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High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method
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作者 Mingming Wang Linfang Qian +3 位作者 Guangsong Chen Tong Lin Junfei Shi Shijie Zhou 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第2期209-221,共13页
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
关键词 Truck-mounted howitzer Projectile motion Uncertainty quantification probability density evolution method
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A new method of formation evaluation for fractured and caved carbonate reservoirs:A case study from the Lundong area,Tarim Basin,China 被引量:7
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作者 Yang Haijun Sam Zandong Sun +4 位作者 Cai Lulu Xiao Youjun WangHaiyang Luo Chunshu Hu Hongru 《Petroleum Science》 SCIE CAS CSCD 2011年第4期446-454,共9页
The carbonate reservoirs in the Tarim Basin are characterized by low matrix-porosity,heterogeneity and anisotropy,which make it difficult to predict and evaluate these reservoirs.The reservoir formations in Lundong ar... The carbonate reservoirs in the Tarim Basin are characterized by low matrix-porosity,heterogeneity and anisotropy,which make it difficult to predict and evaluate these reservoirs.The reservoir formations in Lundong area experienced a series of diagenesis and tectonic evolution stages.And secondary storage spaces such as fractures and dissolution caves were developed while nearly all the primary pores have disappeared.Based on a summary of different types of storage spaces and their responses in conventional logs,FMI and full waveform sonic logs which are sensitive to different reservoirs,the comprehensive probability index (CPI) method is applied to evaluating the reservoirs and a standard of reservoir classification is established.By comparing the evaluation results with actual welllogging results,the method has proven to be practical for formation evaluation of carbonate reservoirs,especially for the fractured carbonate reservoirs.In reservoir fluid identification,the multivariate stepwise discriminant analysis (MSDA) method is introduced.Combining the CPI method and MSDA method,comprehensive formation evaluation has been performed for fractured and caved carbonate reservoirs in the Tarim Basin.Additionally,on the basis of secondary pore inversion results,another new method of formation evaluation is also proposed in the discussion part of this paper.Through detailed application result analysis,the method shows a promising capability for formation evaluation of complex carbonate reservoirs dominated by various secondary pores such as holes,caves,and cracks. 展开更多
关键词 Carbonate reservoir formation evaluation comprehensive probability index method discriminant analysis Tarim Basin
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A method to calculate displacement factors using SVM 被引量:5
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作者 Li Peixian Tan Zhixiang +1 位作者 Yan Lili Deng Kazhong 《Mining Science and Technology》 EI CAS 2011年第3期307-311,共5页
In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine (SVM) was established to calculate the displacement factor. The study is based on a comprehensive ... In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine (SVM) was established to calculate the displacement factor. The study is based on a comprehensive analysis of factors affecting the displacement factor, such as mechanical properties of the cover rock, the ratio of mining depth to seam thickness, dip angle of the coal seam and the thickness of loose layer. Data of 63 typical observation stations were used as a training and testing sample set. A SVM regression model of the displacement factor and the factors affecting it was established with a kernel function, an insensitive loss factor and a properly selected penalty factor. Given an accurate calculation algorithm for testing and analysis, the results show that an SVM regression model can calcu- late displacement factor precisely and reliable precision can be obtained which meets engineering requirements. The experimental results show that the method to calculation of the displacement factor, based on the SVM method, is feasible. The many factors affecting the displacement factor can be consid- ered with this method. The research provides an efficient and accurate approach for the calculation of displacement in mining subsidence orediction. 展开更多
关键词 Mining subsidence Displacement factor SVM probability integration method
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