language in ANSYS. Combining the finite element model and optimization technology, the dimension optimization aiming at obtaining the minimum loading force and the optimum sealing performance was designed by the zero order optimization method. Experiments of the optimized connector were carried out. The results indicate that the optimum structural design significantly improved the indicators of the minimum loading force and sealing performance of the connector.
基金This work was supported by the Scientific Research Projects of Tianjin Educational Committee(No.2020KJ029)。
文摘The prediction process often runs with small samples and under-sufficient information.To target this problem,we propose a performance comparison study that combines prediction and optimization algorithms based on experimental data analysis.Through a large number of prediction and optimization experiments,the accuracy and stability of the prediction method and the correction ability of the optimization method are studied.First,five traditional single-item prediction methods are used to process small samples with under-sufficient information,and the standard deviation method is used to assign weights on the five methods for combined forecasting.The accuracy of the prediction results is ranked.The mean and variance of the rankings reflect the accuracy and stability of the prediction method.Second,the error elimination prediction optimization method is proposed.To make,the prediction results are corrected by error elimination optimization method(EEOM),Markov optimization and two-layer optimization separately to obtain more accurate prediction results.The degree improvement and decline are used to reflect the correction ability of the optimization method.The results show that the accuracy and stability of combined prediction are the best in the prediction methods,and the correction ability of error elimination optimization is the best in the optimization methods.The combination of the two methods can well solve the problem of prediction with small samples and under-sufficient information.Finally,the accuracy of the combination of the combined prediction and the error elimination optimization is verified by predicting the number of unsafe events in civil aviation in a certain year.
基金Supported by the Project of Ministry of Education and Finance(No.200512)the Project of the State Key Laboratory of ocean engineering(GKZD010053-10)
文摘A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore,the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship,suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.
基金Supported by the National Natural Science Foundation of China(51376090,51676099)
文摘In this paper,size and shape optimization problem of a machine gun system is addressed with an efficient hybrid method,in which a novel and flexible mesh morphing technique is employed to achieve fast parameterization and modification of complexity structure without going back to CAD for reconstruction of geometric models or to finite element analysis（ FEA） for remodeling. Design of experiments（ DOE） and response surface method（ RSM） are applied to approximate the constitutive parameters of a machine gun system based on experimental tests. Further FEA,secondary development technique and genetic algorithm（ GA） are introduced to find all the optimal solutions in one go and the optimal design of the demonstrated machine gun system is obtained. Results of the rigid-flexible coupling dynamic analysis and exterior ballistics calculation validate the proposed methodology,which is relatively time-saving,reliable and has the potential to solve similar problems.
基金supported by the National Natural Science Foundation of China(Grant No.11205115)the Program for Academic Leader Reserve Candidates in Tongling University(Grant No.2014tlxyxs30)the 2014-year Program for Excellent Youth Talents in University of Anhui Province,China
文摘Song [Song D 2004 Phys. Rev. A69034301] first proposed two key distribution schemes with the symmetry feature.We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization.Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states.
基金Project supported by the National Natural Science Foundation of China(Grant No.62101004)the Opening Research Fund of Anhui Engineering Research Center of Vehicle Display Integrated Systems(Grant No.VDIS2023C05)+1 种基金the Opening Project of Key Laboratory of Electric Drive and Control of Anhui Province,China(Grant No.DQKJ202309)the Excellent Scientific Research and Innovation Teams of Anhui Province,China(Grant No.2022AH010059)。
文摘The design and fabrication method of magnetic field coils with high uniformity is essential for atomic magnetometers.In this paper,a novel design strategy for cylindrical uniform coils is first proposed,which combines the target-field method(TFM)with an optimized slime mold algorithm(SMA)to determine optimal structure parameters.Then,the realization method for the designed cylindrical coil by using the flexible printed circuit(FPC)technology is presented.Compared with traditional fabrication methods,this method has advantages in excellent flexibility and bending property,making the coils easier to be arranged in limited space.Moreover,the manufacturing process of the FPC technology via a specific cylindrical uniform magnetic field coil is discussed in detail,and the successfully realized coil is well tested in a verification system.By comparing the uniformity performance of the experimental coil with the simulation one,the effectiveness of the FPC technology in producing cylindrical coils has been well validated.
文摘A novel data-driven, soft sensor based on support vector regression （SVR） integrated with a data compression technique was developed to predict the product quality for the hydrodesulfurization （HDS） process. A wide range of experimental data was taken from a HDS setup to train and test the SVR model. Hyper-parameter tuning is one of the main challenges to improve predictive accuracy of the SVR model. Therefore, a hybrid approach using a combination of genetic algorithm （GA） and sequential quadratic programming （SQP） methods （GA-SQP） was developed. Performance of different optimization algorithms including GA-SQP, GA, pattern search （PS）, and grid search （GS） indicated that the best average absolute relative error （AARE）, squared correlation coefficient （R2）, and computation time （CT） （AARE = 0.0745, R2 = 0.997 and CT = 56 s） was accomplished by the hybrid algorithm. Moreover, to reduce the CT and improve the accuracy of the SVR model, the vector quantization （VQ） technique was used. The results also showed that the VQ technique can decrease the training time and improve prediction performance of the SVR model. The proposed method can provide a robust, soft sensor in a wide range of sulfur contents with good accuracy.
基金National Natural Science Foundation of China (NO. Z02047)CNPC Program (NO.Z03014).
文摘The Sulige tight gas reservoir is characterized by low-pressure, low-permeability and lowabundance. During production, gas flow rate and reservoir pressure decrease sharply; and in the shut- in period, reservoir pressure builds up slowly. Many conventional methods, such as the indicative curve method, systematic analysis method and numerical simulation, are not applicable to determining an appropriate gas flow rate. Static data and dynamic performance show permeability capacity, kh is the most sensitive factor influencing well productivity, so criteria based on kh were proposed to classify vertical wells. All gas wells were classified into 4 groups. A multi-objective fuzzy optimization method, in which dimensionless gas flow rate, period of stable production, and recovery at the end of the stable production period were selected as optimizing objectives, was established to determine the reasonable range of gas flow rate. In this method, membership functions of above-mentioned optimizing factors and their weights were given. Moreover, to simplify calculation and facilitate field use, a simplified graphical illustration （or correlation） was given for the four classes of wells. Case study illustrates the applicability of the proposed method and graphical correlation, and an increase in cumulative gas production up to 37% is achieved and the well can produce at a constant flow rate for a long time.
基金supported by the Pre-research project on Civil Aerospace Technologies(No.D020102)funded by China National Space Administration(CNSA)the funding from National Natural Science Foundation of China(Nos.U1931211,41573056)+1 种基金the Natural Science Foundation of Shandong Province(No.ZR2019MD008)the Major Research Project of Shandong Province(No.GG201809130208)。
文摘Laser-induced breakdown spectroscopy(LIBS)has been applied to many fields for the quantitative analysis of diverse materials.Improving the prediction accuracy of LIBS regression models is still of great significance for the Mars exploration in the near future.In this study,we explored the quantitative analysis of LIBS for the one-dimensional Chem Cam(an instrument containing a LIBS spectrometer and a Remote Micro-Imager)spectral data whose spectra are produced by the Chem Cam team using LIBS under the Mars-like atmospheric conditions.We constructed a convolutional neural network(CNN)regression model with unified parameters for all oxides,which is efficient and concise.CNN that has the excellent capability of feature extraction can effectively overcome the chemical matrix effects that impede the prediction accuracy of regression models.Firstly,we explored the effects of four activation functions on the performance of the CNN model.The results show that the CNN model with the hyperbolic tangent(tanh)function outperforms the CNN models with the other activation functions(the rectified linear unit function,the linear function and the Sigmoid function).Secondly,we compared the performance among the CNN models using different optimization methods.The CNN model with the stochastic gradient descent optimization and the initial learning rate?=?0.0005 achieves satisfactory performance compared to the other CNN models.Finally,we compared the performance of the CNN model,the model based on support vector regression(SVR)and the model based on partial least square regression(PLSR).The results exhibit the CNN model is superior to the SVR model and the PLSR model for all oxides.Based on the above analysis,we conclude the CNN regression model can effectively improve the prediction accuracy of LIBS.
