A new back-analysis method of ground stress is proposed with comprehensive consideration of influence of topography, geology and nonlinear physical mechanical properties of rock on ground stress. This method based on ...A new back-analysis method of ground stress is proposed with comprehensive consideration of influence of topography, geology and nonlinear physical mechanical properties of rock on ground stress. This method based on non-uniform rational B-spline (NURBS) technology provides the means to build a refined three-dimensional finite element model with more accurate meshing under complex terrain and geological conditions. Meanwhile, this method is a back-analysis of ground stress with combination of multivariable linear regression model and neural network (ANN) model. Firstly, the regression model is used to fit approximately boundary loads. Regarding the regressed loads as mean value, some sets of boundary loads with the same interval are constructed according to the principle of orthogonal design, to calculate the corresponding ground stress at the observation positions using finite element method. The results (boundary loads and the corresponding ground stress) are added to the samples for ANN training. And on this basis, an ANN model is established to implement higher precise back-analysis of initial ground stress. A practical application case shows that the relative error between the inversed ground stress and observed value is mostly less than 10 %, which can meet the need of engineering design and construction requirements.展开更多
Due to continuous process scaling, process, voltage, and temperature （PVT） parameter variations have become one of the most problematic issues in circuit design. The resulting correlations among performance metrics ...Due to continuous process scaling, process, voltage, and temperature （PVT） parameter variations have become one of the most problematic issues in circuit design. The resulting correlations among performance metrics lead to a significant parametric yield loss. Previous algorithms on parametric yield prediction are limited to predicting a single-parametric yield or performing balanced optimization for several single-parametric yields. Consequently, these methods fail to predict the multiparametric yield that optimizes multiple performance metrics simultaneously, which may result in significant accuracy loss. In this paper we suggest an efficient multi-parametric yield prediction framework, in which multiple performance metrics are considered as simultaneous constraint conditions for parametric yield prediction, to maintain the correlations among metrics. First, the framework models the performance metrics in terms of PVT parameter variations by using the adaptive elastic net （AEN） method. Then the parametric yield for a single performance metric can be predicted through the computation of the cumulative distribution function （CDF） based on the multiplication theorem and the Markov chain Monte Carlo （MCMC） method. Finally, a copula-based parametric yield prediction procedure has been developed to solve the multi-parametric yield prediction problem, and to generate an accurate yield estimate. Experimental results demonstrate that the proposed multi-parametric yield prediction framework is able to provide the designer with either an accurate value for parametric yield under specific performance limits, or a multi-parametric yield surface under all ranges of performance limits.展开更多
As multistage gear transmission systems are complex and precise, the flexibility of shaft can influence the dynamic response of system. In order to study dynamic response of the system, we build the rigid model of gea...As multistage gear transmission systems are complex and precise, the flexibility of shaft can influence the dynamic response of system. In order to study dynamic response of the system, we build the rigid model of gear system and the finite element model of the gear shaft. virtual prototype technology, and a contrast between rigid The rigid-flex coupling model is established with the model and rigid-flex coupling model is constructed. With these methods, the dynamic responses with different rotation speeds and different loading magnitudes are examined. We also analyze the influence of shaft flexibility, rotation speeds and loading magnitudes on the vibration characteristics of gear transmission systems.展开更多
基金Innovative Research Groups of the National Natural Science Foundation of China (No.51021004)National Science Foundation of China (No. 51079096)Program for New Century Excellent Talents in University (No. NCET-08-0391)
文摘A new back-analysis method of ground stress is proposed with comprehensive consideration of influence of topography, geology and nonlinear physical mechanical properties of rock on ground stress. This method based on non-uniform rational B-spline (NURBS) technology provides the means to build a refined three-dimensional finite element model with more accurate meshing under complex terrain and geological conditions. Meanwhile, this method is a back-analysis of ground stress with combination of multivariable linear regression model and neural network (ANN) model. Firstly, the regression model is used to fit approximately boundary loads. Regarding the regressed loads as mean value, some sets of boundary loads with the same interval are constructed according to the principle of orthogonal design, to calculate the corresponding ground stress at the observation positions using finite element method. The results (boundary loads and the corresponding ground stress) are added to the samples for ANN training. And on this basis, an ANN model is established to implement higher precise back-analysis of initial ground stress. A practical application case shows that the relative error between the inversed ground stress and observed value is mostly less than 10 %, which can meet the need of engineering design and construction requirements.
基金Project supposed by the Natural Science Foundation of Jiangsu Province （Nos. BK20161072, BK20150785, and BK20130877） and the National Natural Science Foundation of China （Nos. 61502234 and 71301081）
文摘Due to continuous process scaling, process, voltage, and temperature （PVT） parameter variations have become one of the most problematic issues in circuit design. The resulting correlations among performance metrics lead to a significant parametric yield loss. Previous algorithms on parametric yield prediction are limited to predicting a single-parametric yield or performing balanced optimization for several single-parametric yields. Consequently, these methods fail to predict the multiparametric yield that optimizes multiple performance metrics simultaneously, which may result in significant accuracy loss. In this paper we suggest an efficient multi-parametric yield prediction framework, in which multiple performance metrics are considered as simultaneous constraint conditions for parametric yield prediction, to maintain the correlations among metrics. First, the framework models the performance metrics in terms of PVT parameter variations by using the adaptive elastic net （AEN） method. Then the parametric yield for a single performance metric can be predicted through the computation of the cumulative distribution function （CDF） based on the multiplication theorem and the Markov chain Monte Carlo （MCMC） method. Finally, a copula-based parametric yield prediction procedure has been developed to solve the multi-parametric yield prediction problem, and to generate an accurate yield estimate. Experimental results demonstrate that the proposed multi-parametric yield prediction framework is able to provide the designer with either an accurate value for parametric yield under specific performance limits, or a multi-parametric yield surface under all ranges of performance limits.
基金the National Natural Science Foundation of China(No.71401173)
文摘As multistage gear transmission systems are complex and precise, the flexibility of shaft can influence the dynamic response of system. In order to study dynamic response of the system, we build the rigid model of gear system and the finite element model of the gear shaft. virtual prototype technology, and a contrast between rigid The rigid-flex coupling model is established with the model and rigid-flex coupling model is constructed. With these methods, the dynamic responses with different rotation speeds and different loading magnitudes are examined. We also analyze the influence of shaft flexibility, rotation speeds and loading magnitudes on the vibration characteristics of gear transmission systems.
