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
Accurate capacity estimation is vital for the management of lithium-ion batteries in Electric Vehicles(EVs).Data-driven methods using the battery charging process provide new insights for battery capacity estimation.H...Accurate capacity estimation is vital for the management of lithium-ion batteries in Electric Vehicles(EVs).Data-driven methods using the battery charging process provide new insights for battery capacity estimation.However,extracting features from the complete or specific charge curves is difficult as the battery charging is related to the behavior of the drivers,e.g.,the battery start state of charge(SOC)and end SOC are usually random.Therefore,this study proposes a framework using a model cluster for the capacity estimation of lithium-ion batteries,which uses multi-submodels adapting to different lengths of input charge voltage segments,where input features are extracted.Three datasets(NCA,NCM,and Oxford datasets)are employed to establish the model cluster,and three types of input features and four algorithms are compared.The Random Forest(RF)algorithm combined with the time vector(input feature)achieves the best estimation results on the NCA dataset,in which the Root Mean Square Errors(RMSEs)of most submodels are lower than 1%.Thus,submodels with RMSE lower than 1%are retained to form the model cluster.The NCM dataset is used for the model cluster verification,and all RMSEs are below 0.74%.Three probability distributions of the charging process are constructed based on the three datasets to fit the model cluster to the actual EV operation situation,and the maximum RMSE is 0.403%,which provides a new perspective on the battery capacity estimation for EVs.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
Regard to the real-time dynamic digital twin modelling problem of a new-type distribution network that includes distributed resources such as distributed photovoltaic,energy storage,charging pile,and electric vehicle,...Regard to the real-time dynamic digital twin modelling problem of a new-type distribution network that includes distributed resources such as distributed photovoltaic,energy storage,charging pile,and electric vehicle,a new-type distribution network digital twin topology modeling method based on Common Information Model(CIM)specifications and spectral clustering is proposed.Firstly,according to the specifications of the CIM standard,the digital twin topology models of distributed resources are extended and established.Secondly,based on the digital twin topology models of distributed resources,a digital twin aggregation modelling method for new-type distribution network is proposed based on spectral clustering.Furthermore,an online linked update strategy for the digital twin model of new-type distribution network that integrates real-time topology states is proposed.Finally,a case study is conducted on a distribution network in a certain demonstration area in China,and the results verify the practicability and effectiveness of the method proposed in this paper.This lays the foundation for the application of electrical network twin analysis,such as power flow calculation,optimal power flow,economic dispatch,and safety check,in a new-type distribution network that includes diversified distributed resources.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
The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchic...The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.展开更多
To overcome the limitation of the traditional clustering algorithms which fail to produce meaningful clusters in high-dimensional, sparseness and binary value data sets, a new method based on hypergraph model is propo...To overcome the limitation of the traditional clustering algorithms which fail to produce meaningful clusters in high-dimensional, sparseness and binary value data sets, a new method based on hypergraph model is proposed. The hypergraph model maps the relationship present in the original data in high dimensional space into a hypergraph. A hyperedge represents the similarity of attrlbute-value distribution between two points. A hypergraph partitioning algorithm is used to find a partitioning of the vertices such that the corresponding data items in each partition are highly related and the weight of the hyperedges cut by the partitioning is minimized. The quality of the clustering result can be evaluated by applying the intra-cluster singularity value. Analysis and experimental results have demonstrated that this approach is applicable and effective in wide ranging scheme.展开更多
The existence of nanographene in cluster form is discussed in organic solvents. Theories are developed based on the columnlet, bundlet and droplet models describing the size-distribution functions. Phenomena present a...The existence of nanographene in cluster form is discussed in organic solvents. Theories are developed based on the columnlet, bundlet and droplet models describing the size-distribution functions. Phenomena present a unified explanation in the columnlet model in which free energy of Cgraphene involved in cluster is combined from a volume part proportional to the number of molecules n in cluster and a constant. The columnlet model enables describing distribution function of Cgraphene clusters by size. From purely geometrical considerations the columnlet （Cgraphene）, bundlet （single-wall carbon nanotube）, CNT （carbon nanotube）, SWNT （single-wall C-nanotube）, and carbon nanobud, CNB （carbon nanobud）） and droplet （fullerene） models predict dissimilar behaviours. The interaction-energy parameters of Cgraphene are taken from C60. An CNB behaviour or further is expected. The decay of solubility with rising temperature is smaller for Cgraphene than for SWNT and CNB and, furthermore, than for C60, in agreement with lesser numbers of units in Cgraphene clusters. The discrepancy between the experimental data of the heat of solution of fullerenes, CNTs, CNBs and graphenes is ascribed to the sharp concentration dependence of the heat of solution. The diffusion coefficient drops with temperature result greater for Cgraphene than CNB and SWNT than C60 corresponding to lesser number of units in clusters. The aggregates near （C60）13, SWNT/CNB7 and （Cgraphene）3 could be representative of the droplet, bundlet and columnlet models.展开更多
The α-target semimicroscopic single folding potentials have been derived by folding a composite (repul-sive and attractive) effective α-α interaction with the α-cluster distribution density in the target nuclei. T...The α-target semimicroscopic single folding potentials have been derived by folding a composite (repul-sive and attractive) effective α-α interaction with the α-cluster distribution density in the target nuclei. The obtained potentials are considered as the real part of the nuclear optical model potentials, while the imaginary parts are phe-nomenologicaly expressed using the Woods-Saxon form. Nine sets of measured experimental data of the 4He+12C and 4 He+16O elastic rainbow scattering over the energy range 80-240 MeV are analyzed using the obtained potentials. The data are successfully reproduced using the extracted potentials. The resulted reaction cross sections are also investigated and compared with the available corresponding data.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funded by the National Natural Science Foundation of China(NSFC,Grant No.52107230,U20A20310,52176199)the Fundamental Research Funds for the Central Universities,and is supported by 21C Innovation Laboratory,Contemporary Amperex Technology Ltd by project No.21C-OP-202309.
文摘Accurate capacity estimation is vital for the management of lithium-ion batteries in Electric Vehicles(EVs).Data-driven methods using the battery charging process provide new insights for battery capacity estimation.However,extracting features from the complete or specific charge curves is difficult as the battery charging is related to the behavior of the drivers,e.g.,the battery start state of charge(SOC)and end SOC are usually random.Therefore,this study proposes a framework using a model cluster for the capacity estimation of lithium-ion batteries,which uses multi-submodels adapting to different lengths of input charge voltage segments,where input features are extracted.Three datasets(NCA,NCM,and Oxford datasets)are employed to establish the model cluster,and three types of input features and four algorithms are compared.The Random Forest(RF)algorithm combined with the time vector(input feature)achieves the best estimation results on the NCA dataset,in which the Root Mean Square Errors(RMSEs)of most submodels are lower than 1%.Thus,submodels with RMSE lower than 1%are retained to form the model cluster.The NCM dataset is used for the model cluster verification,and all RMSEs are below 0.74%.Three probability distributions of the charging process are constructed based on the three datasets to fit the model cluster to the actual EV operation situation,and the maximum RMSE is 0.403%,which provides a new perspective on the battery capacity estimation for EVs.
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.
基金Supported by Science and Technology Project of State Grid Corporation of China(5108-202218280A-2-396-XG).
文摘Regard to the real-time dynamic digital twin modelling problem of a new-type distribution network that includes distributed resources such as distributed photovoltaic,energy storage,charging pile,and electric vehicle,a new-type distribution network digital twin topology modeling method based on Common Information Model(CIM)specifications and spectral clustering is proposed.Firstly,according to the specifications of the CIM standard,the digital twin topology models of distributed resources are extended and established.Secondly,based on the digital twin topology models of distributed resources,a digital twin aggregation modelling method for new-type distribution network is proposed based on spectral clustering.Furthermore,an online linked update strategy for the digital twin model of new-type distribution network that integrates real-time topology states is proposed.Finally,a case study is conducted on a distribution network in a certain demonstration area in China,and the results verify the practicability and effectiveness of the method proposed in this paper.This lays the foundation for the application of electrical network twin analysis,such as power flow calculation,optimal power flow,economic dispatch,and safety check,in a new-type distribution network that includes diversified distributed resources.
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.
文摘The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.
文摘To overcome the limitation of the traditional clustering algorithms which fail to produce meaningful clusters in high-dimensional, sparseness and binary value data sets, a new method based on hypergraph model is proposed. The hypergraph model maps the relationship present in the original data in high dimensional space into a hypergraph. A hyperedge represents the similarity of attrlbute-value distribution between two points. A hypergraph partitioning algorithm is used to find a partitioning of the vertices such that the corresponding data items in each partition are highly related and the weight of the hyperedges cut by the partitioning is minimized. The quality of the clustering result can be evaluated by applying the intra-cluster singularity value. Analysis and experimental results have demonstrated that this approach is applicable and effective in wide ranging scheme.
文摘The existence of nanographene in cluster form is discussed in organic solvents. Theories are developed based on the columnlet, bundlet and droplet models describing the size-distribution functions. Phenomena present a unified explanation in the columnlet model in which free energy of Cgraphene involved in cluster is combined from a volume part proportional to the number of molecules n in cluster and a constant. The columnlet model enables describing distribution function of Cgraphene clusters by size. From purely geometrical considerations the columnlet （Cgraphene）, bundlet （single-wall carbon nanotube）, CNT （carbon nanotube）, SWNT （single-wall C-nanotube）, and carbon nanobud, CNB （carbon nanobud）） and droplet （fullerene） models predict dissimilar behaviours. The interaction-energy parameters of Cgraphene are taken from C60. An CNB behaviour or further is expected. The decay of solubility with rising temperature is smaller for Cgraphene than for SWNT and CNB and, furthermore, than for C60, in agreement with lesser numbers of units in Cgraphene clusters. The discrepancy between the experimental data of the heat of solution of fullerenes, CNTs, CNBs and graphenes is ascribed to the sharp concentration dependence of the heat of solution. The diffusion coefficient drops with temperature result greater for Cgraphene than CNB and SWNT than C60 corresponding to lesser number of units in clusters. The aggregates near （C60）13, SWNT/CNB7 and （Cgraphene）3 could be representative of the droplet, bundlet and columnlet models.
文摘The α-target semimicroscopic single folding potentials have been derived by folding a composite (repul-sive and attractive) effective α-α interaction with the α-cluster distribution density in the target nuclei. The obtained potentials are considered as the real part of the nuclear optical model potentials, while the imaginary parts are phe-nomenologicaly expressed using the Woods-Saxon form. Nine sets of measured experimental data of the 4He+12C and 4 He+16O elastic rainbow scattering over the energy range 80-240 MeV are analyzed using the obtained potentials. The data are successfully reproduced using the extracted potentials. The resulted reaction cross sections are also investigated and compared with the available corresponding data.
