Without knowing the emittance value, it is difficult to optimize ion beam optics for minimum beam loss during transmission, especially considering the very high emittance values of electron cyclotron resonance(ECR) io...Without knowing the emittance value, it is difficult to optimize ion beam optics for minimum beam loss during transmission, especially considering the very high emittance values of electron cyclotron resonance(ECR) ion sources.With this in mind, to measure the emittance of the ion beams produced by the mVINIS ECR, which is part of the FAMA facility at the Vin?a Institute of Nuclear Sciences, we have developed a pepper-pot scintillator screen system combined with a CMOS camera. The application, developed on the Lab VIEW platform, allows us to control the camera's main attribute settings, such as the shutter speed and the gain, record the images in the region of interest, and process and filter the images in real time. To analyze the data from the obtained image, we have developed an algorithm called measurement and analysis of ion beam luminosity(MAIBL) to reconstruct the four-dimensional(4D) beam profile and calculate the root mean square(RMS) emittance. Before measuring emittance, we performed a simulated experiment using the pepper-pot simulation(PPS) program. An exported file(PPS) gives a numerically generated raw image(mock image) of a beam with a predefined emittance value after it has passed through a pepper-pot mask. By analyzing data from mock images instead of the image obtained by the camera and putting it into the MAIBL algorithm, we can compare the calculated emittance with PPS's initial emittance value. In this paper, we present our computational tools and explain the method for verifying the correctness of the calculated emittance values.展开更多
Seismic attributes encapsulate substantial reservoir characterization information and can effectively support reservoir prediction.Given the high-dimensional nonlinear between sandbodies and seismic attributes,this st...Seismic attributes encapsulate substantial reservoir characterization information and can effectively support reservoir prediction.Given the high-dimensional nonlinear between sandbodies and seismic attributes,this study employs the RFECV method for seismic attribute selection,inputting the optimized attributes into a LightGBM model to enhance spatial delineation of sandbody identification.By constructing training datasets based on optimized seismic attributes and well logs,followed by class imbalance correction as input variables for machine learning models,with sandbody probability as the output variable,and employing grid search to optimize model parameters,a high-precision sandbody prediction model was established.Taking the 3D seismic data of Block F3 in the North Sea of Holland as an example,this method successfully depicted the three-dimensional spatial distribution of target formation sandstones.The results indicate that even under strong noise conditions,the multi-attribute sandbody identification method based on LightGBM effectively characterizes the distribution features of sandbodies.Compared to unselected attributes,the prediction results using selected attributes have higher vertical resolution and inter-well conformity,with the prediction accuracy for single wells reaching 80.77%,significantly improving the accuracy of sandbody boundary delineation.展开更多
To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical c...To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.展开更多
Algorithms are the primary component of Artificial Intelligence(AI).The algorithm is the process in AI that imitates the human mind to solve problems.Currently evaluating the performance of AI is achieved by evaluatin...Algorithms are the primary component of Artificial Intelligence(AI).The algorithm is the process in AI that imitates the human mind to solve problems.Currently evaluating the performance of AI is achieved by evaluating AI algorithms by metric scores on data sets.However the evaluation of algorithms in AI is challenging because the evaluation of the same type of algorithm has many data sets and evaluation metrics.Different algorithms may have individual strengths and weaknesses in evaluation metric scores on separate data sets,lacking the credibility and validity of the evaluation.Moreover,evaluation of algorithms requires repeated experiments on different data sets,reducing the attention of researchers to the research of the algorithms itself.Crucially,this approach to evaluating comparative metric scores does not take into account the algorithm’s ability to solve problems.And the classical algorithm evaluation of time and space complexity is not suitable for evaluating AI algorithms.Because classical algorithms input is infinite numbers,whereas AI algorithms input is a data set,which is limited and multifarious.According to the AI algorithm evaluation without response to the problem solving capability,this paper summarizes the features of AI algorithm evaluation and proposes an AI evaluation method that incorporates the problem-solving capabilities of algorithms.展开更多
Non-technical losses(NTL)of electric power are a serious problem for electric distribution companies.The solution determines the cost,stability,reliability,and quality of the supplied electricity.The widespread use of...Non-technical losses(NTL)of electric power are a serious problem for electric distribution companies.The solution determines the cost,stability,reliability,and quality of the supplied electricity.The widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity consumption.During the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption readings.This model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural networks.The best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test sample.Such a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL sources.The use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock mater...The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials.展开更多
To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise mode...To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses.展开更多
Convex feasibility problems are widely used in image reconstruction,sparse signal recovery,and other areas.This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery...Convex feasibility problems are widely used in image reconstruction,sparse signal recovery,and other areas.This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery.We rst derive the projection formulas for a vector onto the feasible sets.The centralized circumcentered-reection method is designed to solve the convex feasibility problem.Some numerical experiments demonstrate the feasibility and e ectiveness of the proposed algorithm,showing superior performance compared to conventional alternating projection methods.展开更多
Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The t...Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.展开更多
Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The pro...Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The proposed method uses both the gray value of a pixel and the local average gray value of an image. At the same time, the simple genetic algorithm is improved by using better reproduction and crossover operators. Thus the proposed method makes up the 2 D entropy method’s drawback of being time consuming, and yields satisfactory segmentation results. Experimental results show that the proposed method can save computational time when it provides good quality segmentation.展开更多
A new orbit transfer method is presented by combining the genetic algorithm（GA）with the refined Q-law method.Considering the energy consumption,the relative thrust efficiency is introduced as a threshold deciding wh...A new orbit transfer method is presented by combining the genetic algorithm（GA）with the refined Q-law method.Considering the energy consumption,the relative thrust efficiency is introduced as a threshold deciding whether to thrust or coast.GA is used to achieve the global time-optimal orbit transfer.The trajectory optimization problem is transformed into the constraint parameter optimization problem,thus the nonlinear two-point boundary value problem is avoided.The refined Q-law method integrated with the fuzzy logic control is adopted for the end course,the vibration is avoided and the high precision is achieved.The numerical simulation of satellite orbit transfer is implemented.Results show that the new method can achieve the time-optimal orbit transfer and the low energy consumption,thus improving the transfer precision.展开更多
A new algorithm based on the projection method with the implicit finite difference technique was established to calculate the velocity fields and pressure.The calculation region can be divided into different regions a...A new algorithm based on the projection method with the implicit finite difference technique was established to calculate the velocity fields and pressure.The calculation region can be divided into different regions according to Reynolds number.In the far-wall region,the thermal melt flow was calculated as Newtonian flow.In the near-wall region,the thermal melt flow was calculated as non-Newtonian flow.It was proved that the new algorithm based on the projection method with the implicit technique was correct through nonparametric statistics method and experiment.The simulation results show that the new algorithm based on the projection method with the implicit technique calculates more quickly than the solution algorithm-volume of fluid method using the explicit difference method.展开更多
To study the domain decomposition algorithms for the equations of elliptic type, the method of optimal boundary control was used to advance a new procedure for domain decomposition algorithms and regularization method...To study the domain decomposition algorithms for the equations of elliptic type, the method of optimal boundary control was used to advance a new procedure for domain decomposition algorithms and regularization method to deal with the ill posedness of the control problem. The determination of the value of the solution of the partial differential equation on the interface——the key of the domain decomposition algorithms——was transformed into a boundary control problem and the ill posedness of the control problem was overcome by regularization. The convergence of the regularizing control solution was proven and the equations which characterize the optimal control were given therefore the value of the unknown solution on the interface of the domain would be obtained by solving a series of coupling equations. Using the boundary control method the domain decomposion algorithm can be carried out.展开更多
Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure...Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.展开更多
The digital speckle correlation method is an important optical metrology for sur- face displacement and strain measurement.With this technique,the whole field deformation in- formation can be obtained by tracking the ...The digital speckle correlation method is an important optical metrology for sur- face displacement and strain measurement.With this technique,the whole field deformation in- formation can be obtained by tracking the geometric points on the speckle images based on a correlation-matching search technique.However,general search techniques suffer from great com- putational complexity in the processing of speckle images with large deformation and the large random errors in the processing of images of bad quality.In this paper,an advanced approach based on genetic algorithms (GA) for correlation-matching search is developed.Benefiting from the abilities of global optimum and parallelism searching of GA,this new approach can complete the correlation-matching search with less computational consumption and at high accuracy.Two experimental results from the simulated speckle images have proved the efficiency of the new approach.展开更多
In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is a...In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is affected by more than one mining panel, traditional PIM parameter inversion model is difficult to ensure the reliability of the results due to the complexity of rock movement. With crossover,mutation and selection operators, GA can perform a global optimization search and has high computation efficiency. Compared with the pattern search algorithm, the fitness function can avoid falling into local minima traps. GA reduces the risk of local minima traps which improves the accuracy and reliability with the mutation mechanism. Application at Xuehu colliery shows that GA can be used to inverse the PIM parameters for multi-panel surface movement observation, and reliable results can be obtained. The research provides a new way for back-analysis of PIM parameters for mining subsidence under complex conditions.展开更多
The dispersed phase in multiphase flows can be modeled by the population balance model(PBM). A typical population balance equation(PBE) contains terms for spatial transport, loss/growth and breakage/coalescence source...The dispersed phase in multiphase flows can be modeled by the population balance model(PBM). A typical population balance equation(PBE) contains terms for spatial transport, loss/growth and breakage/coalescence source terms. The equation is therefore quite complex and difficult to solve analytically or numerically. The quadrature-based moment methods(QBMMs) are a class of methods that solve the PBE by converting the transport equation of the number density function(NDF) into moment transport equations. The unknown source terms are closed by numerical quadrature. Over the years, many QBMMs have been developed for different problems, such as the quadrature method of moments(QMOM), direct quadrature method of moments(DQMOM),extended quadrature method of moments(EQMOM), conditional quadrature method of moments(CQMOM),extended conditional quadrature method of moments(ECQMOM) and hyperbolic quadrature method of moments(Hy QMOM). In this paper, we present a comprehensive algorithm review of these QBMMs. The mathematical equations for spatially homogeneous systems with first-order point processes and second-order point processes are derived in detail. The algorithms are further extended to the inhomogeneous system for multiphase flows, in which the computational fluid dynamics(CFD) can be coupled with the PBE. The physical limitations and the challenging numerical problems of these QBMMs are discussed. Possible solutions are also summarized.展开更多
Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained fr...Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained from laboratory triaxial tests often underestimate the deformation of high rockfill dams.Therefore, constitutive model parameters obtained by back analysis were used to calculate and predict the long-term deformation of rockfill dams.Instead of using artificial neural networks (ANNs), the response surface method (RSM) was employed to replace the finite element simulation used in the optimization iteration.Only 27 training samples were required for RSM, improving computational efficiency compared with ANN, which required 300 training samples.RSM can be used to describe the relationship between the constitutive model parameters and dam settlements.The inversion results of the Shuibuya concrete face rockfill dam (CFRD) show that the calculated settlements agree with the measured data, indicating the accuracy and efficiency of RSM.展开更多
基金funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia via the FAMA project (research topic “Physics and chemistry with ion beams”)。
文摘Without knowing the emittance value, it is difficult to optimize ion beam optics for minimum beam loss during transmission, especially considering the very high emittance values of electron cyclotron resonance(ECR) ion sources.With this in mind, to measure the emittance of the ion beams produced by the mVINIS ECR, which is part of the FAMA facility at the Vin?a Institute of Nuclear Sciences, we have developed a pepper-pot scintillator screen system combined with a CMOS camera. The application, developed on the Lab VIEW platform, allows us to control the camera's main attribute settings, such as the shutter speed and the gain, record the images in the region of interest, and process and filter the images in real time. To analyze the data from the obtained image, we have developed an algorithm called measurement and analysis of ion beam luminosity(MAIBL) to reconstruct the four-dimensional(4D) beam profile and calculate the root mean square(RMS) emittance. Before measuring emittance, we performed a simulated experiment using the pepper-pot simulation(PPS) program. An exported file(PPS) gives a numerically generated raw image(mock image) of a beam with a predefined emittance value after it has passed through a pepper-pot mask. By analyzing data from mock images instead of the image obtained by the camera and putting it into the MAIBL algorithm, we can compare the calculated emittance with PPS's initial emittance value. In this paper, we present our computational tools and explain the method for verifying the correctness of the calculated emittance values.
基金co-funded by the China National Nuclear Corporation-State Key Laboratory of Nuclear Resources and Environment(East ChinaUniversity of Technology)Joint Innovation Fund Project(No.2023NRE-LH-08)the Natural Science Foundation of Jiangxi Province,China(No.20252BAC240270)+1 种基金the Funding of National Key Laboratory of Uranium Resources Exploration-Mining and Nuclear Remote Sensing(2025QZ-YZZ-08)the National Major Science and Technology Project on Deep Earth of China(No.2024ZD 1003300)。
文摘Seismic attributes encapsulate substantial reservoir characterization information and can effectively support reservoir prediction.Given the high-dimensional nonlinear between sandbodies and seismic attributes,this study employs the RFECV method for seismic attribute selection,inputting the optimized attributes into a LightGBM model to enhance spatial delineation of sandbody identification.By constructing training datasets based on optimized seismic attributes and well logs,followed by class imbalance correction as input variables for machine learning models,with sandbody probability as the output variable,and employing grid search to optimize model parameters,a high-precision sandbody prediction model was established.Taking the 3D seismic data of Block F3 in the North Sea of Holland as an example,this method successfully depicted the three-dimensional spatial distribution of target formation sandstones.The results indicate that even under strong noise conditions,the multi-attribute sandbody identification method based on LightGBM effectively characterizes the distribution features of sandbodies.Compared to unselected attributes,the prediction results using selected attributes have higher vertical resolution and inter-well conformity,with the prediction accuracy for single wells reaching 80.77%,significantly improving the accuracy of sandbody boundary delineation.
基金Supported by Shanxi Province Natural Science Research(202203021212249)Special/Youth Foundation of Taiyuan University of Technology(2022QN101)+3 种基金National Natural Science Foundation of China(12301556)Research Project Supported by Shanxi Scholarship Council of China(2021-029)International Cooperation Base and Platform Project of Shanxi Province(202104041101019)Basic Research Plan of Shanxi Province(202203021211129)。
文摘To enhance the computational efficiency of spatio-temporally discretized phase-field models,we present a high-speed solver specifically designed for the Poisson equations,a component frequently used in the numerical computation of such models.This efficient solver employs algorithms based on discrete cosine transformations(DCT)or discrete sine transformations(DST)and is not restricted by any spatio-temporal schemes.Our proposed methodology is appropriate for a variety of phase-field models and is especially efficient when combined with flow field systems.Meanwhile,this study has conducted an extensive numerical comparison and found that employing DCT and DST techniques not only yields results comparable to those obtained via the Multigrid(MG)method,a conventional approach used in the resolution of the Poisson equations,but also enhances computational efficiency by over 90%.
基金funded by the General Program of the National Natural Science Foundation of China grant number[62277022].
文摘Algorithms are the primary component of Artificial Intelligence(AI).The algorithm is the process in AI that imitates the human mind to solve problems.Currently evaluating the performance of AI is achieved by evaluating AI algorithms by metric scores on data sets.However the evaluation of algorithms in AI is challenging because the evaluation of the same type of algorithm has many data sets and evaluation metrics.Different algorithms may have individual strengths and weaknesses in evaluation metric scores on separate data sets,lacking the credibility and validity of the evaluation.Moreover,evaluation of algorithms requires repeated experiments on different data sets,reducing the attention of researchers to the research of the algorithms itself.Crucially,this approach to evaluating comparative metric scores does not take into account the algorithm’s ability to solve problems.And the classical algorithm evaluation of time and space complexity is not suitable for evaluating AI algorithms.Because classical algorithms input is infinite numbers,whereas AI algorithms input is a data set,which is limited and multifarious.According to the AI algorithm evaluation without response to the problem solving capability,this paper summarizes the features of AI algorithm evaluation and proposes an AI evaluation method that incorporates the problem-solving capabilities of algorithms.
文摘Non-technical losses(NTL)of electric power are a serious problem for electric distribution companies.The solution determines the cost,stability,reliability,and quality of the supplied electricity.The widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity consumption.During the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption readings.This model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural networks.The best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test sample.Such a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL sources.The use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.42172312 and 52211540395)support from the Institut Universitaire de France(IUF).
文摘The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials.
基金co-supported by the National Natural Science Foundation of China(Nos.52405293,52375237)China Postdoctoral Science Foundation(No.2024M754219)Shaanxi Province Postdoctoral Research Project Funding,China。
文摘To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses.
基金Supported by the Natural Science Foundation of Guangxi Province(Grant Nos.2023GXNSFAA026067,2024GXN SFAA010521)the National Natural Science Foundation of China(Nos.12361079,12201149,12261026).
文摘Convex feasibility problems are widely used in image reconstruction,sparse signal recovery,and other areas.This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery.We rst derive the projection formulas for a vector onto the feasible sets.The centralized circumcentered-reection method is designed to solve the convex feasibility problem.Some numerical experiments demonstrate the feasibility and e ectiveness of the proposed algorithm,showing superior performance compared to conventional alternating projection methods.
基金Supported by the National Natural Science Foundation of China under Grant No.51975138the High-Tech Ship Scientific Research Project from the Ministry of Industry and Information Technology under Grant No.CJ05N20the National Defense Basic Research Project under Grant No.JCKY2023604C006.
文摘Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.
文摘Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The proposed method uses both the gray value of a pixel and the local average gray value of an image. At the same time, the simple genetic algorithm is improved by using better reproduction and crossover operators. Thus the proposed method makes up the 2 D entropy method’s drawback of being time consuming, and yields satisfactory segmentation results. Experimental results show that the proposed method can save computational time when it provides good quality segmentation.
基金Supported by the Key Project of Natural Science Foundation of Jiangsu Province(BK2010072)~~
文摘A new orbit transfer method is presented by combining the genetic algorithm（GA）with the refined Q-law method.Considering the energy consumption,the relative thrust efficiency is introduced as a threshold deciding whether to thrust or coast.GA is used to achieve the global time-optimal orbit transfer.The trajectory optimization problem is transformed into the constraint parameter optimization problem,thus the nonlinear two-point boundary value problem is avoided.The refined Q-law method integrated with the fuzzy logic control is adopted for the end course,the vibration is avoided and the high precision is achieved.The numerical simulation of satellite orbit transfer is implemented.Results show that the new method can achieve the time-optimal orbit transfer and the low energy consumption,thus improving the transfer precision.
基金Project (50975263) supported by the National Natural Science Foundation of ChinaProject (2010081015) supported by International Cooperation Project of Shanxi Province, China+1 种基金 Project (2010-78) supported by the Scholarship Council in Shanxi province, ChinaProject (2010420120005) supported by Doctoral Fund of Ministry of Education of China
文摘A new algorithm based on the projection method with the implicit finite difference technique was established to calculate the velocity fields and pressure.The calculation region can be divided into different regions according to Reynolds number.In the far-wall region,the thermal melt flow was calculated as Newtonian flow.In the near-wall region,the thermal melt flow was calculated as non-Newtonian flow.It was proved that the new algorithm based on the projection method with the implicit technique was correct through nonparametric statistics method and experiment.The simulation results show that the new algorithm based on the projection method with the implicit technique calculates more quickly than the solution algorithm-volume of fluid method using the explicit difference method.
文摘To study the domain decomposition algorithms for the equations of elliptic type, the method of optimal boundary control was used to advance a new procedure for domain decomposition algorithms and regularization method to deal with the ill posedness of the control problem. The determination of the value of the solution of the partial differential equation on the interface——the key of the domain decomposition algorithms——was transformed into a boundary control problem and the ill posedness of the control problem was overcome by regularization. The convergence of the regularizing control solution was proven and the equations which characterize the optimal control were given therefore the value of the unknown solution on the interface of the domain would be obtained by solving a series of coupling equations. Using the boundary control method the domain decomposion algorithm can be carried out.
基金National Natural Science Foundation of China (10572117,10802063,50875213)Aeronautical Science Foundation of China (2007ZA53012)+1 种基金New Century Program For Excellent Talents of Ministry of Education of China (NCET-05-0868)National High-tech Research and Development Program (2007AA04Z401)
文摘Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.
基金Project supported by the National Natural Science Foundation of China(No.19772033)the Research Innovation Fund of Tsinghua University for Ph.D.Candidates(No.092410048).
文摘The digital speckle correlation method is an important optical metrology for sur- face displacement and strain measurement.With this technique,the whole field deformation in- formation can be obtained by tracking the geometric points on the speckle images based on a correlation-matching search technique.However,general search techniques suffer from great com- putational complexity in the processing of speckle images with large deformation and the large random errors in the processing of images of bad quality.In this paper,an advanced approach based on genetic algorithms (GA) for correlation-matching search is developed.Benefiting from the abilities of global optimum and parallelism searching of GA,this new approach can complete the correlation-matching search with less computational consumption and at high accuracy.Two experimental results from the simulated speckle images have proved the efficiency of the new approach.
基金provided by the National Natural Science Foundation of China(No.51404272)the Hunan Province Key Laboratory of Coal Resources Clean-Utilization and Mine Environment Protection(No.E21224)
文摘In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is affected by more than one mining panel, traditional PIM parameter inversion model is difficult to ensure the reliability of the results due to the complexity of rock movement. With crossover,mutation and selection operators, GA can perform a global optimization search and has high computation efficiency. Compared with the pattern search algorithm, the fitness function can avoid falling into local minima traps. GA reduces the risk of local minima traps which improves the accuracy and reliability with the mutation mechanism. Application at Xuehu colliery shows that GA can be used to inverse the PIM parameters for multi-panel surface movement observation, and reliable results can be obtained. The research provides a new way for back-analysis of PIM parameters for mining subsidence under complex conditions.
文摘The dispersed phase in multiphase flows can be modeled by the population balance model(PBM). A typical population balance equation(PBE) contains terms for spatial transport, loss/growth and breakage/coalescence source terms. The equation is therefore quite complex and difficult to solve analytically or numerically. The quadrature-based moment methods(QBMMs) are a class of methods that solve the PBE by converting the transport equation of the number density function(NDF) into moment transport equations. The unknown source terms are closed by numerical quadrature. Over the years, many QBMMs have been developed for different problems, such as the quadrature method of moments(QMOM), direct quadrature method of moments(DQMOM),extended quadrature method of moments(EQMOM), conditional quadrature method of moments(CQMOM),extended conditional quadrature method of moments(ECQMOM) and hyperbolic quadrature method of moments(Hy QMOM). In this paper, we present a comprehensive algorithm review of these QBMMs. The mathematical equations for spatially homogeneous systems with first-order point processes and second-order point processes are derived in detail. The algorithms are further extended to the inhomogeneous system for multiphase flows, in which the computational fluid dynamics(CFD) can be coupled with the PBE. The physical limitations and the challenging numerical problems of these QBMMs are discussed. Possible solutions are also summarized.
基金supported by the National Natural Science Foundation of China(Grant No.51579193)the Science and Technology Planning Project of Guizhou Province(Grant No.[2016]1154)
文摘Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained from laboratory triaxial tests often underestimate the deformation of high rockfill dams.Therefore, constitutive model parameters obtained by back analysis were used to calculate and predict the long-term deformation of rockfill dams.Instead of using artificial neural networks (ANNs), the response surface method (RSM) was employed to replace the finite element simulation used in the optimization iteration.Only 27 training samples were required for RSM, improving computational efficiency compared with ANN, which required 300 training samples.RSM can be used to describe the relationship between the constitutive model parameters and dam settlements.The inversion results of the Shuibuya concrete face rockfill dam (CFRD) show that the calculated settlements agree with the measured data, indicating the accuracy and efficiency of RSM.
