This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is establi...This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.展开更多
概率密度演化方法(probability density evolution equation,PDEM)为非线性随机结构的动力响应分析提供了新的途径.通过PDEM获得结构响应概率密度函数(probability density function,PDF)的关键步骤是求解广义概率密度演化方程(generali...概率密度演化方法(probability density evolution equation,PDEM)为非线性随机结构的动力响应分析提供了新的途径.通过PDEM获得结构响应概率密度函数(probability density function,PDF)的关键步骤是求解广义概率密度演化方程(generalized probability density evolution equation,GDEE).对于GDEE的求解通常采用有限差分法,然而,由于GDEE是初始条件间断的变系数一阶双曲偏微分方程,通过有限差分法求解GDEE可能会面临网格敏感性问题、数值色散和数值耗散现象.文章从全局逼近的角度出发,基于Chebyshev拟谱法为GDEE构造了全局插值格式,解决了数值色散、数值耗散以及网格敏感性问题.考虑GDEE的系数在每个时间步长均为常数,推导了GDEE在每一个时间步长内时域上的序列矩阵指数解.由于序列矩阵指数解形式上是解析的,从而很好地克服了数值稳定性问题.两个数值算例表明,通过Chebyshev拟谱法结合时域的序列矩阵指数解求解GDEE得到的结果与精确解以及Monte Carlo模拟的结果非常吻合,且数值耗散和数值色散现象几乎可以忽略.此外,拟谱法具有高效的收敛性且序列矩阵指数解不受CFL (Courant-Friedrichs-Lewy)条件的限制,因此该方法具有良好的数值稳定性和计算效率.展开更多
在装配整体式剪力墙结构中,由于套筒灌浆连接的质量具有一定的随机性,势必影响结构的竖向连接性能和结构抗震性能。根据不同缺陷程度的套筒灌浆拉拔试验,建立了一套等效套筒灌浆缺陷连接承载力模型,并基于某实际工程结构,建立了装配整...在装配整体式剪力墙结构中,由于套筒灌浆连接的质量具有一定的随机性,势必影响结构的竖向连接性能和结构抗震性能。根据不同缺陷程度的套筒灌浆拉拔试验,建立了一套等效套筒灌浆缺陷连接承载力模型,并基于某实际工程结构,建立了装配整体式剪力墙结构有限元模型。通过考虑灌浆缺陷的随机性,赋予连接接头相应缺陷程度的力学连接性能,来反映套筒灌浆中可能存在的缺陷。通过非线性有限元分析并结合概率密度演化方法(probability density evolution method,PDEM)进行了结构随机非线性反应分析和可靠度评估。结果表明:在动力作用下,结构非线性与随机性具有明显的耦合效应;缺陷的随机性会随着时间的推移,逐渐放大对结构响应的影响;在不同的安全域内,结构的整体可靠度将存在较大的差异。展开更多
提出了考虑多重不确定性的光伏支撑体系(Photovoltaic Support System,PSS)随机动力可靠性分析方法。首先,构建了基于概率密度演化理论(Probability Density Evolution Method,PDEM)的光伏支撑体系可靠性分析模型,包括概率守恒方程、基...提出了考虑多重不确定性的光伏支撑体系(Photovoltaic Support System,PSS)随机动力可靠性分析方法。首先,构建了基于概率密度演化理论(Probability Density Evolution Method,PDEM)的光伏支撑体系可靠性分析模型,包括概率守恒方程、基本控制方程和密度演化方程;然后,建立了光伏支撑体系的有限元分析模型,包括结构受力模型、荷载组合形式、网格划分算法等。仿真模型中考虑了结构所受荷载与结构本身的随机性,共计6个随机变量和44个代表点。为提升算法分析效率,提出了Abaqus⁃PDEM的联合仿真算法,仿真分析表明,光伏支撑体系的失效模式主要为应力控制和位移控制两种,后者影响更为明显,基本荷载组合工况下的可靠度为0.928。随着风力等级的提高,结构可靠性逐渐降低,在高风速区间(大于40 m/s),结构本身的不确定性会高估结构的可靠性水平,在设计中应予以关注。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
Traditional track dynamic geometric state(TDGS)simulation incurs substantial computational burdens,posing challenges for developing reliability assessment approach that accounts for TDGS.To overcome these,firstly,a si...Traditional track dynamic geometric state(TDGS)simulation incurs substantial computational burdens,posing challenges for developing reliability assessment approach that accounts for TDGS.To overcome these,firstly,a simulation-based TDGS model is established,and a surrogate-based model,grid search algorithm-particle swarm optimization-genetic algorithm-multi-output least squares support vector regression,is established.Among them,hyperparameter optimization algorithm’s effectiveness is confirmed through test functions.Subsequently,an adaptive surrogate-based probability density evolution method(PDEM)considering random track geometry irregularity(TGI)is developed.Finally,taking curved train-steel spring floating slab track-U beam as case study,the surrogate-based model trained on simulation datasets not only shows accuracy in both time and frequency domains,but also surpasses existing models.Additionally,the adaptive surrogate-based PDEM shows high accuracy and efficiency,outperforming Monte Carlo simulation and simulation-based PDEM.The reliability assessment shows that the TDGS part peak management indexes,left/right vertical dynamic irregularity,right alignment dynamic irregularity,and track twist,have reliability values of 0.9648,0.9918,0.9978,and 0.9901,respectively.The TDGS mean management index,i.e.,track quality index,has reliability value of 0.9950.These findings show that the proposed framework can accurately and efficiently assess the reliability of curved low-stiffness track-viaducts,providing a theoretical basis for the TGI maintenance.展开更多
基金the National Natural Science Foundation of China(Grant No.11472137).
文摘This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.
文摘概率密度演化方法(probability density evolution equation,PDEM)为非线性随机结构的动力响应分析提供了新的途径.通过PDEM获得结构响应概率密度函数(probability density function,PDF)的关键步骤是求解广义概率密度演化方程(generalized probability density evolution equation,GDEE).对于GDEE的求解通常采用有限差分法,然而,由于GDEE是初始条件间断的变系数一阶双曲偏微分方程,通过有限差分法求解GDEE可能会面临网格敏感性问题、数值色散和数值耗散现象.文章从全局逼近的角度出发,基于Chebyshev拟谱法为GDEE构造了全局插值格式,解决了数值色散、数值耗散以及网格敏感性问题.考虑GDEE的系数在每个时间步长均为常数,推导了GDEE在每一个时间步长内时域上的序列矩阵指数解.由于序列矩阵指数解形式上是解析的,从而很好地克服了数值稳定性问题.两个数值算例表明,通过Chebyshev拟谱法结合时域的序列矩阵指数解求解GDEE得到的结果与精确解以及Monte Carlo模拟的结果非常吻合,且数值耗散和数值色散现象几乎可以忽略.此外,拟谱法具有高效的收敛性且序列矩阵指数解不受CFL (Courant-Friedrichs-Lewy)条件的限制,因此该方法具有良好的数值稳定性和计算效率.
文摘在装配整体式剪力墙结构中,由于套筒灌浆连接的质量具有一定的随机性,势必影响结构的竖向连接性能和结构抗震性能。根据不同缺陷程度的套筒灌浆拉拔试验,建立了一套等效套筒灌浆缺陷连接承载力模型,并基于某实际工程结构,建立了装配整体式剪力墙结构有限元模型。通过考虑灌浆缺陷的随机性,赋予连接接头相应缺陷程度的力学连接性能,来反映套筒灌浆中可能存在的缺陷。通过非线性有限元分析并结合概率密度演化方法(probability density evolution method,PDEM)进行了结构随机非线性反应分析和可靠度评估。结果表明:在动力作用下,结构非线性与随机性具有明显的耦合效应;缺陷的随机性会随着时间的推移,逐渐放大对结构响应的影响;在不同的安全域内,结构的整体可靠度将存在较大的差异。
文摘提出了考虑多重不确定性的光伏支撑体系(Photovoltaic Support System,PSS)随机动力可靠性分析方法。首先,构建了基于概率密度演化理论(Probability Density Evolution Method,PDEM)的光伏支撑体系可靠性分析模型,包括概率守恒方程、基本控制方程和密度演化方程;然后,建立了光伏支撑体系的有限元分析模型,包括结构受力模型、荷载组合形式、网格划分算法等。仿真模型中考虑了结构所受荷载与结构本身的随机性,共计6个随机变量和44个代表点。为提升算法分析效率,提出了Abaqus⁃PDEM的联合仿真算法,仿真分析表明,光伏支撑体系的失效模式主要为应力控制和位移控制两种,后者影响更为明显,基本荷载组合工况下的可靠度为0.928。随着风力等级的提高,结构可靠性逐渐降低,在高风速区间(大于40 m/s),结构本身的不确定性会高估结构的可靠性水平,在设计中应予以关注。
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Project(52072412)supported by the National Natural Science Foundation of China。
文摘Traditional track dynamic geometric state(TDGS)simulation incurs substantial computational burdens,posing challenges for developing reliability assessment approach that accounts for TDGS.To overcome these,firstly,a simulation-based TDGS model is established,and a surrogate-based model,grid search algorithm-particle swarm optimization-genetic algorithm-multi-output least squares support vector regression,is established.Among them,hyperparameter optimization algorithm’s effectiveness is confirmed through test functions.Subsequently,an adaptive surrogate-based probability density evolution method(PDEM)considering random track geometry irregularity(TGI)is developed.Finally,taking curved train-steel spring floating slab track-U beam as case study,the surrogate-based model trained on simulation datasets not only shows accuracy in both time and frequency domains,but also surpasses existing models.Additionally,the adaptive surrogate-based PDEM shows high accuracy and efficiency,outperforming Monte Carlo simulation and simulation-based PDEM.The reliability assessment shows that the TDGS part peak management indexes,left/right vertical dynamic irregularity,right alignment dynamic irregularity,and track twist,have reliability values of 0.9648,0.9918,0.9978,and 0.9901,respectively.The TDGS mean management index,i.e.,track quality index,has reliability value of 0.9950.These findings show that the proposed framework can accurately and efficiently assess the reliability of curved low-stiffness track-viaducts,providing a theoretical basis for the TGI maintenance.
