In this paper, we present a highly efficient structure determination pipeline software suite(X^2 DF) that is based on the "Parameter space screening" method, by combining the popular crystallographic structu...In this paper, we present a highly efficient structure determination pipeline software suite(X^2 DF) that is based on the "Parameter space screening" method, by combining the popular crystallographic structure determination programs and high-performance parallel computing. The phasing method employed in X^2 DF is based on the single-wavelength anomalous diffraction(SAD) theory. In the X^2 DF, the choice of crystallographic software, the input parameters to this software and the results display layout, are all parameters which users can select and screen automatically. Users may submit multiple structure determination jobs each time, and each job uses a slightly different set of input parameters or programs. Upon completion, the results of the calculation performed can be displayed, harvested, and analyzed by using the graphical user interface(GUI) of the system. We have applied the X^2 DF successfully to many cases including the cases that the structure solutions fail to be yielded by using manual approaches.展开更多
This paper presents a modified method to solve multi-objective nonlinear programming problems with fuzzy parameters in its objective functions and these fuzzy parameters are characterized by fuzzy numbers. The modifie...This paper presents a modified method to solve multi-objective nonlinear programming problems with fuzzy parameters in its objective functions and these fuzzy parameters are characterized by fuzzy numbers. The modified method is based on normalized trade-off weights. The obtained stability set corresponding to α-Pareto optimal solution, using our method, is investigated. Moreover, an algorithm for obtaining any subset of the parametric space which has the same corresponding α-Pareto optimal solution is presented. Finally, a numerical example to illustrate our method is also given.展开更多
Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SIND...Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SINDy)rule to restore nonlinear equations,there also exist obstacles.One is the excessive dependence on empirical parameters,which increases the difficulty of data pre-processing.Another one is the coexistence of multiple coefficient vectors,which causes the optimal solution to be drowned in multiple solutions.The third one is the composition of basic function,which is exclusively applicable to specific equations.In this article,a local sparse screening identification algorithm(LSSI)is proposed to identify nonlinear systems.First,we present the k-neighbor parameter to replace all empirical parameters in data filtering.Second,we combine the mean error screening method with the SINDy algorithm to select the optimal one from multiple solutions.Third,the time variable t is introduced to expand the scope of the SINDy algorithm.Finally,the LSSI algorithm is applied to recover a classic ODE and a bi-stable energy harvester system.The results show that the new algorithm improves the ability of noise immunity and optimal parameters identification provides a desired foundation for nonlinear analyses.展开更多
This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determi...This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determining bounds of system response.The screening method is firstly used to reduce the scale of active uncertain parameters.The sequential high-order polynomials surrogate models are then used to approximate the dynamic system’s response at each time step.To reduce the sampling cost of constructing surrogate model,the interaction effect among uncertain parameters is gradually added to the surrogate model by sequentially incorporating samples from a candidate set,which is composed of vertices and inner grid points.Finally,the points that may produce the bounds of the system response at each time step are searched using the surrogate models.The optimization algorithm is used to locate extreme points,which contribute to determining the inner points producing system response bounds.Additionally,all vertices are also checked using the surrogate models.A vehicle nonlinear dynamic model with 72 uncertain parameters is presented to demonstrate the accuracy and efficiency of the proposed uncertain computational method.展开更多
利用离散单元法(Discrete element method,DEM)对球形颗粒群以及非球形颗粒群的筛分过程进行了仿真并开展了实验研究,结果表明球形和非球形颗粒的仿真与实验中筛分效率的变化是一致的,但非球形颗粒的仿真结果与实验结果更接近.正交设计...利用离散单元法(Discrete element method,DEM)对球形颗粒群以及非球形颗粒群的筛分过程进行了仿真并开展了实验研究,结果表明球形和非球形颗粒的仿真与实验中筛分效率的变化是一致的,但非球形颗粒的仿真结果与实验结果更接近.正交设计多组模拟试验,分析了各振动参数(振动频率、振幅以及筛面倾角)对颗粒分布曲线、筛分效率以及物料平均运输速度的影响规律.对正交试验表中的数据进行多元非线性拟合,得到筛分效率与振动参数间的关系式;并在此关系式的基础上,对振动参数进行优化设计,得到了最优振动参数且在仿真中得到了验证.研究内容不但为高频振网筛振动参数的设计提供了理论依据,而且为研究高频振动系统的筛分机理提供了实验和仿真数据支持.展开更多
文摘In this paper, we present a highly efficient structure determination pipeline software suite(X^2 DF) that is based on the "Parameter space screening" method, by combining the popular crystallographic structure determination programs and high-performance parallel computing. The phasing method employed in X^2 DF is based on the single-wavelength anomalous diffraction(SAD) theory. In the X^2 DF, the choice of crystallographic software, the input parameters to this software and the results display layout, are all parameters which users can select and screen automatically. Users may submit multiple structure determination jobs each time, and each job uses a slightly different set of input parameters or programs. Upon completion, the results of the calculation performed can be displayed, harvested, and analyzed by using the graphical user interface(GUI) of the system. We have applied the X^2 DF successfully to many cases including the cases that the structure solutions fail to be yielded by using manual approaches.
文摘This paper presents a modified method to solve multi-objective nonlinear programming problems with fuzzy parameters in its objective functions and these fuzzy parameters are characterized by fuzzy numbers. The modified method is based on normalized trade-off weights. The obtained stability set corresponding to α-Pareto optimal solution, using our method, is investigated. Moreover, an algorithm for obtaining any subset of the parametric space which has the same corresponding α-Pareto optimal solution is presented. Finally, a numerical example to illustrate our method is also given.
基金The work was supported by the National Science Foundation of China(grant nos.11772218 and 11872044)China-UK NSFC-RS Joint Project(grant nos.11911530177 in China and IE181496 in the UK)Tianjin Research Program of Application Foundation and Advanced Technology(grant no.17JCYBJC18900).
文摘Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SINDy)rule to restore nonlinear equations,there also exist obstacles.One is the excessive dependence on empirical parameters,which increases the difficulty of data pre-processing.Another one is the coexistence of multiple coefficient vectors,which causes the optimal solution to be drowned in multiple solutions.The third one is the composition of basic function,which is exclusively applicable to specific equations.In this article,a local sparse screening identification algorithm(LSSI)is proposed to identify nonlinear systems.First,we present the k-neighbor parameter to replace all empirical parameters in data filtering.Second,we combine the mean error screening method with the SINDy algorithm to select the optimal one from multiple solutions.Third,the time variable t is introduced to expand the scope of the SINDy algorithm.Finally,the LSSI algorithm is applied to recover a classic ODE and a bi-stable energy harvester system.The results show that the new algorithm improves the ability of noise immunity and optimal parameters identification provides a desired foundation for nonlinear analyses.
基金supported by the National Natural Science Foundation of China(Grant No.12272142)Fundamental Research Funds for the Central Universities(Grant No.2172021XXJS048)。
文摘This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determining bounds of system response.The screening method is firstly used to reduce the scale of active uncertain parameters.The sequential high-order polynomials surrogate models are then used to approximate the dynamic system’s response at each time step.To reduce the sampling cost of constructing surrogate model,the interaction effect among uncertain parameters is gradually added to the surrogate model by sequentially incorporating samples from a candidate set,which is composed of vertices and inner grid points.Finally,the points that may produce the bounds of the system response at each time step are searched using the surrogate models.The optimization algorithm is used to locate extreme points,which contribute to determining the inner points producing system response bounds.Additionally,all vertices are also checked using the surrogate models.A vehicle nonlinear dynamic model with 72 uncertain parameters is presented to demonstrate the accuracy and efficiency of the proposed uncertain computational method.
文摘利用离散单元法(Discrete element method,DEM)对球形颗粒群以及非球形颗粒群的筛分过程进行了仿真并开展了实验研究,结果表明球形和非球形颗粒的仿真与实验中筛分效率的变化是一致的,但非球形颗粒的仿真结果与实验结果更接近.正交设计多组模拟试验,分析了各振动参数(振动频率、振幅以及筛面倾角)对颗粒分布曲线、筛分效率以及物料平均运输速度的影响规律.对正交试验表中的数据进行多元非线性拟合,得到筛分效率与振动参数间的关系式;并在此关系式的基础上,对振动参数进行优化设计,得到了最优振动参数且在仿真中得到了验证.研究内容不但为高频振网筛振动参数的设计提供了理论依据,而且为研究高频振动系统的筛分机理提供了实验和仿真数据支持.
