As an alternative or complementary approach to the classical probability theory,the ability of the evidence theory in uncertainty quantification（UQ） analyses is subject of intense research in recent years.Two state-...As an alternative or complementary approach to the classical probability theory,the ability of the evidence theory in uncertainty quantification（UQ） analyses is subject of intense research in recent years.Two state-of-the-art numerical methods,the vertex method and the sampling method,are commonly used to calculate the resulting uncertainty based on the evidence theory.The vertex method is very effective for the monotonous system,but not for the non-monotonous one due to its high computational errors.The sampling method is applicable for both systems.But it always requires a high computational cost in UQ analyses,which makes it inefficient in most complex engineering systems.In this work,a computational intelligence approach is developed to reduce the computational cost and improve the practical utility of the evidence theory in UQ analyses.The method is demonstrated on two challenging problems proposed by Sandia National Laboratory.Simulation results show that the computational efficiency of the proposed method outperforms both the vertex method and the sampling method without decreasing the degree of accuracy.Especially,when the numbers of uncertain parameters and focal elements are large,and the system model is non-monotonic,the computational cost is five times less than that of the sampling method.展开更多
ART Ⅱ网络以模式的相似性量度值为基础,能够对动态的输入模式样本进行自适应的聚类和识别,然而标准的ART Ⅱ网络在输入数据处理过程中,忽略了样本数据中的负数信息和幅值信息,造成信号畸变和"同相位不可分"问题,在权值调整...ART Ⅱ网络以模式的相似性量度值为基础,能够对动态的输入模式样本进行自适应的聚类和识别,然而标准的ART Ⅱ网络在输入数据处理过程中,忽略了样本数据中的负数信息和幅值信息,造成信号畸变和"同相位不可分"问题,在权值调整过程中,聚类中心发生移动,容易造成"模式漂移"现象。针对上述问题结合相关文献提出了引入非线性函数对输入数据进行变换的方法解决"同相位不可分"问题,用待测数据与同一模式类中有限数据的欧氏距离与限定值进行比较实现聚类判定,抑制"模式漂移"现象。用Matlab仿真表明,改进算法性能优于标准算法。展开更多
炸药运输环境的要求较高也较为复杂,可能会有跌落、撞击等意外风险的发生,使得炸药内部形成局部损伤,引起燃烧、爆炸等后果。但炸药撞击过程中的不确定性使装药撞击点火也存在不确定性,从而导致现有的确定性定量分析结果往往过于保守或...炸药运输环境的要求较高也较为复杂,可能会有跌落、撞击等意外风险的发生,使得炸药内部形成局部损伤,引起燃烧、爆炸等后果。但炸药撞击过程中的不确定性使装药撞击点火也存在不确定性,从而导致现有的确定性定量分析结果往往过于保守或偏离理想状态。为此,研究了炸药爆炸过程中不确定性参数对装药撞击的影响,采用ANSYS/LS-DYNA,建立能够反映装药撞击点火的有限元模型,同时依据“裕量和不确定性量化(quantification of margins and uncertainties,QMU)”概念,提出了基于证据理论的装药撞击点火“最大动内能和”QMU方法,建立了装药撞击点火最大动内能和的响应面函数,从而获得“最大动内能和”的概率上下界。最后,基于QMU理论,确定了装药撞击点火模型“最大动内能和”在不同置信水平下的置信因子,用以评价装药撞击点火结构的安全性。该研究能为排查炸药撞击产生的安全隐患提供理论依据,亦为此后炸药运输的安全性设计提供基础保障。展开更多
基金supported by the Advanced Research of National Defense Foundation of China(426010501)
文摘As an alternative or complementary approach to the classical probability theory,the ability of the evidence theory in uncertainty quantification（UQ） analyses is subject of intense research in recent years.Two state-of-the-art numerical methods,the vertex method and the sampling method,are commonly used to calculate the resulting uncertainty based on the evidence theory.The vertex method is very effective for the monotonous system,but not for the non-monotonous one due to its high computational errors.The sampling method is applicable for both systems.But it always requires a high computational cost in UQ analyses,which makes it inefficient in most complex engineering systems.In this work,a computational intelligence approach is developed to reduce the computational cost and improve the practical utility of the evidence theory in UQ analyses.The method is demonstrated on two challenging problems proposed by Sandia National Laboratory.Simulation results show that the computational efficiency of the proposed method outperforms both the vertex method and the sampling method without decreasing the degree of accuracy.Especially,when the numbers of uncertain parameters and focal elements are large,and the system model is non-monotonic,the computational cost is five times less than that of the sampling method.
文摘炸药运输环境的要求较高也较为复杂,可能会有跌落、撞击等意外风险的发生,使得炸药内部形成局部损伤,引起燃烧、爆炸等后果。但炸药撞击过程中的不确定性使装药撞击点火也存在不确定性,从而导致现有的确定性定量分析结果往往过于保守或偏离理想状态。为此,研究了炸药爆炸过程中不确定性参数对装药撞击的影响,采用ANSYS/LS-DYNA,建立能够反映装药撞击点火的有限元模型,同时依据“裕量和不确定性量化(quantification of margins and uncertainties,QMU)”概念,提出了基于证据理论的装药撞击点火“最大动内能和”QMU方法,建立了装药撞击点火最大动内能和的响应面函数,从而获得“最大动内能和”的概率上下界。最后,基于QMU理论,确定了装药撞击点火模型“最大动内能和”在不同置信水平下的置信因子,用以评价装药撞击点火结构的安全性。该研究能为排查炸药撞击产生的安全隐患提供理论依据,亦为此后炸药运输的安全性设计提供基础保障。
