Compared with traditional feedback control,predictive control can eliminate the lag of pose control and avoid the snakelike motion of shield machines.Therefore,a shield pose prediction model was proposed based on dyna...Compared with traditional feedback control,predictive control can eliminate the lag of pose control and avoid the snakelike motion of shield machines.Therefore,a shield pose prediction model was proposed based on dynamic modeling.Firstly,the dynamic equations of shield thrust system were established to clarify the relationship between force and movement of shield machine.Secondly,an analytical model was proposed to predict future multistep pose of the shield machine.Finally,a virtual prototype model was developed to simulate the dynamic behavior of the shield machine and validate the accuracy of the proposed pose prediction method.Results reveal that the model proposed can predict the shield pose with high accuracy,which can provide a decision basis whether for manual or automatic control of shield pose.展开更多
This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key de...This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.展开更多
A deep understanding of explosive sensitivities and their factors is important for safe and reliable applications.However,quantitative prediction of the sensitivities is difficult.Here,reactive molecular dynamics simu...A deep understanding of explosive sensitivities and their factors is important for safe and reliable applications.However,quantitative prediction of the sensitivities is difficult.Here,reactive molecular dynamics simulation models for high-speed piston impacts on explosive supercells were established.Simulations were also performed to investigate shock-induced reactions of various high-energy explosives.The fraction of reacted explosive molecules in an initial supercell changed linearly with the propagation distance of the shock-wave front.The corresponding slope could be used as a reaction rate for a specific shock-loading velocity.Reaction rates that varied with the shock-loading pressure exhibited two-stage linearities with different slopes.The two inflection points corresponded to the initial and accelerated reactions,which respectively correlated to the thresholds of shock-induced ignition and detonation.Therefore,the ignition and detonation critical pressures could be determined.The sensitivity could then be a quantitative prediction of the critical pressure.The accuracies of the quantitative shock sensitivity predictions were verified by comparing the impact and shock sensitivities of common explosives and the characteristics of anisotropic shock-induced reactions.Molecular dynamics simulations quantitatively predict and rank shock sensitivities by using only crystal structures of the explosives.Overall,this method will enable the design and safe use of explosives.展开更多
A new mobile multicast scheme called mobility prediction based mobile multicast(MPBMM) was proposed. In MPBMM, when a mobile node (MN) roams among subnets during a multicast session, MN predicts the next subnet, to wh...A new mobile multicast scheme called mobility prediction based mobile multicast(MPBMM) was proposed. In MPBMM, when a mobile node (MN) roams among subnets during a multicast session, MN predicts the next subnet, to which MN will attach, by the information of its position and mobility speed, consequently speeds up the handoff procedure. Simulation results show that the proposed scheme can minimize the loss of multicast packets, reduce the delay of subnet handoff, decrease the frequency of multicast tree reconfiguration, and optimize the delivery path of multicast packets. When MN moves among subnets at different speeds (from 5 to 25 ms), the maximum loss ratio of multicast packets is less than0.2%, the maximum inter-arrival time of multicast packets is 117 ms, so the proposed scheme can meet the QoS requirements of real-time services. In addition, MPBMM can support the mobility of multicast source.展开更多
The flow behavior and dynamic globularization of TC11 titanium alloy during subtransus deformation are investigated through hot compression tests. A constitutive model is established based on physical-based hardening ...The flow behavior and dynamic globularization of TC11 titanium alloy during subtransus deformation are investigated through hot compression tests. A constitutive model is established based on physical-based hardening model and phenomenological softening model. And based on the recrystallization mechanisms of globularization, the Avrami type kinetics model is established for prediction of globularization fraction and globularized grain size under large strain subtransus deformation of TC11 alloy. As the preliminary application of the previous results, the cogging process of large size TC11 alloy billet is simulated. Based on subroutine development of the DEFORM software, the coupled simulation of one fire cogging process is developed. It shows that the predicted results are in good agreement with the experimental results in forging load and microstructure characteristic, which validates the reliability of the developed FEM subroutine models.展开更多
Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of contro...Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of control schemes for this problem, but the increasingly strict market demand for strip quality requires further improvements. This work describes a dynamic matrix predictive control(DMC) strategy that realizes the optimal control of a hydraulic looper multivariable system. Simulation experiments for a traditional controller and the proposed DMC controller were conducted using MATLAB/Simulink software. The simulation results show that both controllers acquire good control effects with model matching. However, when the model is mismatched, the traditional controller produces an overshoot of 32.4% and a rising time of up to 2120.2 ms, which is unacceptable in a hydraulic looper system. The DMC controller restricts the overshoot to less than 0.08%, and the rising time is less than 48.6 ms in all cases.展开更多
Although the dynamic properties of subgrade soils in seasonally frozen areas have already been studied, few researchers have considered the influence of shallow groundwater during the freeze–thaw(F–T) cycles. So a m...Although the dynamic properties of subgrade soils in seasonally frozen areas have already been studied, few researchers have considered the influence of shallow groundwater during the freeze–thaw(F–T) cycles. So a multifunctional F–T cycle system was developed to imitate the groundwater recharge in the subgrade during the freezing process and a large number of dynamic triaxial experiments were conducted after the F–T cycles. Some significant factors including the F–T cycle number, compaction degree, confining pressure, cyclic deviator stress, loading frequency, and water content were investigated for the resilient modulus of soils. The experimental results indicated that the dynamic resilient modulus of the subgrade was negatively correlated with the cyclic deviator stress, F–T cycle number, and initial water content, whereas the degree of compaction, confining pressure, and loading frequency could enhance the resilient modulus. Furthermore, a modified model considering the F–T cycle number and stress state was established to predict the dynamic resilient modulus. The calculated results of this modified model were very close to the experimental results. Consequently, calculation of the resilient modulus for F–T cycles considering the dynamic load was appropriate. This study provides reference for research focusing on F–T cycles with groundwater supply and the dynamic resilient moduli of subgrade soils in seasonally frozen areas.展开更多
A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work...A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work modes, system configuration, dynamic probabilities and degeneration of components,as well as spacecraft dynamics and kinematics. By introducing the frame of DFT, the system is classified into several layers, and the problem of state combination explosion is artfully overcome.An improved dynamic reliability model(DRM) based on the Nelson hypothesis is investigated to improve the defect of cumulative failure probability(CFP), which is used to address the failure probability of components in the SHA model. The simulation using the Monte-Carlo method is finally conducted on two satellites, which are deployed with the same multi-gyro subsystem but run on different orbits. The results show that the predicted useful life of the attitude control system(ACS) with consideration of abrupt failure,degradation, and running environment is quite different between the two satellites.展开更多
Refined composite multi-scale dispersion entropy(RCMDE),as a new and effective nonlinear dynamic method,has been applied in the field of medical diagnosis and fault diagnosis.In this paper,we first introduce RCMDE int...Refined composite multi-scale dispersion entropy(RCMDE),as a new and effective nonlinear dynamic method,has been applied in the field of medical diagnosis and fault diagnosis.In this paper,we first introduce RCMDE into the field of underwater acoustic signal processing for complexity feature extraction of ship radiated noise,and then propose a novel classification method for ship-radiated noise based on RCMDE and k-nearest neighbor(KNN),termed RCMDE-KNN.The results of a comparative experiment show that the proposed RCMDE-KNN classification method can effectively extract the complexity features of ship-radiated noise,and has better classification performance under one and two scales than the other three classification methods based on multi-scale permutation entropy(MPE)and KNN,multi-scale weighted-permutation entropy(MW-PE)and KNN,and multi-scale dispersion entropy(MDE)and KNN,termed MPE-KNN,MW-PE-KNN,and MDE-KNN.It is proved that the RCMDE-KNN classification method for ship-radiated noise is feasible and effective,and can obtain a very high recognition rate.展开更多
A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,mu...A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was modeled.Because the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was proposed.In addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching process.Unlike traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic environments.Several reported algorithms were compared with AIDE by using Moving Peaks Benchmarks.Preliminary experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the optimization.Thus,AIDE is useful for the optimization of dynamic environments.展开更多
Wheel/rail relationship is a fundamental problem of railway system. Wear of wheel profiles has great effect on vehicle performance. Thus, it is important not just for the analysis of wear characteristics but for its p...Wheel/rail relationship is a fundamental problem of railway system. Wear of wheel profiles has great effect on vehicle performance. Thus, it is important not just for the analysis of wear characteristics but for its prediction. Actual wheel profiles of the high-speed trains on service were measured in the high-speed line and the wear characteristics were analyzed which came to the following results. The wear location was centralized from-15 mm to 25 mm. The maximum wear value appeared at the area of 5 mm from tread center far from wheel flange and it was less than 1.5 mm. Then, wheel wear was fitted to get the polynomial functions on different locations and operation mileages. A binary numerical prediction model was raised to predict wheel wear. The prediction model was proved by vehicle system dynamics and wheel/rail contact geometry. The results show that the prediction model can reflect wear characteristics of measured profiles and vehicle performances.展开更多
基金Project(2023JBZY030)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(U1834208)supported by the National Natural Science Foundation of China。
文摘Compared with traditional feedback control,predictive control can eliminate the lag of pose control and avoid the snakelike motion of shield machines.Therefore,a shield pose prediction model was proposed based on dynamic modeling.Firstly,the dynamic equations of shield thrust system were established to clarify the relationship between force and movement of shield machine.Secondly,an analytical model was proposed to predict future multistep pose of the shield machine.Finally,a virtual prototype model was developed to simulate the dynamic behavior of the shield machine and validate the accuracy of the proposed pose prediction method.Results reveal that the model proposed can predict the shield pose with high accuracy,which can provide a decision basis whether for manual or automatic control of shield pose.
基金supported by Poongsan-KAIST Future Research Center Projectthe fund support provided by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Grant No.2023R1A2C2005661)。
文摘This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.
基金supported by the National Natural Science Foundation of China(Grant No.11832006).
文摘A deep understanding of explosive sensitivities and their factors is important for safe and reliable applications.However,quantitative prediction of the sensitivities is difficult.Here,reactive molecular dynamics simulation models for high-speed piston impacts on explosive supercells were established.Simulations were also performed to investigate shock-induced reactions of various high-energy explosives.The fraction of reacted explosive molecules in an initial supercell changed linearly with the propagation distance of the shock-wave front.The corresponding slope could be used as a reaction rate for a specific shock-loading velocity.Reaction rates that varied with the shock-loading pressure exhibited two-stage linearities with different slopes.The two inflection points corresponded to the initial and accelerated reactions,which respectively correlated to the thresholds of shock-induced ignition and detonation.Therefore,the ignition and detonation critical pressures could be determined.The sensitivity could then be a quantitative prediction of the critical pressure.The accuracies of the quantitative shock sensitivity predictions were verified by comparing the impact and shock sensitivities of common explosives and the characteristics of anisotropic shock-induced reactions.Molecular dynamics simulations quantitatively predict and rank shock sensitivities by using only crystal structures of the explosives.Overall,this method will enable the design and safe use of explosives.
基金Project (60573127) supported by the National Natural Science Foundation of ChinaProject (20040533036) supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China+1 种基金Project (05JJ40131) supported by the Natural Science Foundation of Hunan Province, ChinaProject(03C326) supported by the Natural Science Foundation of Education Department of Hunan Province, China
文摘A new mobile multicast scheme called mobility prediction based mobile multicast(MPBMM) was proposed. In MPBMM, when a mobile node (MN) roams among subnets during a multicast session, MN predicts the next subnet, to which MN will attach, by the information of its position and mobility speed, consequently speeds up the handoff procedure. Simulation results show that the proposed scheme can minimize the loss of multicast packets, reduce the delay of subnet handoff, decrease the frequency of multicast tree reconfiguration, and optimize the delivery path of multicast packets. When MN moves among subnets at different speeds (from 5 to 25 ms), the maximum loss ratio of multicast packets is less than0.2%, the maximum inter-arrival time of multicast packets is 117 ms, so the proposed scheme can meet the QoS requirements of real-time services. In addition, MPBMM can support the mobility of multicast source.
文摘The flow behavior and dynamic globularization of TC11 titanium alloy during subtransus deformation are investigated through hot compression tests. A constitutive model is established based on physical-based hardening model and phenomenological softening model. And based on the recrystallization mechanisms of globularization, the Avrami type kinetics model is established for prediction of globularization fraction and globularized grain size under large strain subtransus deformation of TC11 alloy. As the preliminary application of the previous results, the cogging process of large size TC11 alloy billet is simulated. Based on subroutine development of the DEFORM software, the coupled simulation of one fire cogging process is developed. It shows that the predicted results are in good agreement with the experimental results in forging load and microstructure characteristic, which validates the reliability of the developed FEM subroutine models.
基金Project(N160704004)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(20131033)supported by the Ph D Start-up Fund of Natural Science Foundation of Liaoning Province,China
文摘Controlling the looper height and strip tension is important in hot strip mills because these variables affect both the strip quality and strip threading. Many researchers have proposed and applied a variety of control schemes for this problem, but the increasingly strict market demand for strip quality requires further improvements. This work describes a dynamic matrix predictive control(DMC) strategy that realizes the optimal control of a hydraulic looper multivariable system. Simulation experiments for a traditional controller and the proposed DMC controller were conducted using MATLAB/Simulink software. The simulation results show that both controllers acquire good control effects with model matching. However, when the model is mismatched, the traditional controller produces an overshoot of 32.4% and a rising time of up to 2120.2 ms, which is unacceptable in a hydraulic looper system. The DMC controller restricts the overshoot to less than 0.08%, and the rising time is less than 48.6 ms in all cases.
基金Projects(41672312, 41972294) supported by the National Natural Science Foundation of ChinaProject(2017CFA056) supported by the Outstanding Youth Foundation of Hubei Province, ChinaProject(KFJ170104) supported by the Changsha University of Science & Technology via Open Fund of National Engineering Laboratory of Highway Maintenance Technology, China。
文摘Although the dynamic properties of subgrade soils in seasonally frozen areas have already been studied, few researchers have considered the influence of shallow groundwater during the freeze–thaw(F–T) cycles. So a multifunctional F–T cycle system was developed to imitate the groundwater recharge in the subgrade during the freezing process and a large number of dynamic triaxial experiments were conducted after the F–T cycles. Some significant factors including the F–T cycle number, compaction degree, confining pressure, cyclic deviator stress, loading frequency, and water content were investigated for the resilient modulus of soils. The experimental results indicated that the dynamic resilient modulus of the subgrade was negatively correlated with the cyclic deviator stress, F–T cycle number, and initial water content, whereas the degree of compaction, confining pressure, and loading frequency could enhance the resilient modulus. Furthermore, a modified model considering the F–T cycle number and stress state was established to predict the dynamic resilient modulus. The calculated results of this modified model were very close to the experimental results. Consequently, calculation of the resilient modulus for F–T cycles considering the dynamic load was appropriate. This study provides reference for research focusing on F–T cycles with groundwater supply and the dynamic resilient moduli of subgrade soils in seasonally frozen areas.
基金supported by the Fundamental Research Funds for the Central Universities(2016083)
文摘A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work modes, system configuration, dynamic probabilities and degeneration of components,as well as spacecraft dynamics and kinematics. By introducing the frame of DFT, the system is classified into several layers, and the problem of state combination explosion is artfully overcome.An improved dynamic reliability model(DRM) based on the Nelson hypothesis is investigated to improve the defect of cumulative failure probability(CFP), which is used to address the failure probability of components in the SHA model. The simulation using the Monte-Carlo method is finally conducted on two satellites, which are deployed with the same multi-gyro subsystem but run on different orbits. The results show that the predicted useful life of the attitude control system(ACS) with consideration of abrupt failure,degradation, and running environment is quite different between the two satellites.
基金supported by National Natural Science Foundation of China(No.61871318 and 61833013)Shaanxi Provincial Key Research and Development Project(No.2019GY-099).
文摘Refined composite multi-scale dispersion entropy(RCMDE),as a new and effective nonlinear dynamic method,has been applied in the field of medical diagnosis and fault diagnosis.In this paper,we first introduce RCMDE into the field of underwater acoustic signal processing for complexity feature extraction of ship radiated noise,and then propose a novel classification method for ship-radiated noise based on RCMDE and k-nearest neighbor(KNN),termed RCMDE-KNN.The results of a comparative experiment show that the proposed RCMDE-KNN classification method can effectively extract the complexity features of ship-radiated noise,and has better classification performance under one and two scales than the other three classification methods based on multi-scale permutation entropy(MPE)and KNN,multi-scale weighted-permutation entropy(MW-PE)and KNN,and multi-scale dispersion entropy(MDE)and KNN,termed MPE-KNN,MW-PE-KNN,and MDE-KNN.It is proved that the RCMDE-KNN classification method for ship-radiated noise is feasible and effective,and can obtain a very high recognition rate.
基金Project(60625302) supported by the National Natural Science Foundation for Distinguished Young Scholars of ChinaProject(2009CB320603) supported by the National Basic Research Program of China+5 种基金Projects(10dz1121900,10JC1403400) supported by Shanghai Key Technologies R & D ProgramProject supported by the Fundamental Research Funds for the Central Universities in ChinaProject(200802511011) supported by the New Teacher Program of Specialized Research Fund for the Doctoral Program of Higher Education in ChinaProject(Y1090548) supported by Zhejiang Provincial Natural Science Fund,ChinaProject(2011C21077) supported by Zhejiang Technology Programme,ChinaProject(2011A610173) supported by Ningbo Natural Science Fund,China
文摘A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was modeled.Because the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was proposed.In addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching process.Unlike traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic environments.Several reported algorithms were compared with AIDE by using Moving Peaks Benchmarks.Preliminary experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the optimization.Thus,AIDE is useful for the optimization of dynamic environments.
基金Project(U1234208)supported by the Major Program of the National Natural Science Foundation of ChinaProject(2013J008-A)supported by the Research and Development Plan of Major Tasks in Science and Technology China Railways Co.Ltd.,China
文摘Wheel/rail relationship is a fundamental problem of railway system. Wear of wheel profiles has great effect on vehicle performance. Thus, it is important not just for the analysis of wear characteristics but for its prediction. Actual wheel profiles of the high-speed trains on service were measured in the high-speed line and the wear characteristics were analyzed which came to the following results. The wear location was centralized from-15 mm to 25 mm. The maximum wear value appeared at the area of 5 mm from tread center far from wheel flange and it was less than 1.5 mm. Then, wheel wear was fitted to get the polynomial functions on different locations and operation mileages. A binary numerical prediction model was raised to predict wheel wear. The prediction model was proved by vehicle system dynamics and wheel/rail contact geometry. The results show that the prediction model can reflect wear characteristics of measured profiles and vehicle performances.
