The present article provides supplementary information of previous works of analytic models for predicting conductivity enhancements of carbon nanotube composites. The models, though fairly simple, are able to take ac...The present article provides supplementary information of previous works of analytic models for predicting conductivity enhancements of carbon nanotube composites. The models, though fairly simple, are able to take account of the effects of conductivity anisotropy, nonstraightness, and aspect ratio of the CNT additives on the conductivity enhancement of the composite and to give predictions agreeing well with existing experimental data. The omitted detailed derivation of this model is demonstrated in the present article with a more systematical analysis, which may help with further development in this direction. Furthermore, the effects of various orientation distributions of CNTs are reported here for the first time. The information may be useful in design or fabrication technology of CNT composites for better or specified conductivities.展开更多
In this paper,we consider the statistical inference problems for the fixed effect and variance component functions in the two-way classification random effects model with skewnormal errors.Firstly,the exact test stati...In this paper,we consider the statistical inference problems for the fixed effect and variance component functions in the two-way classification random effects model with skewnormal errors.Firstly,the exact test statistic for the fixed effect is constructed.Secondly,using the Bootstrap approach and generalized approach,the one-sided hypothesis testing and interval estimation problems for the single variance component,the sum and ratio of variance components are discussed respectively.Further,the Monte Carlo simulation results indicate that the exact test statistic performs well in the one-sided hypothesis testing problem for the fixed effect.And the Bootstrap approach is better than the generalized approach in the one-sided hypothesis testing problems for variance component functions in most cases.Finally,the above approaches are applied to the real data examples of the consumer price index and value-added index of three industries to verify their rationality and effectiveness.展开更多
文摘The present article provides supplementary information of previous works of analytic models for predicting conductivity enhancements of carbon nanotube composites. The models, though fairly simple, are able to take account of the effects of conductivity anisotropy, nonstraightness, and aspect ratio of the CNT additives on the conductivity enhancement of the composite and to give predictions agreeing well with existing experimental data. The omitted detailed derivation of this model is demonstrated in the present article with a more systematical analysis, which may help with further development in this direction. Furthermore, the effects of various orientation distributions of CNTs are reported here for the first time. The information may be useful in design or fabrication technology of CNT composites for better or specified conductivities.
基金supported by National Social Science Foundation of China(21BTJ068)。
文摘In this paper,we consider the statistical inference problems for the fixed effect and variance component functions in the two-way classification random effects model with skewnormal errors.Firstly,the exact test statistic for the fixed effect is constructed.Secondly,using the Bootstrap approach and generalized approach,the one-sided hypothesis testing and interval estimation problems for the single variance component,the sum and ratio of variance components are discussed respectively.Further,the Monte Carlo simulation results indicate that the exact test statistic performs well in the one-sided hypothesis testing problem for the fixed effect.And the Bootstrap approach is better than the generalized approach in the one-sided hypothesis testing problems for variance component functions in most cases.Finally,the above approaches are applied to the real data examples of the consumer price index and value-added index of three industries to verify their rationality and effectiveness.