To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. ...To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.展开更多
Population-based algorithms have been used in many real-world problems.Bat algorithm(BA)is one of the states of the art of these approaches.Because of the super bat,on the one hand,BA can converge quickly;on the other...Population-based algorithms have been used in many real-world problems.Bat algorithm(BA)is one of the states of the art of these approaches.Because of the super bat,on the one hand,BA can converge quickly;on the other hand,it is easy to fall into local optimum.Therefore,for typical BA algorithms,the ability of exploration and exploitation is not strong enough and it is hard to find a precise result.In this paper,we propose a novel bat algorithm based on cross boundary learning(CBL)and uniform explosion strategy(UES),namely BABLUE in short,to avoid the above contradiction and achieve both fast convergence and high quality.Different from previous opposition-based learning,the proposed CBL can expand the search area of population and then maintain the ability of global exploration in the process of fast convergence.In order to enhance the ability of local exploitation of the proposed algorithm,we propose UES,which can achieve almost the same search precise as that of firework explosion algorithm but consume less computation resource.BABLUE is tested with numerous experiments on unimodal,multimodal,one-dimensional,high-dimensional and discrete problems,and then compared with other typical intelligent optimization algorithms.The results show that the proposed algorithm outperforms other algorithms.展开更多
To study the diagnostic problem of Wire-OR （W-O） interconnect fault of PCB （Printed Circuit Board）, five modified boundary scan adaptive algorithms for interconnect test are put forward. These algorithms apply Glo...To study the diagnostic problem of Wire-OR （W-O） interconnect fault of PCB （Printed Circuit Board）, five modified boundary scan adaptive algorithms for interconnect test are put forward. These algorithms apply Global-diagnosis sequence algorithm to replace the equal weight algorithm of primary test, and the test time is shortened without changing the fault diagnostic capability. The descriptions of five modified adaptive test algorithms are presented, and the capability comparison between the modified algorithm and the original algorithm is made to prove the validity of these algorithms.展开更多
The present study proposes a stochastic simulation scheme to model reactive boundaries through a position jump process which can be readily implemented into the Inhomogeneous Stochastic Simulation Algorithm by modifyi...The present study proposes a stochastic simulation scheme to model reactive boundaries through a position jump process which can be readily implemented into the Inhomogeneous Stochastic Simulation Algorithm by modifying the propensity of the diffusive jump over the reactive boundary. As compared to the literature, the present approach does not require any correction factors for the propensity. Also, the current expression relaxes the constraint on the compartment size allowing the problem to be solved with a coarser grid and therefore saves considerable computational cost. The modified algorithm is then applied to simulate three reaction-diffusion systems with reactive boundaries.展开更多
In the present work,autonomous mobile robot(AMR)system is intended with basic behaviour,one is obstacle avoidance and the other is target seeking in various environments.The AMR is navigated using fuzzy logic,neural n...In the present work,autonomous mobile robot(AMR)system is intended with basic behaviour,one is obstacle avoidance and the other is target seeking in various environments.The AMR is navigated using fuzzy logic,neural network and adaptive neurofuzzy inference system(ANFIS)controller with safe boundary algorithm.In this method of target seeking behaviour,the obstacle avoidance at every instant improves the performance of robot in navigation approach.The inputs to the controller are the signals from various sensors fixed at front face,left and right face of the AMR.The output signal from controller regulates the angular velocity of both front power wheels of the AMR.The shortest path is identified using fuzzy,neural network and ANFIS techniques with integrated safe boundary algorithm and the predicted results are validated with experimentation.The experimental result has proven that ANFIS with safe boundary algorithm yields better performance in navigation,in particular with curved/irregular obstacles.展开更多
A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm （FE-BI-MLFMA）. Among many algorithms of FE-BI-M...A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm （FE-BI-MLFMA）. Among many algorithms of FE-BI-MLFMA, the decomposition algorithm （DA） is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization. On the basis of the DA, the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finiteelement method and the parallelized MLFMA for the matrix from the boundary integral method respectively. The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor- mance computing platform CEMS-Liuhui. Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy, efficiency, and generality.展开更多
As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most q...As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.展开更多
Active semi-supervised fuzzy clustering integrates fuzzy clustering techniques with limited labeled data,guided by active learning,to enhance classification accuracy,particularly in complex and ambiguous datasets.Alth...Active semi-supervised fuzzy clustering integrates fuzzy clustering techniques with limited labeled data,guided by active learning,to enhance classification accuracy,particularly in complex and ambiguous datasets.Although several active semi-supervised fuzzy clustering methods have been developed previously,they typically face significant limitations,including high computational complexity,sensitivity to initial cluster centroids,and difficulties in accurately managing boundary clusters where data points often overlap among multiple clusters.This study introduces a novel Active Semi-Supervised Fuzzy Clustering algorithm specifically designed to identify,analyze,and correct misclassified boundary elements.By strategically utilizing labeled data through active learning,our method improves the robustness and precision of cluster boundary assignments.Extensive experimental evaluations conducted on three types of datasets—including benchmark UCI datasets,synthetic data with controlled boundary overlap,and satellite imagery—demonstrate that our proposed approach achieves superior performance in terms of clustering accuracy and robustness compared to existing active semi-supervised fuzzy clustering methods.The results confirm the effectiveness and practicality of our method in handling real-world scenarios where precise cluster boundaries are critical.展开更多
In regions characterized with great mining depths,complex topography,and intense geological activities,solely relying on lateral pressure coefficients or linear boundary conditions for predicting the in situ stress fi...In regions characterized with great mining depths,complex topography,and intense geological activities,solely relying on lateral pressure coefficients or linear boundary conditions for predicting the in situ stress field of rock bodies can induce substantial deviations and limitations.This study focuses on a typical karst area in Southwest Guizhou,China as its research background.It employs a hybrid approach integrating machine learning,numerical simulations,and field experiments to develop an optimization algorithm for nonlinear prediction of the complex three-dimensional(3D)in situ stress fields.Through collecting and fitting analysis of in situ stress measurement data from the karst region,the distributions of in situ stresses with depth were identified with nonlinear boundary conditions.A prediction model for in situ stress was then established based on artificial neural network(ANN)and genetic algorithm(GA)approach,validated in the typical karst landscape mine,Jinfeng Gold Mine.The results demonstrate that the model's predictions align well with actual measurements,showcasing consistency and regularity.Specifically,the error between the predicted and actual values of the maximum horizontal principal stress was the smallest,with an absolute error 0.01-3 MPa and a relative error of 0.04-15.31%.This model accurately and effectively predicts in situ stresses in complex geological areas.展开更多
The low-Reynolds-number full developed turbulent flow in channels is simulated using large eddy simulation（LES）method with the preconditioned algorithm and the dynamic subgrid-scale model,with a given disturbance in...The low-Reynolds-number full developed turbulent flow in channels is simulated using large eddy simulation（LES）method with the preconditioned algorithm and the dynamic subgrid-scale model,with a given disturbance in inlet boundary,after a short development section.The inlet Reynolds number based on momentum thickness is 670.The computed results show good agreement with direct numerical simulation（DNS）,which include root mean square fluctuated velocity distribution and average velocity distribution.It is also found that the staggered phenomenon of the coherent structures is caused by sub-harmonic.The results clearly show the formation and evolution of horseshoe vortex in the turbulent boundary layer,including horseshoe vortex structure with a pair of streamwise vortexes and one-side leg of horseshoe vortex.Based on the results,the development of the horseshoe-shaped coherent structures is analyzed in turbulent boundary layer.展开更多
As an efficient artificial truncating boundary condition, conformal perfectly matched layer (CPML) is a kind of multilayer anisotropic absorbing media. To reduce computing effort of CPML, this article proposes a layer...As an efficient artificial truncating boundary condition, conformal perfectly matched layer (CPML) is a kind of multilayer anisotropic absorbing media. To reduce computing effort of CPML, this article proposes a layer-oriented element integration algorithm. In this algorithm, the relative dielectric constant and permeability are considered as constants for each the very thin monolayer of CPML, and the element integration of multilayer along the normal direction is substituted by the element integration of m...展开更多
Bird swarm algorithm(BSA), a novel bio-inspired algorithm, has good performance in solving numerical optimization problems. In this paper, a new improved bird swarm algorithm is conducted to solve unconstrained optimi...Bird swarm algorithm(BSA), a novel bio-inspired algorithm, has good performance in solving numerical optimization problems. In this paper, a new improved bird swarm algorithm is conducted to solve unconstrained optimization problems. To enhance the performance of BSA, handling boundary constraints are applied to fix the candidate solutions that are out of boundary or on the boundary in iterations, which can boost the diversity of the swarm to avoid the premature problem. On the other hand, we accelerate the foraging behavior by adjusting the cognitive and social components the sin cosine coefficients. Simulation results and comparison based on sixty benchmark functions demonstrate that the improved BSA has superior performance over the BSA in terms of almost all functions.展开更多
The two-archive 2 algorithm(Two_Arch2) is a manyobjective evolutionary algorithm for balancing the convergence,diversity,and complexity using diversity archive(DA) and convergence archive(CA).However,the individuals i...The two-archive 2 algorithm(Two_Arch2) is a manyobjective evolutionary algorithm for balancing the convergence,diversity,and complexity using diversity archive(DA) and convergence archive(CA).However,the individuals in DA are selected based on the traditional Pareto dominance which decreases the selection pressure in the high-dimensional problems.The traditional algorithm even cannot converge due to the weak selection pressure.Meanwhile,Two_Arch2 adopts DA as the output of the algorithm which is hard to maintain diversity and coverage of the final solutions synchronously and increase the complexity of the algorithm.To increase the evolutionary pressure of the algorithm and improve distribution and convergence of the final solutions,an ε-domination based Two_Arch2 algorithm(ε-Two_Arch2) for many-objective problems(MaOPs) is proposed in this paper.In ε-Two_Arch2,to decrease the computational complexity and speed up the convergence,a novel evolutionary framework with a fast update strategy is proposed;to increase the selection pressure,ε-domination is assigned to update the individuals in DA;to guarantee the uniform distribution of the solution,a boundary protection strategy based on I_(ε+) indicator is designated as two steps selection strategies to update individuals in CA.To evaluate the performance of the proposed algorithm,a series of benchmark functions with different numbers of objectives is solved.The results demonstrate that the proposed method is competitive with the state-of-the-art multi-objective evolutionary algorithms and the efficiency of the algorithm is significantly improved compared with Two_Arch2.展开更多
In this paper, an absorbing Fictitious Boundary Condition (FBC) is presented to generate an iterative Domain Decomposition Method (DDM) for analyzing waveguide problems.The relaxed algorithm is introduced to improve t...In this paper, an absorbing Fictitious Boundary Condition (FBC) is presented to generate an iterative Domain Decomposition Method (DDM) for analyzing waveguide problems.The relaxed algorithm is introduced to improve the iterative convergence. And the matrix equations are solved using the multifrontal algorithm. The resulting CPU time is greatly reduced.Finally, a number of numerical examples are given to illustrate its accuracy and efficiency.展开更多
The scaled boundary finite element method （SBFEM） is a recently developed numerical method combining advantages of both finite element methods （FEM） and boundary element methods （BEM） and with its own special fe...The scaled boundary finite element method （SBFEM） is a recently developed numerical method combining advantages of both finite element methods （FEM） and boundary element methods （BEM） and with its own special features as well. One of the most prominent advantages is its capability of calculating stress intensity factors （SIFs） directly from the stress solutions whose singularities at crack tips are analytically represented. This advantage is taken in this study to model static and dynamic fracture problems. For static problems, a remeshing algorithm as simple as used in the BEM is developed while retaining the generality and flexibility of the FEM. Fully-automatic modelling of the mixed-mode crack propagation is then realised by combining the remeshing algorithm with a propagation criterion. For dynamic fracture problems, a newly developed series-increasing solution to the SBFEM governing equations in the frequency domain is applied to calculate dynamic SIFs. Three plane problems are modelled. The numerical results show that the SBFEM can accurately predict static and dynamic SIFs, cracking paths and load-displacement curves, using only a fraction of degrees of freedom generally needed by the traditional finite element methods.展开更多
For the structural-acoustic radiation optimization problem under external loading,acoustic radiation power was considered to be an objective function in the optimization method. The finite element method(FEM) and boun...For the structural-acoustic radiation optimization problem under external loading,acoustic radiation power was considered to be an objective function in the optimization method. The finite element method(FEM) and boundary element method(BEM) were adopted in numerical calculations,and structural response and the acoustic response were assumed to be de-coupled in the analysis. A genetic algorithm was used as the strategy in optimization. In order to build the relational expression of the pressure objective function and the power objective function,the enveloping surface model was used to evaluate pressure in the acoustic domain. By taking the stiffened panel structural-acoustic optimization problem as an example,the acoustic power and field pressure after optimized was compared. Optimization results prove that this method is reasonable and effective.展开更多
A hybrid Cartesian structured grid method is proposed for solving moving boundary unsteady problems. The near body region is discretized by using the body-fitted structured grids, while the remaining computational dom...A hybrid Cartesian structured grid method is proposed for solving moving boundary unsteady problems. The near body region is discretized by using the body-fitted structured grids, while the remaining computational domain is tessellated with the generated Cartesian grids. As the body moves, the structured grids move with the body and the outer boundaries of inside grids are used to generate new holes in the outside adaptive Cartesian grid to facilitate data communication. By using the alternating digital tree （ADT） algorithm, the computational time of hole-cutting and identification of donor cells can be reduced significantly. A compressible solver for unsteady flow problems is developed. A cell-centered, second-order accurate finite volume method is employed in spatial discreti- zation and an implicit dual-time stepping low-upper symmetric Gauss-Seidei （LU-SGS） approach is employed in temporal discretization. Geometry-based adaptation is used during unsteady simulation time steps when boundary moves and the flow solution is interpolated from the old Cartesian grids to the new one with inverse distance weigh- ting interpolation formula. Both laminar and turbulent unsteady cases are tested to demonstrate the accuracy and efficiency of the proposed method. Then, a 2-D store separation problem is simulated. The result shows that the hybrid Cartesian grid method can handle the unsteady flow problems involving large-scale moving boundaries.展开更多
We present a numerical method based on genetic algorithm combined with a fictitious domain method for a shape optimization problem governed by an elliptic equation with Dirichlet boundary condition. The technique of t...We present a numerical method based on genetic algorithm combined with a fictitious domain method for a shape optimization problem governed by an elliptic equation with Dirichlet boundary condition. The technique of the immersed boundary method is incorporated into the framework of the fictitious domain method for solving the state equations. Contrary to the conventional methods, our method does not make use of the finite element discretization with obstacle fitted meshes. It conduces to overcoming difficulties arising from re-meshing operations in the optimization process. The method can lead to a reduction in computational effort and is easily programmable. It is applied to a shape reconstruction problem in the airfoil design. Numerical experiments demonstrate the efficiency of the proposed approach.展开更多
Immersed boundary method is a crucial method to deal with particle suspension flow.Particle shapes involved in such flow are usually simple geometry,such as sphere and ellipsoid,which can be conveniently represented b...Immersed boundary method is a crucial method to deal with particle suspension flow.Particle shapes involved in such flow are usually simple geometry,such as sphere and ellipsoid,which can be conveniently represented by the triangular surface grid.When the number of particles and resolution of the surface grid increase,calculating the hydrodynamic force on the particle surface through integration can be time-consuming.Hence,the present paper establishes a fast mapping method to evaluate immersed boundary hydrodynamic force.Firstly,the particle surface grid is generated by an initial triangular element grid.Subsequently,the initial surface grid is refined by bisection refinement to the desired resolution.The final step is to find the triangular element index on the particle triangular surface grid,which contains the projective point.Test cases show that the present mapping algorithm has good accuracy and efficiency for calculating hydrodynamic forces of particles.展开更多
基金the National Natural Science Foundation of China (90407007 60372001).
文摘To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.
基金Supported by the National Natural Science Foundation of China(61472289)the Open Project Program of the State Key Laboratory of Digital Manufacturing Equipment and Technology(DMETKF2017016)
文摘Population-based algorithms have been used in many real-world problems.Bat algorithm(BA)is one of the states of the art of these approaches.Because of the super bat,on the one hand,BA can converge quickly;on the other hand,it is easy to fall into local optimum.Therefore,for typical BA algorithms,the ability of exploration and exploitation is not strong enough and it is hard to find a precise result.In this paper,we propose a novel bat algorithm based on cross boundary learning(CBL)and uniform explosion strategy(UES),namely BABLUE in short,to avoid the above contradiction and achieve both fast convergence and high quality.Different from previous opposition-based learning,the proposed CBL can expand the search area of population and then maintain the ability of global exploration in the process of fast convergence.In order to enhance the ability of local exploitation of the proposed algorithm,we propose UES,which can achieve almost the same search precise as that of firework explosion algorithm but consume less computation resource.BABLUE is tested with numerous experiments on unimodal,multimodal,one-dimensional,high-dimensional and discrete problems,and then compared with other typical intelligent optimization algorithms.The results show that the proposed algorithm outperforms other algorithms.
文摘To study the diagnostic problem of Wire-OR （W-O） interconnect fault of PCB （Printed Circuit Board）, five modified boundary scan adaptive algorithms for interconnect test are put forward. These algorithms apply Global-diagnosis sequence algorithm to replace the equal weight algorithm of primary test, and the test time is shortened without changing the fault diagnostic capability. The descriptions of five modified adaptive test algorithms are presented, and the capability comparison between the modified algorithm and the original algorithm is made to prove the validity of these algorithms.
文摘The present study proposes a stochastic simulation scheme to model reactive boundaries through a position jump process which can be readily implemented into the Inhomogeneous Stochastic Simulation Algorithm by modifying the propensity of the diffusive jump over the reactive boundary. As compared to the literature, the present approach does not require any correction factors for the propensity. Also, the current expression relaxes the constraint on the compartment size allowing the problem to be solved with a coarser grid and therefore saves considerable computational cost. The modified algorithm is then applied to simulate three reaction-diffusion systems with reactive boundaries.
文摘In the present work,autonomous mobile robot(AMR)system is intended with basic behaviour,one is obstacle avoidance and the other is target seeking in various environments.The AMR is navigated using fuzzy logic,neural network and adaptive neurofuzzy inference system(ANFIS)controller with safe boundary algorithm.In this method of target seeking behaviour,the obstacle avoidance at every instant improves the performance of robot in navigation approach.The inputs to the controller are the signals from various sensors fixed at front face,left and right face of the AMR.The output signal from controller regulates the angular velocity of both front power wheels of the AMR.The shortest path is identified using fuzzy,neural network and ANFIS techniques with integrated safe boundary algorithm and the predicted results are validated with experimentation.The experimental result has proven that ANFIS with safe boundary algorithm yields better performance in navigation,in particular with curved/irregular obstacles.
文摘A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm （FE-BI-MLFMA）. Among many algorithms of FE-BI-MLFMA, the decomposition algorithm （DA） is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization. On the basis of the DA, the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finiteelement method and the parallelized MLFMA for the matrix from the boundary integral method respectively. The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor- mance computing platform CEMS-Liuhui. Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy, efficiency, and generality.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62172268 and 62302289)the Shanghai Science and Technology Project(Grant Nos.21JC1402800 and 23YF1416200)。
文摘As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.
文摘Active semi-supervised fuzzy clustering integrates fuzzy clustering techniques with limited labeled data,guided by active learning,to enhance classification accuracy,particularly in complex and ambiguous datasets.Although several active semi-supervised fuzzy clustering methods have been developed previously,they typically face significant limitations,including high computational complexity,sensitivity to initial cluster centroids,and difficulties in accurately managing boundary clusters where data points often overlap among multiple clusters.This study introduces a novel Active Semi-Supervised Fuzzy Clustering algorithm specifically designed to identify,analyze,and correct misclassified boundary elements.By strategically utilizing labeled data through active learning,our method improves the robustness and precision of cluster boundary assignments.Extensive experimental evaluations conducted on three types of datasets—including benchmark UCI datasets,synthetic data with controlled boundary overlap,and satellite imagery—demonstrate that our proposed approach achieves superior performance in terms of clustering accuracy and robustness compared to existing active semi-supervised fuzzy clustering methods.The results confirm the effectiveness and practicality of our method in handling real-world scenarios where precise cluster boundaries are critical.
基金financially supported by the National Natural Science Foundation of China(Grant No.52374118)the Science and Technology Support Project of Guizhou Province,China(Project Grant No.Qiankehe Support(2022)General 247).
文摘In regions characterized with great mining depths,complex topography,and intense geological activities,solely relying on lateral pressure coefficients or linear boundary conditions for predicting the in situ stress field of rock bodies can induce substantial deviations and limitations.This study focuses on a typical karst area in Southwest Guizhou,China as its research background.It employs a hybrid approach integrating machine learning,numerical simulations,and field experiments to develop an optimization algorithm for nonlinear prediction of the complex three-dimensional(3D)in situ stress fields.Through collecting and fitting analysis of in situ stress measurement data from the karst region,the distributions of in situ stresses with depth were identified with nonlinear boundary conditions.A prediction model for in situ stress was then established based on artificial neural network(ANN)and genetic algorithm(GA)approach,validated in the typical karst landscape mine,Jinfeng Gold Mine.The results demonstrate that the model's predictions align well with actual measurements,showcasing consistency and regularity.Specifically,the error between the predicted and actual values of the maximum horizontal principal stress was the smallest,with an absolute error 0.01-3 MPa and a relative error of 0.04-15.31%.This model accurately and effectively predicts in situ stresses in complex geological areas.
基金Supported by the National Natural Science Foundation of China(10772082)~~
文摘The low-Reynolds-number full developed turbulent flow in channels is simulated using large eddy simulation（LES）method with the preconditioned algorithm and the dynamic subgrid-scale model,with a given disturbance in inlet boundary,after a short development section.The inlet Reynolds number based on momentum thickness is 670.The computed results show good agreement with direct numerical simulation（DNS）,which include root mean square fluctuated velocity distribution and average velocity distribution.It is also found that the staggered phenomenon of the coherent structures is caused by sub-harmonic.The results clearly show the formation and evolution of horseshoe vortex in the turbulent boundary layer,including horseshoe vortex structure with a pair of streamwise vortexes and one-side leg of horseshoe vortex.Based on the results,the development of the horseshoe-shaped coherent structures is analyzed in turbulent boundary layer.
基金National Natural Science Foundation of China (10477018) Science and Technology Innovation Foundation of North-western Polytechnical University (W016143)
文摘As an efficient artificial truncating boundary condition, conformal perfectly matched layer (CPML) is a kind of multilayer anisotropic absorbing media. To reduce computing effort of CPML, this article proposes a layer-oriented element integration algorithm. In this algorithm, the relative dielectric constant and permeability are considered as constants for each the very thin monolayer of CPML, and the element integration of multilayer along the normal direction is substituted by the element integration of m...
基金Supported by the National Natural Science Foundation of China(11871383,71471140 and 11771058)
文摘Bird swarm algorithm(BSA), a novel bio-inspired algorithm, has good performance in solving numerical optimization problems. In this paper, a new improved bird swarm algorithm is conducted to solve unconstrained optimization problems. To enhance the performance of BSA, handling boundary constraints are applied to fix the candidate solutions that are out of boundary or on the boundary in iterations, which can boost the diversity of the swarm to avoid the premature problem. On the other hand, we accelerate the foraging behavior by adjusting the cognitive and social components the sin cosine coefficients. Simulation results and comparison based on sixty benchmark functions demonstrate that the improved BSA has superior performance over the BSA in terms of almost all functions.
基金supported by the National Natural Science Foundation of ChinaNatural Science Foundation of Zhejiang Province (52077203,LY19E070003)the Fundamental Research Funds for the Provincial Universities of Zhejiang (2021YW06)。
文摘The two-archive 2 algorithm(Two_Arch2) is a manyobjective evolutionary algorithm for balancing the convergence,diversity,and complexity using diversity archive(DA) and convergence archive(CA).However,the individuals in DA are selected based on the traditional Pareto dominance which decreases the selection pressure in the high-dimensional problems.The traditional algorithm even cannot converge due to the weak selection pressure.Meanwhile,Two_Arch2 adopts DA as the output of the algorithm which is hard to maintain diversity and coverage of the final solutions synchronously and increase the complexity of the algorithm.To increase the evolutionary pressure of the algorithm and improve distribution and convergence of the final solutions,an ε-domination based Two_Arch2 algorithm(ε-Two_Arch2) for many-objective problems(MaOPs) is proposed in this paper.In ε-Two_Arch2,to decrease the computational complexity and speed up the convergence,a novel evolutionary framework with a fast update strategy is proposed;to increase the selection pressure,ε-domination is assigned to update the individuals in DA;to guarantee the uniform distribution of the solution,a boundary protection strategy based on I_(ε+) indicator is designated as two steps selection strategies to update individuals in CA.To evaluate the performance of the proposed algorithm,a series of benchmark functions with different numbers of objectives is solved.The results demonstrate that the proposed method is competitive with the state-of-the-art multi-objective evolutionary algorithms and the efficiency of the algorithm is significantly improved compared with Two_Arch2.
文摘In this paper, an absorbing Fictitious Boundary Condition (FBC) is presented to generate an iterative Domain Decomposition Method (DDM) for analyzing waveguide problems.The relaxed algorithm is introduced to improve the iterative convergence. And the matrix equations are solved using the multifrontal algorithm. The resulting CPU time is greatly reduced.Finally, a number of numerical examples are given to illustrate its accuracy and efficiency.
基金The project supported by the National Natural Science Foundation of China (50579081)the Australian Research Council (DP0452681)The English text was polished by Keren Wang
文摘The scaled boundary finite element method （SBFEM） is a recently developed numerical method combining advantages of both finite element methods （FEM） and boundary element methods （BEM） and with its own special features as well. One of the most prominent advantages is its capability of calculating stress intensity factors （SIFs） directly from the stress solutions whose singularities at crack tips are analytically represented. This advantage is taken in this study to model static and dynamic fracture problems. For static problems, a remeshing algorithm as simple as used in the BEM is developed while retaining the generality and flexibility of the FEM. Fully-automatic modelling of the mixed-mode crack propagation is then realised by combining the remeshing algorithm with a propagation criterion. For dynamic fracture problems, a newly developed series-increasing solution to the SBFEM governing equations in the frequency domain is applied to calculate dynamic SIFs. Three plane problems are modelled. The numerical results show that the SBFEM can accurately predict static and dynamic SIFs, cracking paths and load-displacement curves, using only a fraction of degrees of freedom generally needed by the traditional finite element methods.
文摘For the structural-acoustic radiation optimization problem under external loading,acoustic radiation power was considered to be an objective function in the optimization method. The finite element method(FEM) and boundary element method(BEM) were adopted in numerical calculations,and structural response and the acoustic response were assumed to be de-coupled in the analysis. A genetic algorithm was used as the strategy in optimization. In order to build the relational expression of the pressure objective function and the power objective function,the enveloping surface model was used to evaluate pressure in the acoustic domain. By taking the stiffened panel structural-acoustic optimization problem as an example,the acoustic power and field pressure after optimized was compared. Optimization results prove that this method is reasonable and effective.
基金supported partly by the National Basic Research Program of China(″973″Program)(No.2014CB046200)
文摘A hybrid Cartesian structured grid method is proposed for solving moving boundary unsteady problems. The near body region is discretized by using the body-fitted structured grids, while the remaining computational domain is tessellated with the generated Cartesian grids. As the body moves, the structured grids move with the body and the outer boundaries of inside grids are used to generate new holes in the outside adaptive Cartesian grid to facilitate data communication. By using the alternating digital tree （ADT） algorithm, the computational time of hole-cutting and identification of donor cells can be reduced significantly. A compressible solver for unsteady flow problems is developed. A cell-centered, second-order accurate finite volume method is employed in spatial discreti- zation and an implicit dual-time stepping low-upper symmetric Gauss-Seidei （LU-SGS） approach is employed in temporal discretization. Geometry-based adaptation is used during unsteady simulation time steps when boundary moves and the flow solution is interpolated from the old Cartesian grids to the new one with inverse distance weigh- ting interpolation formula. Both laminar and turbulent unsteady cases are tested to demonstrate the accuracy and efficiency of the proposed method. Then, a 2-D store separation problem is simulated. The result shows that the hybrid Cartesian grid method can handle the unsteady flow problems involving large-scale moving boundaries.
文摘We present a numerical method based on genetic algorithm combined with a fictitious domain method for a shape optimization problem governed by an elliptic equation with Dirichlet boundary condition. The technique of the immersed boundary method is incorporated into the framework of the fictitious domain method for solving the state equations. Contrary to the conventional methods, our method does not make use of the finite element discretization with obstacle fitted meshes. It conduces to overcoming difficulties arising from re-meshing operations in the optimization process. The method can lead to a reduction in computational effort and is easily programmable. It is applied to a shape reconstruction problem in the airfoil design. Numerical experiments demonstrate the efficiency of the proposed approach.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.51636009 and 52006212)Chinese Academy of Sciences(Grant Nos.ZDBS-LY-JSC033 and XDB22040201).
文摘Immersed boundary method is a crucial method to deal with particle suspension flow.Particle shapes involved in such flow are usually simple geometry,such as sphere and ellipsoid,which can be conveniently represented by the triangular surface grid.When the number of particles and resolution of the surface grid increase,calculating the hydrodynamic force on the particle surface through integration can be time-consuming.Hence,the present paper establishes a fast mapping method to evaluate immersed boundary hydrodynamic force.Firstly,the particle surface grid is generated by an initial triangular element grid.Subsequently,the initial surface grid is refined by bisection refinement to the desired resolution.The final step is to find the triangular element index on the particle triangular surface grid,which contains the projective point.Test cases show that the present mapping algorithm has good accuracy and efficiency for calculating hydrodynamic forces of particles.
