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
When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution...When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.展开更多
Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can b...Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.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
The microstructure evolution of 7A85 aluminum alloy at the conditions of strain rate(0.001−1 s^(−1))and deformation temperature(250−450°C)was studied by optical microscopy(OM)and electron back scattering diffract...The microstructure evolution of 7A85 aluminum alloy at the conditions of strain rate(0.001−1 s^(−1))and deformation temperature(250−450°C)was studied by optical microscopy(OM)and electron back scattering diffraction(EBSD).Based on the K-M dislocation density model,a two-stage K-M dislocation density model of 7A85 aluminum alloy was established.The results reveal that dynamic recovery(DRV)and dynamic recrystallization(DRX)are the main mechanisms of microstructure evolution during thermal deformation of 7A85 aluminum alloy.350−400°C is the transformation zone from dynamic recovery to dynamic recrystallization.At low temperature(≤350°C),DRV is the main mechanism,while DRX mostly occurs at high temperature(≥400°C).At this point,the sensitivity of microstructure evolution to temperature is relatively high.As the temperature increased,the average misorientation angle(θˉ_(c))increased significantly,ranging from 0.93°to 7.13°.Meanwhile,the f_(LAGBs) decreased with the highest decrease of 24%.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(72471240).
文摘When performing tasks,unmanned clusters often face a variety of strategy choices.One of the key issues in unmanned cluster tasks is the method through which to design autonomous collaboration and cooperative evolution mechanisms that allow for unmanned clusters to maximize their overall task effective-ness under the condition of strategic diversity.This paper ana-lyzes these task requirements from three perspectives:the diver-sity of the decision space,information network construction,and the autonomous collaboration mechanism.Then,this paper pro-poses a method for solving the problem of strategy selection diversity under two network structures.Next,this paper presents a Moran-rule-based evolution dynamics model for unmanned cluster strategies and a vision-driven-mechanism-based evolu-tion dynamics model for unmanned cluster strategy in the con-text of strategy selection diversity according to various unmanned cluster application scenarios.Finally,this paper pro-vides a simulation analysis of the effects of relevant parameters such as the payoff factor and cluster size on cooperative evolu-tion in autonomous cluster collaboration for the two types of models.On this basis,this paper presents advice for effectively addressing diverse choices in unmanned cluster tasks,thereby providing decision support for practical applications of unmanned cluster tasks.
基金Project(2023YFB4302500)supported by the National Key R&D Program of ChinaProject(52078485)supported by the National Natural Science Foundation of ChinaProjects(2021-Major-16,2021-Special-08)supported by the Science and Technology Research and Development Program Project of China Railway Group Limited。
文摘Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.
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Project(51675465)supported by the National Natural Science Foundation of ChinaProject(E2019203075)supported by the Natural Science Foundation of Hebei Province,China+1 种基金Project(BJ2019001)supported by the Top Young Talents Project of the Education Department of Hebei Province,ChinaProject(Kfkt2017-07)supported by the State Key Laboratory Program of High Performance Complex Manufacturing,China。
文摘The microstructure evolution of 7A85 aluminum alloy at the conditions of strain rate(0.001−1 s^(−1))and deformation temperature(250−450°C)was studied by optical microscopy(OM)and electron back scattering diffraction(EBSD).Based on the K-M dislocation density model,a two-stage K-M dislocation density model of 7A85 aluminum alloy was established.The results reveal that dynamic recovery(DRV)and dynamic recrystallization(DRX)are the main mechanisms of microstructure evolution during thermal deformation of 7A85 aluminum alloy.350−400°C is the transformation zone from dynamic recovery to dynamic recrystallization.At low temperature(≤350°C),DRV is the main mechanism,while DRX mostly occurs at high temperature(≥400°C).At this point,the sensitivity of microstructure evolution to temperature is relatively high.As the temperature increased,the average misorientation angle(θˉ_(c))increased significantly,ranging from 0.93°to 7.13°.Meanwhile,the f_(LAGBs) decreased with the highest decrease of 24%.
