In response to the demand for rapid geometric modeling in Monte Carlo radiation transportation calculations for large-scale and complex geometric scenes,functional improvements,and algorithm optimizations were perform...In response to the demand for rapid geometric modeling in Monte Carlo radiation transportation calculations for large-scale and complex geometric scenes,functional improvements,and algorithm optimizations were performed using CAD-to-Monte Carlo geometry conversion(CMGC)code.Boundary representation(BRep)to constructive solid geometry(CSG)conversion and visual CSG modeling were combined to address the problem of non-convertible geometries such as spline surfaces.The splitting surface assessment method in BRep-to-CSG conversion was optimized to reduce the number of Boolean operations using an Open Cascade.This,in turn,reduced the probability of CMGC conversion failure.The auxiliary surface generation algorithm was optimized to prevent the generation of redundant auxiliary surfaces that cause an excessive decomposition of CAD geometry solids.These optimizations enhanced the usability and stability of the CMGC model conversion.CMGC was applied successfully to the JMCT transportation calculations for the conceptual designs of five China Fusion Engineering Test Reactor(CFETR)blankets.The rapid replacement of different blanket schemes was achieved based on the baseline CFETR model.The geometric solid number of blankets ranged from hundreds to tens of thousands.The correctness of the converted CFETR models using CMGC was verified through comparisons with the MCNP calculation results.The CMGC supported radiation field evaluations for a large urban scene and detailed ship scene.This enabled the rapid conversion of CAD models with thousands of geometric solids into Monte Carlo CSG models.An analysis of the JMCT transportation simulation results further demonstrated the accuracy and effectiveness of the CMGC.展开更多
This paper investigates the influence of the spanwise-distributed trailing-edge camber morphing on the dynamic stall characteristics of a finite-span wing at Re=2×10^(5).The mathematical model of the spanwise-dis...This paper investigates the influence of the spanwise-distributed trailing-edge camber morphing on the dynamic stall characteristics of a finite-span wing at Re=2×10^(5).The mathematical model of the spanwise-distributed trailing-edge camber morphing is established based on Chebyshev polynomials,and the deformed wing surface is modeled by a spline surface according to the rib's morphing in the chordwise direction.The Computational Fluid Dynamics(CFD)method is adopted to obtain flow-field results and aerodynamic forces.The SST-γmodel is introduced and the overset mesh technique is adopted.The numerical results show that the spanwisedistributed trailing-edge morphing obviously changes the aerodynamic and energy transfer characteristics of the dynamic stall.Especially when the phase difference between the trailing-edge motion and the wing pitch is-π/2,the interaction between the three-dimensional(3-D)Leading-Edge Vortex(LEV)and Trailing-Edge Vortex(TEV)is strengthened,and the work done by the aerodynamic force turns negative.This indicates that the trailing-edge deformation has the potential to suppress the oscillation amplitude of stall flutter.We also found that as the trailing-edge camber morphing varies more complexly along the spanwise direction,the suppression effect decreases accordingly.展开更多
The challenge of enhancing the generalization capacity of reinforcement learning(RL)agents remains a formidable obstacle.Existing RL methods,despite achieving superhuman performance on certain benchmarks,often struggl...The challenge of enhancing the generalization capacity of reinforcement learning(RL)agents remains a formidable obstacle.Existing RL methods,despite achieving superhuman performance on certain benchmarks,often struggle with this aspect.A potential reason is that the benchmarks used for training and evaluation may not adequately offer a diverse set of transferable tasks.Although recent studies have developed bench-marking environments to address this shortcoming,they typically fall short in providing tasks that both ensure a solid foundation for generalization and exhibit significant variability.To overcome these limitations,this work introduces the concept that‘objects are composed of more fundamental components’in environment design,as implemented in the proposed environment called summon the magic(StM).This environment generates tasks where objects are derived from extensible and shareable basic components,facilitating strategy reuse and enhancing generalization.Furthermore,two new metrics,adaptation sensitivity range(ASR)and parameter correlation coefficient(PCC),are proposed to better capture and evaluate the generalization process of RL agents.Experimental results show that increasing the number of basic components of the object reduces the proximal policy optimization(PPO)agent’s training-testing gap by 60.9%(in episode reward),significantly alleviating overfitting.Additionally,linear variations in other environmental factors,such as the training monster set proportion and the total number of basic components,uniformly decrease the gap by at least 32.1%.These results highlight StM’s effectiveness in benchmarking and probing the generalization capabilities of RL algorithms.展开更多
Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning mode...Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.展开更多
Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of rocks.The macrofailure behaviors of rocks are primarily formed after experiencing the initiation,propagation,and coalescenc...Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of rocks.The macrofailure behaviors of rocks are primarily formed after experiencing the initiation,propagation,and coalescenceof micro-cracks.In this paper,the grain-based discretized virtual internal bond model is employed to investigatethe fracturing process of unloaded rock under high in-situ stresses from the micro-fracture perspective.Thesimulated micro-fracturing process reveals that the longitudinal stress waves induced by unloading lead to thevisible unloading effect.The influences of in-situ stresses,mineral grain sizes,and grain heterogeneity on rockmacro and micro fracture are investigated.Micro-crack areas of tensile and shear cracks and micro-crack anglesare statistically analyzed to reveal the rock micro-fracture characteristics.The simulated results indicate thatthe combined effect of the stress state transition and the unloading effect dominates the rock unloading failure.The vertical and horizontal in-situ stresses determine the stress state of surrounding rock after unloading andthe unloading effect,respectively.As the vertical stress increases,the stress level after unloading is higher,andthe shear failure characteristics become more obvious.As the horizontal stress increases,the unloading effectincreases,leading to the intensification of tensile failure.The mineral grain size and grain heterogeneity alsohave nonnegligible influences on rock unloading failure.The micro-fracture perspective provides further insightinto the unloading failure mechanism of deep rock excavation.展开更多
The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The bas...The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.展开更多
Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentime...Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.展开更多
The amount of water withdrawn by wells is one of the quantitative variables that can be applied to estimate groundwater resources and further evaluate the human influence on groundwater systems. The accuracy for the c...The amount of water withdrawn by wells is one of the quantitative variables that can be applied to estimate groundwater resources and further evaluate the human influence on groundwater systems. The accuracy for the calculation of the amount of water withdrawal significantly influences the regional groundwater resource evaluation and management. However, the decentralized groundwater pumping, inefficient management, measurement errors and uncertainties have resulted in considerable errors in the groundwater withdrawal estimation. In this study, to improve the estimation of the groundwater withdrawal, an innovative approach was proposed using an inversion method based on a regional groundwater flow numerical model, and this method was then applied in the North China Plain. The principle of the method was matching the simulated water levels with the observation ones by adjusting the amount of groundwater withdrawal. In addition, uncertainty analysis of hydraulic conductivity and specific yield for the estimation of the groundwater withdrawal was conducted. By using the proposed inversion method, the estimated annual average groundwater withdrawal was approximately 24.92×10^9 m^3 in the North China Plain from 2002 to 2008. The inversion method also significantly improved the simulation results for both hydrograph and the flow field. Results of the uncertainty analysis showed that the hydraulic conductivity was more sensitive to the inversion results than the specific yield.展开更多
A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),an...A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),and the Industrial Internet ofThings.With the guidance and quick acceleration of the developme nt of advanced materials,as envisioned by official documents worldwide,more investigations are required to construct relative numerical standards for material informatics.This work proposes a universal DID format consisting of a set of build chains,which aligns with the classical form of identifier in both international and national standards,such as ISO/IEC 29168-1:2000,GB/T 27766-2011,GA/T 543.2-2011,GM/T 0006-2012,GJB 7365-2011,SL 325-2014,SL 607-201&WS 363.2-2011,and QX/T 39-2005.Each build chain is made up of capital letters and numbers,with no symbols.Moreover,the total length of each build chain is not restricted,which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC 10646.Based on these rules,the proposed DID is flexible and convenient for extendi ng and sharing in and between various cloud-based platforms.Accordingly,classical two-dimensional(2D)codes,including the Hanxin Code,Lots Perception Matrix(LP)Code,Quick Response(Q.R)code,Grid Matrix(GM)code,and Data Matrix(DM)Code,can be constructed and precisely recognized and/or decoded by either smart phones or specific machines.By utilizing these 2D codes as the fingerprints of a set of data linked with cloud-based platforms,progress and updates in the composition-processing-structure-property-performance workflow process can be tracked spontaneously,paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity,performance,and collaboration.展开更多
Automatic conversion from a computer-aided design(CAD) model to Monte Carlo geometry is one of the most effective methods for large-scale and detailed Monte Carlo modeling. The CAD to Monte Carlo geometry converter(CM...Automatic conversion from a computer-aided design(CAD) model to Monte Carlo geometry is one of the most effective methods for large-scale and detailed Monte Carlo modeling. The CAD to Monte Carlo geometry converter(CMGC) is a newly developed conversion code based on the boundary representation to constructive solid geometry(BRep→CSG) conversion method. The goal of the conversion process in the CMGC is to generate an appropriate CSG representation to achieve highly efficient Monte Carlo simulations. We designed a complete solid decomposition scheme to split a complex solid into as few nonoverlapping simple sub-solids as possible. In the complete solid decomposition scheme, the complex solid is successively split by so-called direct, indirect, and auxiliary splitting surfaces. We defined the splitting edge and designed a method for determining the direct splitting surface based on the splitting edge, then provided a method for determining indirect and auxiliary splitting surfaces based on solid vertices. Only the sub-solids that contain concave boundary faces need to be supplemented with auxiliary surfaces because the solid is completely decomposed, which will reduce the redundancy in the CSG expression. After decomposition, these sub-solids are located on only one side of their natural and auxiliary surfaces;thus, each sub-solid can be described by the intersections of a series of half-spaces or geometrical primitives. The CMGC has a friendly graphical user interface and can convert a CAD model into geometry input files for several Monte Carlo codes. The reliability of the CMGC was evaluated by converting several complex models and calculating the relative volume errors. Moreover, JMCT was used to test the efficiency of the Monte Carlo simulation. The results showed that the converted models performed well in particle transport calculations.展开更多
The detection technology of concealed bulk explosives is related to social security and national defense construction and has important research significance. In this paper, an element analysis method of concealed exp...The detection technology of concealed bulk explosives is related to social security and national defense construction and has important research significance. In this paper, an element analysis method of concealed explosives based on thermal neutron analysis is proposed.This method could provide better reconstruction precision for hydrogen, carbon, and nitrogen ratios, making it possible to discriminate explosives from other compounds with the same elements but different proportions, as well as to identify the types of concealed bulk explosives. In this paper, the basic principles and mathematical model of this method are first introduced, and the calculation formula of the element number ratio(the ratio between the nucleus numbers of two different elements) of the concealed explosive is deduced. Second, a numerical simulation platform of this method was established based on the Monte Carlo JMCT code. By calibrating the absorption efficiencies of the explosive device to c rays, the element number ratios of a concealed explosive model under the irradiation of thermal neutrons were reconstructed from the neutron capture prompt c-ray spectrum. The reconstruction values were in good agreement with the actual values,which shows that this method has a high reconstruction precision of the element number ratio for concealed explosives. Lastly, it was demonstrated using the simulation study that this method can discriminate explosives,drugs, and common materials, with the capability of determining the existence of concealed bulk explosives and identifying explosive types.展开更多
The analysis of the fuel depletion behavior is critical for maintaining the safety of accelerator-driven subcritical systems(ADSs). The code COUPLE2.0 coupling 3-D neutron transport and point burnup calculation was de...The analysis of the fuel depletion behavior is critical for maintaining the safety of accelerator-driven subcritical systems(ADSs). The code COUPLE2.0 coupling 3-D neutron transport and point burnup calculation was developed by Tsinghua University. A Monte Carlo method is used for the neutron transport analysis, and the burnup calculation is based on a deterministic method. The code can be used for the analysis of targets coupled with a reactor in ADSs. In response to additional ADS analysis requirements at the Institute of Modern Physics at the Chinese Academy of Sciences, the COUPLE3.0 version was developed to include the new functions of(1) a module for the calculation of proton irradiation for the analysis of cumulative behavior using the residual radionuclide operating history,(2) a fixed-flux radiation module for hazard assessment and analysis of the burnable poison, and(3) a module for multi-kernel parallel calculation, which improves the radionuclide replacement for the burnup analysis to balance the precision level and computational efficiency of the program. This paper introduces thevalidation of the COUPLE3.0 code using a fast reactor benchmark and ADS benchmark calculations. Moreover,the proton irradiation module was verified by a comparison with the analytic method of calculating the210 Po accumulation results. The results demonstrate that COUPLE3.0 is suitable for the analysis of neutron transport and the burnup of nuclides for ADSs.展开更多
Numerical modeling is of crucial importance in understanding the behavior of regional groundwater system. However, the demand on modeling capability is intensive when performing high-resolution simulation over long ti...Numerical modeling is of crucial importance in understanding the behavior of regional groundwater system. However, the demand on modeling capability is intensive when performing high-resolution simulation over long time span. This paper presents the application of a parallel program to speed up the detailed modeling of the groundwater flow system in the North China Plain. The parallel program is implemented by rebuilding the well-known MODFLOW program on our parallelcomputing framework, which is achieved by designing patch-based parallel data structures and algorithms but maintaining the compute flow and functionalities of MODFLOW. The detailed model with more than one million grids and a decade of time has been solved. The parallel simulation results were examined against the field observed data and these two data are generally in good agreement. For the comparison on solution time, the parallel program running on 32 cores is 6 times faster than the fastest MICCG-based MODFLOW program and 11 times faster than the GMG-based MODFLOW program. Therefore, remarkable computational time can be saved when using the parallel program, which facilitates the rapid modeling and prediction of the groundwater flow system in the North China Plain.展开更多
Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accur...Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network.展开更多
The desire to increase spatial and temporal resolution in modeling groundwater system has led to the requirement for intensive computational ability and large memory space. In the course of satisfying such requirement...The desire to increase spatial and temporal resolution in modeling groundwater system has led to the requirement for intensive computational ability and large memory space. In the course of satisfying such requirement, parallel computing has played a core role over the past several decades. This paper reviews the parallel algebraic linear solution methods and the parallel implementation technologies for groundwater simulation. This work is carried out to provide guidance to enable modelers of groundwater systems to make sensible choices when developing solution methods based upon the current state of knowledge in parallel computing.展开更多
Determining the mass of plutonium metal is an important research objective in the field of nuclear material accounting and control.Based on the 3D neutron and photon transport code JMCT(Jointed Monte Carlo Transport),...Determining the mass of plutonium metal is an important research objective in the field of nuclear material accounting and control.Based on the 3D neutron and photon transport code JMCT(Jointed Monte Carlo Transport),the gamma ray multiplicity of ^(240)Pu was simulated in this study,and the average number of gamma rays leaking from ^(240)Pu solid spheres with different masses was also obtained.The simulation results show that there is a oneto-one correspondence between the average number of gamma rays and the mass of ^(240)Pu solid spheres in the range of 0.50–3.00 kg.This result provides a basis for using the average number of gamma rays to account for the mass of ^(240)Pu.展开更多
Ambient Assisted Living(AAL) is becoming an important research field. Many technologies have emerged related with pervasive computing vision, which can give support for AAL. One of the most reliable approaches is base...Ambient Assisted Living(AAL) is becoming an important research field. Many technologies have emerged related with pervasive computing vision, which can give support for AAL. One of the most reliable approaches is based on wireless sensor networks(WSNs). In this paper, we propose a coverage-aware unequal clustering protocol with load separation(CUCPLS) for data gathering of AAL applications based on WSNs. Firstly, the coverage overlap factor for nodes is introduced that accounts for the degree of target nodes covered. In addition, to balance the intra-cluster and inter-cluster energy consumptions, different competition radiuses of CHs are computed theoretically in different rings, and smaller clusters are formed near the sink. Moreover, two CHs are selected in each cluster for load separation to alleviate the substantial energy consumption difference between a single CH and its member nodes. Furthermore, a backoff waiting time is adopted during the selection of the two CHs to reduce the number of control messages employed. Simulation results demonstrate that the CUCPLS not only can achieve better coverage performance, but also balance the energy consumption of a network and prolong network lifetime.展开更多
The electromagnetic environment of laneways in underground coal mines is an important area for the design of new electronic products,as well as a fundamental space for mine monitoring,surveillance,communications and c...The electromagnetic environment of laneways in underground coal mines is an important area for the design of new electronic products,as well as a fundamental space for mine monitoring,surveillance,communications and control systems.An investigation of electromagnetic interference in coal mines is essential for the enhancement of performances of these systems.In this study,a new field method is provided in which radiated emission tests in coal mine laneways have been carried out.We conclude that:1) the wiring motor vehicles can radiate interference with a bandwidth up to 1 GHz and with an amplitude 10 dBμV/m higher than the background noise;2) the PHS(Personal Handy phone System) mobile communication system can cause interference 40 dBμV/m higher than the background noise;3) an interference 25 dBμV/m higher than the background noise can be generated during the communication at a working bandwidth of 48.8 MHz;and 4) power cables,battery vehicles as well as mechanical and electrical dong rooms have little effect on the electromagnetic radiation environment in coal mine tunnels.展开更多
Due to lack of strictly defined formal semantics, an UML activity diagram is unsuitable for the tasks of formal analysis, verification and assertion on the system it describes. In this paper, Petri net is used to defi...Due to lack of strictly defined formal semantics, an UML activity diagram is unsuitable for the tasks of formal analysis, verification and assertion on the system it describes. In this paper, Petri net is used to define the formal semantics of an UML activity diagram containing object flow states, laying a foundation for the precise description and analysis of a workflow system.展开更多
The global view of firewall policy conflict is important for administrators to optimize the policy.It has been lack of appropriate firewall policy global conflict analysis,existing methods focus on local conflict dete...The global view of firewall policy conflict is important for administrators to optimize the policy.It has been lack of appropriate firewall policy global conflict analysis,existing methods focus on local conflict detection.We research the global conflict detection algorithm in this paper.We presented a semantic model that captures more complete classifications of the policy using knowledge concept in rough set.Based on this model,we presented the global conflict formal model,and represent it with OBDD(Ordered Binary Decision Diagram).Then we developed GFPCDA(Global Firewall Policy Conflict Detection Algorithm) algorithm to detect global conflict.In experiment,we evaluated the usability of our semantic model by eliminating the false positives and false negatives caused by incomplete policy semantic model,of a classical algorithm.We compared this algorithm with GFPCDA algorithm.The results show that GFPCDA detects conflicts more precisely and independently,and has better performance.展开更多
基金supported by the National Natural Science Foundation of China(No.U23B2067)Innovation Program of CAEP(No.CX20210045)。
文摘In response to the demand for rapid geometric modeling in Monte Carlo radiation transportation calculations for large-scale and complex geometric scenes,functional improvements,and algorithm optimizations were performed using CAD-to-Monte Carlo geometry conversion(CMGC)code.Boundary representation(BRep)to constructive solid geometry(CSG)conversion and visual CSG modeling were combined to address the problem of non-convertible geometries such as spline surfaces.The splitting surface assessment method in BRep-to-CSG conversion was optimized to reduce the number of Boolean operations using an Open Cascade.This,in turn,reduced the probability of CMGC conversion failure.The auxiliary surface generation algorithm was optimized to prevent the generation of redundant auxiliary surfaces that cause an excessive decomposition of CAD geometry solids.These optimizations enhanced the usability and stability of the CMGC model conversion.CMGC was applied successfully to the JMCT transportation calculations for the conceptual designs of five China Fusion Engineering Test Reactor(CFETR)blankets.The rapid replacement of different blanket schemes was achieved based on the baseline CFETR model.The geometric solid number of blankets ranged from hundreds to tens of thousands.The correctness of the converted CFETR models using CMGC was verified through comparisons with the MCNP calculation results.The CMGC supported radiation field evaluations for a large urban scene and detailed ship scene.This enabled the rapid conversion of CAD models with thousands of geometric solids into Monte Carlo CSG models.An analysis of the JMCT transportation simulation results further demonstrated the accuracy and effectiveness of the CMGC.
基金co-supported by the National Natural Science Foundation of China(No.12472332)。
文摘This paper investigates the influence of the spanwise-distributed trailing-edge camber morphing on the dynamic stall characteristics of a finite-span wing at Re=2×10^(5).The mathematical model of the spanwise-distributed trailing-edge camber morphing is established based on Chebyshev polynomials,and the deformed wing surface is modeled by a spline surface according to the rib's morphing in the chordwise direction.The Computational Fluid Dynamics(CFD)method is adopted to obtain flow-field results and aerodynamic forces.The SST-γmodel is introduced and the overset mesh technique is adopted.The numerical results show that the spanwisedistributed trailing-edge morphing obviously changes the aerodynamic and energy transfer characteristics of the dynamic stall.Especially when the phase difference between the trailing-edge motion and the wing pitch is-π/2,the interaction between the three-dimensional(3-D)Leading-Edge Vortex(LEV)and Trailing-Edge Vortex(TEV)is strengthened,and the work done by the aerodynamic force turns negative.This indicates that the trailing-edge deformation has the potential to suppress the oscillation amplitude of stall flutter.We also found that as the trailing-edge camber morphing varies more complexly along the spanwise direction,the suppression effect decreases accordingly.
基金Supported by the National Key R&D Program of China(No.2023YFB4502200)the National Natural Science Foundation of China(No.U22A2028,61925208,62222214,62341411,62102398,62102399,U20A20227,62302478,62302482,62302483,62302480,62302481)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB0660300,XDB0660301,XDB0660302)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(No.YSBR-029)the Youth Innovation Promotion Association of Chinese Academy of Sciences and Xplore Prize.
文摘The challenge of enhancing the generalization capacity of reinforcement learning(RL)agents remains a formidable obstacle.Existing RL methods,despite achieving superhuman performance on certain benchmarks,often struggle with this aspect.A potential reason is that the benchmarks used for training and evaluation may not adequately offer a diverse set of transferable tasks.Although recent studies have developed bench-marking environments to address this shortcoming,they typically fall short in providing tasks that both ensure a solid foundation for generalization and exhibit significant variability.To overcome these limitations,this work introduces the concept that‘objects are composed of more fundamental components’in environment design,as implemented in the proposed environment called summon the magic(StM).This environment generates tasks where objects are derived from extensible and shareable basic components,facilitating strategy reuse and enhancing generalization.Furthermore,two new metrics,adaptation sensitivity range(ASR)and parameter correlation coefficient(PCC),are proposed to better capture and evaluate the generalization process of RL agents.Experimental results show that increasing the number of basic components of the object reduces the proximal policy optimization(PPO)agent’s training-testing gap by 60.9%(in episode reward),significantly alleviating overfitting.Additionally,linear variations in other environmental factors,such as the training monster set proportion and the total number of basic components,uniformly decrease the gap by at least 32.1%.These results highlight StM’s effectiveness in benchmarking and probing the generalization capabilities of RL algorithms.
基金Youth Innovation Promotion Association CAS,Grant/Award Number:2021103Strategic Priority Research Program of Chinese Academy of Sciences,Grant/Award Number:XDC02060500。
文摘Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.
基金supported by the National Natural Science Foundation of China(Grant No.12302501)the China Postdoctoral Science Foun-dation(Grant No.2023MD744236)+4 种基金the Natural Science Basic Research Program of Shaanxi(Grant No.2024JC-YBQN-0061)the Postdoctoral Research Project of Shaanxi Province(Grant No.2023BSHEDZZ270)the Special Scientific Research Plan Project of Education Department of Shaanxi Provincial Government(Grant No.23JK0509)the Scientific Research Foundation for Excellent Returned Overseas Chinese Schol-ars funded by Shaanxi Provincial Government(Grant No.2023-021)the Innovation and Entrepreneurship Projects for College Students(Grant No.S202310703047).
文摘Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of rocks.The macrofailure behaviors of rocks are primarily formed after experiencing the initiation,propagation,and coalescenceof micro-cracks.In this paper,the grain-based discretized virtual internal bond model is employed to investigatethe fracturing process of unloaded rock under high in-situ stresses from the micro-fracture perspective.Thesimulated micro-fracturing process reveals that the longitudinal stress waves induced by unloading lead to thevisible unloading effect.The influences of in-situ stresses,mineral grain sizes,and grain heterogeneity on rockmacro and micro fracture are investigated.Micro-crack areas of tensile and shear cracks and micro-crack anglesare statistically analyzed to reveal the rock micro-fracture characteristics.The simulated results indicate thatthe combined effect of the stress state transition and the unloading effect dominates the rock unloading failure.The vertical and horizontal in-situ stresses determine the stress state of surrounding rock after unloading andthe unloading effect,respectively.As the vertical stress increases,the stress level after unloading is higher,andthe shear failure characteristics become more obvious.As the horizontal stress increases,the unloading effectincreases,leading to the intensification of tensile failure.The mineral grain size and grain heterogeneity alsohave nonnegligible influences on rock unloading failure.The micro-fracture perspective provides further insightinto the unloading failure mechanism of deep rock excavation.
基金funded by the National Natural Science Foundation of China(Grant No.12272247)National Key Project(Grant No.GJXM92579)Major Research and Development Project of Metallurgical Corporation of China Ltd.in the Non-Steel Field(Grant No.2021-5).
文摘The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.
文摘Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.
基金supported by the National Basic Research Program of China (No. 2010CB428804)the Public Welfare Industry Special Funds for Scientific Research from Ministry of Land and Resources of China (No. 201211079-4).
文摘The amount of water withdrawn by wells is one of the quantitative variables that can be applied to estimate groundwater resources and further evaluate the human influence on groundwater systems. The accuracy for the calculation of the amount of water withdrawal significantly influences the regional groundwater resource evaluation and management. However, the decentralized groundwater pumping, inefficient management, measurement errors and uncertainties have resulted in considerable errors in the groundwater withdrawal estimation. In this study, to improve the estimation of the groundwater withdrawal, an innovative approach was proposed using an inversion method based on a regional groundwater flow numerical model, and this method was then applied in the North China Plain. The principle of the method was matching the simulated water levels with the observation ones by adjusting the amount of groundwater withdrawal. In addition, uncertainty analysis of hydraulic conductivity and specific yield for the estimation of the groundwater withdrawal was conducted. By using the proposed inversion method, the estimated annual average groundwater withdrawal was approximately 24.92×10^9 m^3 in the North China Plain from 2002 to 2008. The inversion method also significantly improved the simulation results for both hydrograph and the flow field. Results of the uncertainty analysis showed that the hydraulic conductivity was more sensitive to the inversion results than the specific yield.
基金This work was financially supported by the National Key Research and Development Program of China(2018YFB0703801,2018YFB0703802,2016YFB0701303,and 2016YFB0701304)CRRC Tangshan Co.,Ltd.(201750463031).Special thanks to Professor Hong Wang at Shanghai Jiao Tong University for the fruitful discussions and the constructive suggestions/comments.
文摘A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),and the Industrial Internet ofThings.With the guidance and quick acceleration of the developme nt of advanced materials,as envisioned by official documents worldwide,more investigations are required to construct relative numerical standards for material informatics.This work proposes a universal DID format consisting of a set of build chains,which aligns with the classical form of identifier in both international and national standards,such as ISO/IEC 29168-1:2000,GB/T 27766-2011,GA/T 543.2-2011,GM/T 0006-2012,GJB 7365-2011,SL 325-2014,SL 607-201&WS 363.2-2011,and QX/T 39-2005.Each build chain is made up of capital letters and numbers,with no symbols.Moreover,the total length of each build chain is not restricted,which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC 10646.Based on these rules,the proposed DID is flexible and convenient for extendi ng and sharing in and between various cloud-based platforms.Accordingly,classical two-dimensional(2D)codes,including the Hanxin Code,Lots Perception Matrix(LP)Code,Quick Response(Q.R)code,Grid Matrix(GM)code,and Data Matrix(DM)Code,can be constructed and precisely recognized and/or decoded by either smart phones or specific machines.By utilizing these 2D codes as the fingerprints of a set of data linked with cloud-based platforms,progress and updates in the composition-processing-structure-property-performance workflow process can be tracked spontaneously,paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity,performance,and collaboration.
基金the National Natural Science Foundation of China(No.11805017)。
文摘Automatic conversion from a computer-aided design(CAD) model to Monte Carlo geometry is one of the most effective methods for large-scale and detailed Monte Carlo modeling. The CAD to Monte Carlo geometry converter(CMGC) is a newly developed conversion code based on the boundary representation to constructive solid geometry(BRep→CSG) conversion method. The goal of the conversion process in the CMGC is to generate an appropriate CSG representation to achieve highly efficient Monte Carlo simulations. We designed a complete solid decomposition scheme to split a complex solid into as few nonoverlapping simple sub-solids as possible. In the complete solid decomposition scheme, the complex solid is successively split by so-called direct, indirect, and auxiliary splitting surfaces. We defined the splitting edge and designed a method for determining the direct splitting surface based on the splitting edge, then provided a method for determining indirect and auxiliary splitting surfaces based on solid vertices. Only the sub-solids that contain concave boundary faces need to be supplemented with auxiliary surfaces because the solid is completely decomposed, which will reduce the redundancy in the CSG expression. After decomposition, these sub-solids are located on only one side of their natural and auxiliary surfaces;thus, each sub-solid can be described by the intersections of a series of half-spaces or geometrical primitives. The CMGC has a friendly graphical user interface and can convert a CAD model into geometry input files for several Monte Carlo codes. The reliability of the CMGC was evaluated by converting several complex models and calculating the relative volume errors. Moreover, JMCT was used to test the efficiency of the Monte Carlo simulation. The results showed that the converted models performed well in particle transport calculations.
文摘The detection technology of concealed bulk explosives is related to social security and national defense construction and has important research significance. In this paper, an element analysis method of concealed explosives based on thermal neutron analysis is proposed.This method could provide better reconstruction precision for hydrogen, carbon, and nitrogen ratios, making it possible to discriminate explosives from other compounds with the same elements but different proportions, as well as to identify the types of concealed bulk explosives. In this paper, the basic principles and mathematical model of this method are first introduced, and the calculation formula of the element number ratio(the ratio between the nucleus numbers of two different elements) of the concealed explosive is deduced. Second, a numerical simulation platform of this method was established based on the Monte Carlo JMCT code. By calibrating the absorption efficiencies of the explosive device to c rays, the element number ratios of a concealed explosive model under the irradiation of thermal neutrons were reconstructed from the neutron capture prompt c-ray spectrum. The reconstruction values were in good agreement with the actual values,which shows that this method has a high reconstruction precision of the element number ratio for concealed explosives. Lastly, it was demonstrated using the simulation study that this method can discriminate explosives,drugs, and common materials, with the capability of determining the existence of concealed bulk explosives and identifying explosive types.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA03030102)
文摘The analysis of the fuel depletion behavior is critical for maintaining the safety of accelerator-driven subcritical systems(ADSs). The code COUPLE2.0 coupling 3-D neutron transport and point burnup calculation was developed by Tsinghua University. A Monte Carlo method is used for the neutron transport analysis, and the burnup calculation is based on a deterministic method. The code can be used for the analysis of targets coupled with a reactor in ADSs. In response to additional ADS analysis requirements at the Institute of Modern Physics at the Chinese Academy of Sciences, the COUPLE3.0 version was developed to include the new functions of(1) a module for the calculation of proton irradiation for the analysis of cumulative behavior using the residual radionuclide operating history,(2) a fixed-flux radiation module for hazard assessment and analysis of the burnable poison, and(3) a module for multi-kernel parallel calculation, which improves the radionuclide replacement for the burnup analysis to balance the precision level and computational efficiency of the program. This paper introduces thevalidation of the COUPLE3.0 code using a fast reactor benchmark and ADS benchmark calculations. Moreover,the proton irradiation module was verified by a comparison with the analytic method of calculating the210 Po accumulation results. The results demonstrate that COUPLE3.0 is suitable for the analysis of neutron transport and the burnup of nuclides for ADSs.
基金supported by the National Basic Research Program (973 Program) of China (Nos. 2010CB428804 and 2011CB309702)the Key Projects of National Natural Science Foundation of China (No. 61033009)
文摘Numerical modeling is of crucial importance in understanding the behavior of regional groundwater system. However, the demand on modeling capability is intensive when performing high-resolution simulation over long time span. This paper presents the application of a parallel program to speed up the detailed modeling of the groundwater flow system in the North China Plain. The parallel program is implemented by rebuilding the well-known MODFLOW program on our parallelcomputing framework, which is achieved by designing patch-based parallel data structures and algorithms but maintaining the compute flow and functionalities of MODFLOW. The detailed model with more than one million grids and a decade of time has been solved. The parallel simulation results were examined against the field observed data and these two data are generally in good agreement. For the comparison on solution time, the parallel program running on 32 cores is 6 times faster than the fastest MICCG-based MODFLOW program and 11 times faster than the GMG-based MODFLOW program. Therefore, remarkable computational time can be saved when using the parallel program, which facilitates the rapid modeling and prediction of the groundwater flow system in the North China Plain.
基金financially supported by the National Natural Science Foundation of China(No.52102470)。
文摘Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network.
基金supported by the National Basic Research Program (973 Program) of China under Grant No.2010CB428804 and 2011CB 309702
文摘The desire to increase spatial and temporal resolution in modeling groundwater system has led to the requirement for intensive computational ability and large memory space. In the course of satisfying such requirement, parallel computing has played a core role over the past several decades. This paper reviews the parallel algebraic linear solution methods and the parallel implementation technologies for groundwater simulation. This work is carried out to provide guidance to enable modelers of groundwater systems to make sensible choices when developing solution methods based upon the current state of knowledge in parallel computing.
基金supported by the National Natural Science Foundation of China(No.12005199)the fund project of the China Academy of Engineering Physics(Nos.TP03201601 and CX20210009)。
文摘Determining the mass of plutonium metal is an important research objective in the field of nuclear material accounting and control.Based on the 3D neutron and photon transport code JMCT(Jointed Monte Carlo Transport),the gamma ray multiplicity of ^(240)Pu was simulated in this study,and the average number of gamma rays leaking from ^(240)Pu solid spheres with different masses was also obtained.The simulation results show that there is a oneto-one correspondence between the average number of gamma rays and the mass of ^(240)Pu solid spheres in the range of 0.50–3.00 kg.This result provides a basis for using the average number of gamma rays to account for the mass of ^(240)Pu.
基金supported by the National Nature Science Foundation of China (61170169, 61170168)
文摘Ambient Assisted Living(AAL) is becoming an important research field. Many technologies have emerged related with pervasive computing vision, which can give support for AAL. One of the most reliable approaches is based on wireless sensor networks(WSNs). In this paper, we propose a coverage-aware unequal clustering protocol with load separation(CUCPLS) for data gathering of AAL applications based on WSNs. Firstly, the coverage overlap factor for nodes is introduced that accounts for the degree of target nodes covered. In addition, to balance the intra-cluster and inter-cluster energy consumptions, different competition radiuses of CHs are computed theoretically in different rings, and smaller clusters are formed near the sink. Moreover, two CHs are selected in each cluster for load separation to alleviate the substantial energy consumption difference between a single CH and its member nodes. Furthermore, a backoff waiting time is adopted during the selection of the two CHs to reduce the number of control messages employed. Simulation results demonstrate that the CUCPLS not only can achieve better coverage performance, but also balance the energy consumption of a network and prolong network lifetime.
基金supported by the National Natural Science Foundation of China (No.50674093)the National Scientific and Technological Support Projects (No.2006BAK03B00) and the Pingdingshan Coal Mine Group
文摘The electromagnetic environment of laneways in underground coal mines is an important area for the design of new electronic products,as well as a fundamental space for mine monitoring,surveillance,communications and control systems.An investigation of electromagnetic interference in coal mines is essential for the enhancement of performances of these systems.In this study,a new field method is provided in which radiated emission tests in coal mine laneways have been carried out.We conclude that:1) the wiring motor vehicles can radiate interference with a bandwidth up to 1 GHz and with an amplitude 10 dBμV/m higher than the background noise;2) the PHS(Personal Handy phone System) mobile communication system can cause interference 40 dBμV/m higher than the background noise;3) an interference 25 dBμV/m higher than the background noise can be generated during the communication at a working bandwidth of 48.8 MHz;and 4) power cables,battery vehicles as well as mechanical and electrical dong rooms have little effect on the electromagnetic radiation environment in coal mine tunnels.
文摘Due to lack of strictly defined formal semantics, an UML activity diagram is unsuitable for the tasks of formal analysis, verification and assertion on the system it describes. In this paper, Petri net is used to define the formal semantics of an UML activity diagram containing object flow states, laying a foundation for the precise description and analysis of a workflow system.
基金supported by the National Nature Science Foundation of China under Grant No.61170295 the Project of National ministry under Grant No.A2120110006+2 种基金 the Co-Funding Project of Beijing Municipal Education Commission under Grant No.JD100060630 the Beijing Education Committee General Program under Grant No. KM201211232010 the National Nature Science Foundation of China under Grant NO. 61370065
文摘The global view of firewall policy conflict is important for administrators to optimize the policy.It has been lack of appropriate firewall policy global conflict analysis,existing methods focus on local conflict detection.We research the global conflict detection algorithm in this paper.We presented a semantic model that captures more complete classifications of the policy using knowledge concept in rough set.Based on this model,we presented the global conflict formal model,and represent it with OBDD(Ordered Binary Decision Diagram).Then we developed GFPCDA(Global Firewall Policy Conflict Detection Algorithm) algorithm to detect global conflict.In experiment,we evaluated the usability of our semantic model by eliminating the false positives and false negatives caused by incomplete policy semantic model,of a classical algorithm.We compared this algorithm with GFPCDA algorithm.The results show that GFPCDA detects conflicts more precisely and independently,and has better performance.
