By use of self-consistent field Xα scattered-wave (SCF-Xα-SW) method, the electronic structure was calculated for four models of Ti4Al14X (X=Al, Fe, Ni and Cu) clusters. The Ti4Al14X cluster was developed based on L...By use of self-consistent field Xα scattered-wave (SCF-Xα-SW) method, the electronic structure was calculated for four models of Ti4Al14X (X=Al, Fe, Ni and Cu) clusters. The Ti4Al14X cluster was developed based on L12 Al3Ti-base intermetallic compound. The results are presented using the density of states (DOS) and one-electron properties, such as relative binding tendency between the atom and the model cluster, and hybrid bonding tendency between the alloying element and the host atoms. By comparing the four models of Ti4Al14X cluster, the effect of the Fe, Ni or Cu atom on the physical properties of Al3Ti-based L12 intermetallic compounds is analyzed. The results indicate that the addition of the Fe, Ni or Cu atom intensifies the relative binding tendency between Ti atom and Ti4Al14X cluster. It was found that the Fermi level (EF) lies in a maximum in the DOS for Ti4Al14Al cluster; on the contrary, the EF comes near a minimum tn the DOS for Ti4Al14X (X=Fe, Ni and Cu) cluster. Thus the L12 crystal structure for binary Al3Ti alloy is unstable, and the addition of the Fe, Ni or Cu atom to Al3Ti is benefical to stabilize L12 crystal structure. The calculation also shows that the Fe, Ni or Cu atom strengthens the hybrid bonding tendency between the central atom and the host atoms for Ti4Al14X cluster and thereby may lead to the constriction of the lattice of Al3Ti-base intermetallic compounds.展开更多
User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation re...User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation regarding to each user;2) Group adaptation focusing on group of users. To support group adaptation, the basic problem which needs to be solved is how to create user groups. This relates to clustering techniques so as to cluster user models because a group is considered as a cluster of similar user models. In this paper we discuss two clustering algorithms: k-means and k-medoids and also propose dissimilarity measures and similarity measures which are applied into different structures (forms) of user models like vector, overlay, and Bayesian network.展开更多
We employed random distributions and gradient descent methods for the Generator Coordinate Method(GCM)to identify effective basis wave functions,taking halo nuclei ^(6)He and ^(6)Li as examples.By comparing the ground...We employed random distributions and gradient descent methods for the Generator Coordinate Method(GCM)to identify effective basis wave functions,taking halo nuclei ^(6)He and ^(6)Li as examples.By comparing the ground state(0^(+))energy of ^(6)He and the excited state(0^(+))energy of 6 Li calculated with various random distributions and manually selected generation coordinates,we found that the heavy tail characteristic of the logistic distribution better describes the features of the halo nuclei.Subsequently,the Adam algorithm from machine learning was applied to optimize the basis wave functions,indicating that a limited number of basis wave functions can approximate the converged values.These results offer some empirical insights for selecting basis wave functions and contribute to the broader application of machine learning methods in predicting effective basis wave functions.展开更多
Symplectic symmetry approach to clustering(SSAC)in atomic nuclei,recently proposed,is modified and further developed in more detail.It is firstly applied to the light two-cluster^(20)Ne+αsystem of^(24)Mg,the latter e...Symplectic symmetry approach to clustering(SSAC)in atomic nuclei,recently proposed,is modified and further developed in more detail.It is firstly applied to the light two-cluster^(20)Ne+αsystem of^(24)Mg,the latter exhibiting well developed low-energy K^(π)=0_(1)^(+),k^(π)=2_(1)^(+) and π^(π)=0_(1)^(-) rotational bands in its spectrum.A simple algebraic Hamiltonian,consisting of dynamical symmetry,residual and vertical mixing parts is used to describe these three lowest rotational bands of positive and negative parity in^(24)Mg.A good description of the excitation energies is obtained by considering only the SU(3)cluster states restricted to the stretched many-particle Hilbert subspace,built on the leading Pauli allowed SU(3)multiplet for the positive-and negative-parity states,respectively.The coupling to the higher cluster-model configurations allows us to describe the known low-lying experimentally observed B(E2)transition probabilities within and between the cluster states of the three bands under consideration without the use of an effective charge.展开更多
As a cluster overlap amplitude,the reduced-width amplitude is an important physical quantity for analyzing clustering in the nucleus depending on specified channels and has been calculated and widely applied in nuclea...As a cluster overlap amplitude,the reduced-width amplitude is an important physical quantity for analyzing clustering in the nucleus depending on specified channels and has been calculated and widely applied in nuclear cluster physics.In this review,we briefly revisit the theoretical framework for calculating the reduced-width amplitude,as well as the outlines of cluster models to obtain microscopic or semi-microscopic cluster wave functions.We also introduce the recent progress related to cluster overlap amplitudes,including the implementation of cross-section estimation and extension to three-body clustering analysis.Comprehensive examples are provided to demonstrate the application of the reduced-width amplitude in analyzing clustering structures.展开更多
Modeling topics in short texts presents significant challenges due to feature sparsity, particularly when analyzing content generated by large-scale online users. This sparsity can substantially impair semantic captur...Modeling topics in short texts presents significant challenges due to feature sparsity, particularly when analyzing content generated by large-scale online users. This sparsity can substantially impair semantic capture accuracy. We propose a novel approach that incorporates pre-clustered knowledge into the BERTopic model while reducing the l2 norm for low-frequency words. Our method effectively mitigates feature sparsity during cluster mapping. Empirical evaluation on the StackOverflow dataset demonstrates that our approach outperforms baseline models, achieving superior Macro-F1 scores. These results validate the effectiveness of our proposed feature sparsity reduction technique for short-text topic modeling.展开更多
In this paper, a cluster model in particle flow code was used to simulate granite specimens after heat treatment under uniaxial compression. The results demonstrated that micro-cracks are randomly distributed in the s...In this paper, a cluster model in particle flow code was used to simulate granite specimens after heat treatment under uniaxial compression. The results demonstrated that micro-cracks are randomly distributed in the specimen when the temperature is below 300?C, and have partial coalescence when the temperature is up to 450?C, then form macro-cracks when the temperature is above 600?C. There is more inter-granular cracking than intra-granular cracking, and their ratio increases with increasing temperature.The micro-cracks are almost constant when the temperature decreases from 900?C to room temperature, except for quartz α–β phase transition temperature(573?C). The fracture evolution process is obviously affected by these cracks, especially at 600–900?C. Elevated temperature leads to easily developed displacement between the grains, and the capacity to store strain energy becomes weaker, corresponding to the plasticity of granite after heat treatment.展开更多
The chemisorption properties of N^18O adsorption on TiO2(110) surface were investigated by experimental and theoretical methods. The results of temperature programmed desorption (TPD) indicated that the temperatures o...The chemisorption properties of N^18O adsorption on TiO2(110) surface were investigated by experimental and theoretical methods. The results of temperature programmed desorption (TPD) indicated that the temperatures of the three desorption peaks of the main N2 molecules were at (low) temperature of 230 K, 450 K, and (high) temperature of 980 K. This meant that N^18O decomposed and recombined during the process of N2 desorption after N^18O was exposed. Analysis of thestable combination and orbital theory calculation of the surface reaction of NO adsorption on the TiO2(110) cluster modelshowed that there was clear preference for the Ti-NO orientation.展开更多
As a widely used measurement technique in rock mechanics,spatial correlation modeling of acoustic emission(AE)scattering signals is attracting increasing focus for describing mechanical behavior quantitatively.Unlike ...As a widely used measurement technique in rock mechanics,spatial correlation modeling of acoustic emission(AE)scattering signals is attracting increasing focus for describing mechanical behavior quantitatively.Unlike the statistical description of the spatial distribution of randomly generated AE signals,spatial correlation modeling is based mainly on short-range correlation considering the interrelationship of adjacent signals.As a new idea from percolation models,the covering strategy is used to build the most representative cube cluster,which corresponds to the critical scale at peak stress.Its modeling process of critical cube cluster depends strongly on the full connection of the main fracture network,and the corresponding cube for coverage is termed the critical cube.The criticality pertains to not only the transition of local-to-whole connection of the fracture network but also the increasing-to-decreasing transition of the deviatoric stress with an obvious stress drop in the brittle failure of granite.Determining a reasonable critical cube guarantees the best observation scale for investigating the failure process.Besides,the topological connection induces the geometric criticality of three descriptors,namely anisotropy,pore fraction,and specific surface area,which are evaluated separately and effectively.The results show that cluster modeling based on the critical cube is effective and has criticality in both topology and geometry,as well as the triaxial behavior.Furthermore,the critical cube length presents a high confidence probability of being correlated to the mineral particle size.Besides,its pore fraction of cube cluster is influenced strongly by the critical cube length and confining pressure.展开更多
One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must ...One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.展开更多
Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow confi...Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.展开更多
The accumulation of He on a W surface during keV-He ion irradiation has been simulated using cluster dynamics modeling. This is based mainly on rate theory and improved by involving different types of objects, adoptin...The accumulation of He on a W surface during keV-He ion irradiation has been simulated using cluster dynamics modeling. This is based mainly on rate theory and improved by involving different types of objects, adopting up-to-date parameters and complex reaction processes, as well as considering the diffusion process along with depth. These new features make the simulated results compare very well with the experimental ones. The accumulation and diffusion processes are analyzed, and the depth and size dependence of the He concentrations contributed by different types of He clusters is also discussed. The exploration of the trapping and diffusion effects of the He atoms is helpful in understanding the evolution of the damages in the near-surface of plasma-facing materials under He ion irradiation.展开更多
Rod insulators are vital parts of the catenary of high speed railways(HSRs).There are many different catenary insulators,and the background of the insulator image is complicated.It is difficult to recognise insulators...Rod insulators are vital parts of the catenary of high speed railways(HSRs).There are many different catenary insulators,and the background of the insulator image is complicated.It is difficult to recognise insulators and detect defects automatically.In this paper,we propose a catenary intelligent defect detection algorithm based on Mask region-convolutional neural network(R-CNN)and an image processing model.Vertical projection technology is used to achieve single shed positioning and precise cutting of the insulator.Gradient,texture,and gray feature fusion(GTGFF)and a K-means clustering analysis model(KCAM)are proposed to detect broken insulators,dirt,foreign bodies,and flashover.Using this model,insulator recognition and defect detection can achieve a high recall rate and accuracy,and generalized defect detection.The algorithm is tested and verified on a dataset of realistic insulator images,and the accuracy and reliability of the algorithm satisfy current requirements for HSR catenary automatic inspection and intelligent maintenance.展开更多
This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the ...This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.展开更多
The cavitation cloud of different internal structures results in different collapse pressures owing to the interaction among bubbles. The internal structure of cloud cavitation is required to accurately predict collap...The cavitation cloud of different internal structures results in different collapse pressures owing to the interaction among bubbles. The internal structure of cloud cavitation is required to accurately predict collapse pressure. A cavitation model was developed through dimensional analysis and direct numerical simulation of collapse of bubble cluster. Bubble number density was included in proposed model to characterize the internal structure of bubble cloud. Implemented on flows over a projectile, the proposed model predicts a higher collapse pressure compared with Singhal model. Results indicate that the collapse pressure of detached cavitation cloud is affected by bubble number density.展开更多
The geometry and electronic topology properties of Mg/Al hydrotalcite cluster models were comparatively investigated by means of density functional theory at GGA/DND levels.The results suggested that cluster model con...The geometry and electronic topology properties of Mg/Al hydrotalcite cluster models were comparatively investigated by means of density functional theory at GGA/DND levels.The results suggested that cluster model containing seven octahedral cations was the smallest size to be employed to simulate other properties.The fact that the n＋ charge of cluster models containing n aluminum atoms can reflect electronic properties of anionic clay layer sheet.The bond lengths of clusters can be modified by terminating with or without OH-/H2O groups in terms of principle of bond order conservation.展开更多
文摘By use of self-consistent field Xα scattered-wave (SCF-Xα-SW) method, the electronic structure was calculated for four models of Ti4Al14X (X=Al, Fe, Ni and Cu) clusters. The Ti4Al14X cluster was developed based on L12 Al3Ti-base intermetallic compound. The results are presented using the density of states (DOS) and one-electron properties, such as relative binding tendency between the atom and the model cluster, and hybrid bonding tendency between the alloying element and the host atoms. By comparing the four models of Ti4Al14X cluster, the effect of the Fe, Ni or Cu atom on the physical properties of Al3Ti-based L12 intermetallic compounds is analyzed. The results indicate that the addition of the Fe, Ni or Cu atom intensifies the relative binding tendency between Ti atom and Ti4Al14X cluster. It was found that the Fermi level (EF) lies in a maximum in the DOS for Ti4Al14Al cluster; on the contrary, the EF comes near a minimum tn the DOS for Ti4Al14X (X=Fe, Ni and Cu) cluster. Thus the L12 crystal structure for binary Al3Ti alloy is unstable, and the addition of the Fe, Ni or Cu atom to Al3Ti is benefical to stabilize L12 crystal structure. The calculation also shows that the Fe, Ni or Cu atom strengthens the hybrid bonding tendency between the central atom and the host atoms for Ti4Al14X cluster and thereby may lead to the constriction of the lattice of Al3Ti-base intermetallic compounds.
文摘User model which is the representation of information about user is the heart of adaptive systems. It helps adaptive systems to perform adaptation tasks. There are two kinds of adaptations: 1) Individual adaptation regarding to each user;2) Group adaptation focusing on group of users. To support group adaptation, the basic problem which needs to be solved is how to create user groups. This relates to clustering techniques so as to cluster user models because a group is considered as a cluster of similar user models. In this paper we discuss two clustering algorithms: k-means and k-medoids and also propose dissimilarity measures and similarity measures which are applied into different structures (forms) of user models like vector, overlay, and Bayesian network.
基金supported by the National Key R&D Program of China(No.2023YFA1606701)the National Natural Science Foundation of China(Nos.12175042,11890710,11890714,12047514,12147101,and 12347106)+1 种基金Guangdong Major Project of Basic and Applied Basic Research(No.2020B0301030008)China National Key R&D Program(No.2022YFA1602402).
文摘We employed random distributions and gradient descent methods for the Generator Coordinate Method(GCM)to identify effective basis wave functions,taking halo nuclei ^(6)He and ^(6)Li as examples.By comparing the ground state(0^(+))energy of ^(6)He and the excited state(0^(+))energy of 6 Li calculated with various random distributions and manually selected generation coordinates,we found that the heavy tail characteristic of the logistic distribution better describes the features of the halo nuclei.Subsequently,the Adam algorithm from machine learning was applied to optimize the basis wave functions,indicating that a limited number of basis wave functions can approximate the converged values.These results offer some empirical insights for selecting basis wave functions and contribute to the broader application of machine learning methods in predicting effective basis wave functions.
文摘Symplectic symmetry approach to clustering(SSAC)in atomic nuclei,recently proposed,is modified and further developed in more detail.It is firstly applied to the light two-cluster^(20)Ne+αsystem of^(24)Mg,the latter exhibiting well developed low-energy K^(π)=0_(1)^(+),k^(π)=2_(1)^(+) and π^(π)=0_(1)^(-) rotational bands in its spectrum.A simple algebraic Hamiltonian,consisting of dynamical symmetry,residual and vertical mixing parts is used to describe these three lowest rotational bands of positive and negative parity in^(24)Mg.A good description of the excitation energies is obtained by considering only the SU(3)cluster states restricted to the stretched many-particle Hilbert subspace,built on the leading Pauli allowed SU(3)multiplet for the positive-and negative-parity states,respectively.The coupling to the higher cluster-model configurations allows us to describe the known low-lying experimentally observed B(E2)transition probabilities within and between the cluster states of the three bands under consideration without the use of an effective charge.
基金supported by the National Key R&D Program of China(No.2023YFA1606701)the National Natural Science Foundation of China(Nos.12175042 and 12147101)。
文摘As a cluster overlap amplitude,the reduced-width amplitude is an important physical quantity for analyzing clustering in the nucleus depending on specified channels and has been calculated and widely applied in nuclear cluster physics.In this review,we briefly revisit the theoretical framework for calculating the reduced-width amplitude,as well as the outlines of cluster models to obtain microscopic or semi-microscopic cluster wave functions.We also introduce the recent progress related to cluster overlap amplitudes,including the implementation of cross-section estimation and extension to three-body clustering analysis.Comprehensive examples are provided to demonstrate the application of the reduced-width amplitude in analyzing clustering structures.
文摘Modeling topics in short texts presents significant challenges due to feature sparsity, particularly when analyzing content generated by large-scale online users. This sparsity can substantially impair semantic capture accuracy. We propose a novel approach that incorporates pre-clustered knowledge into the BERTopic model while reducing the l2 norm for low-frequency words. Our method effectively mitigates feature sparsity during cluster mapping. Empirical evaluation on the StackOverflow dataset demonstrates that our approach outperforms baseline models, achieving superior Macro-F1 scores. These results validate the effectiveness of our proposed feature sparsity reduction technique for short-text topic modeling.
基金supported by the National Natural Science Foundation of Jiangsu Province of China for Distinguished Young Scholars (Grant BK20150005)the Fundamental Research Funds for the Central Universities (China University of Mining and Technology) (Grant 2014XT03)
文摘In this paper, a cluster model in particle flow code was used to simulate granite specimens after heat treatment under uniaxial compression. The results demonstrated that micro-cracks are randomly distributed in the specimen when the temperature is below 300?C, and have partial coalescence when the temperature is up to 450?C, then form macro-cracks when the temperature is above 600?C. There is more inter-granular cracking than intra-granular cracking, and their ratio increases with increasing temperature.The micro-cracks are almost constant when the temperature decreases from 900?C to room temperature, except for quartz α–β phase transition temperature(573?C). The fracture evolution process is obviously affected by these cracks, especially at 600–900?C. Elevated temperature leads to easily developed displacement between the grains, and the capacity to store strain energy becomes weaker, corresponding to the plasticity of granite after heat treatment.
文摘The chemisorption properties of N^18O adsorption on TiO2(110) surface were investigated by experimental and theoretical methods. The results of temperature programmed desorption (TPD) indicated that the temperatures of the three desorption peaks of the main N2 molecules were at (low) temperature of 230 K, 450 K, and (high) temperature of 980 K. This meant that N^18O decomposed and recombined during the process of N2 desorption after N^18O was exposed. Analysis of thestable combination and orbital theory calculation of the surface reaction of NO adsorption on the TiO2(110) cluster modelshowed that there was clear preference for the Ti-NO orientation.
基金the National Natural Science Foundation of China(No.51504257)the State Key Research Development Program of China(No.2016YFC0600704)+1 种基金the Fund of Yueqi Outstanding Scholars(No.2018B051616)the Open Fund of the State Key Laboratory of Coal Mine Disaster Dynamics and Control(No.2011DA105287-FW201604).
文摘As a widely used measurement technique in rock mechanics,spatial correlation modeling of acoustic emission(AE)scattering signals is attracting increasing focus for describing mechanical behavior quantitatively.Unlike the statistical description of the spatial distribution of randomly generated AE signals,spatial correlation modeling is based mainly on short-range correlation considering the interrelationship of adjacent signals.As a new idea from percolation models,the covering strategy is used to build the most representative cube cluster,which corresponds to the critical scale at peak stress.Its modeling process of critical cube cluster depends strongly on the full connection of the main fracture network,and the corresponding cube for coverage is termed the critical cube.The criticality pertains to not only the transition of local-to-whole connection of the fracture network but also the increasing-to-decreasing transition of the deviatoric stress with an obvious stress drop in the brittle failure of granite.Determining a reasonable critical cube guarantees the best observation scale for investigating the failure process.Besides,the topological connection induces the geometric criticality of three descriptors,namely anisotropy,pore fraction,and specific surface area,which are evaluated separately and effectively.The results show that cluster modeling based on the critical cube is effective and has criticality in both topology and geometry,as well as the triaxial behavior.Furthermore,the critical cube length presents a high confidence probability of being correlated to the mineral particle size.Besides,its pore fraction of cube cluster is influenced strongly by the critical cube length and confining pressure.
文摘One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.
基金Supported by National Natural Science Foundation of China(Grant No.11372036)
文摘Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.
基金supported by the Special Funds for Major State Basic Research Project of China(973)(Nos.2007CB925004 and 2008CB717802)the Knowledge Innovation Program of the Chinese Academy of Sciences(No.KJCX2-YW-N35)+2 种基金National Natural Science Foundation of China(No.11005124)the China Postdoctoral Science Foundation Funded Project(No.20100470863)Director Grants of CASHIPS.Part of the calculations were performed in the Center for Computational Science of CASHIPS
文摘The accumulation of He on a W surface during keV-He ion irradiation has been simulated using cluster dynamics modeling. This is based mainly on rate theory and improved by involving different types of objects, adopting up-to-date parameters and complex reaction processes, as well as considering the diffusion process along with depth. These new features make the simulated results compare very well with the experimental ones. The accumulation and diffusion processes are analyzed, and the depth and size dependence of the He concentrations contributed by different types of He clusters is also discussed. The exploration of the trapping and diffusion effects of the He atoms is helpful in understanding the evolution of the damages in the near-surface of plasma-facing materials under He ion irradiation.
基金supported by the National Natural Science Foundation of China(Nos.51677171,51637009,51577166 and 51827810)the National Key R&D Program of China(No.2018YFB0606000)+2 种基金the China Scholarship Council(No.201708330502)the Fund of Shuohuang Railway Development Limited Liability Company(No.SHTL-2020-13)the Fund of State Key Laboratory of Industrial Control Technology(No.ICT2022B29),China。
文摘Rod insulators are vital parts of the catenary of high speed railways(HSRs).There are many different catenary insulators,and the background of the insulator image is complicated.It is difficult to recognise insulators and detect defects automatically.In this paper,we propose a catenary intelligent defect detection algorithm based on Mask region-convolutional neural network(R-CNN)and an image processing model.Vertical projection technology is used to achieve single shed positioning and precise cutting of the insulator.Gradient,texture,and gray feature fusion(GTGFF)and a K-means clustering analysis model(KCAM)are proposed to detect broken insulators,dirt,foreign bodies,and flashover.Using this model,insulator recognition and defect detection can achieve a high recall rate and accuracy,and generalized defect detection.The algorithm is tested and verified on a dataset of realistic insulator images,and the accuracy and reliability of the algorithm satisfy current requirements for HSR catenary automatic inspection and intelligent maintenance.
文摘This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.
基金support from the National Natural Science Foundation of China (11402276)
文摘The cavitation cloud of different internal structures results in different collapse pressures owing to the interaction among bubbles. The internal structure of cloud cavitation is required to accurately predict collapse pressure. A cavitation model was developed through dimensional analysis and direct numerical simulation of collapse of bubble cluster. Bubble number density was included in proposed model to characterize the internal structure of bubble cloud. Implemented on flows over a projectile, the proposed model predicts a higher collapse pressure compared with Singhal model. Results indicate that the collapse pressure of detached cavitation cloud is affected by bubble number density.
基金supported by China University of Petroleum (East China) (grant 09CX04045A)
文摘The geometry and electronic topology properties of Mg/Al hydrotalcite cluster models were comparatively investigated by means of density functional theory at GGA/DND levels.The results suggested that cluster model containing seven octahedral cations was the smallest size to be employed to simulate other properties.The fact that the n＋ charge of cluster models containing n aluminum atoms can reflect electronic properties of anionic clay layer sheet.The bond lengths of clusters can be modified by terminating with or without OH-/H2O groups in terms of principle of bond order conservation.
