In this paper, we are interested to find the most sensitive parameter, local and global stability of ovarian tumor growth model. For sensitivity analysis, we use Latin Hypercube Sampling (LHS) method to generate sampl...In this paper, we are interested to find the most sensitive parameter, local and global stability of ovarian tumor growth model. For sensitivity analysis, we use Latin Hypercube Sampling (LHS) method to generate sample points and Partial Rank Correlation Coefficient (PRCC) method, uses those sample points to find out which parameters are important for the model. Based on our findings, we suggest some treatment strategies. We investigate the sensitivity of the parameters for tumor volume, <em>y</em>, cell nutrient density, <em>Q</em> and maximum tumor size, <em>ymax</em>. We also use Scatter Plot method using LHS samples to show the consistency of the results obtained by using PRCC. Moreover, we discuss the qualitative analysis of ovarian tumor growth model investigating the local and global stability.展开更多
With rigorous dynamic performance of mechanical products,it is important to identify dynamic parameters exactly.In this paper,a response surface plotting method is proposed and it can be applied to identify the dynami...With rigorous dynamic performance of mechanical products,it is important to identify dynamic parameters exactly.In this paper,a response surface plotting method is proposed and it can be applied to identify the dynamic parameters of some nonlinear systems.The method is based on the principle of harmonic balance method(HBM).The nonlinear vibration system behaves linearly under the steady-state response amplitude,which presents the equivalent stiffness and damping coefficient.The response surface plot is over two-dimensional space,which utilizes excitation as the vertical axis and the frequency as the horizontal axis.It can be applied to observe the output vibration response data.The modal parameters are identified by the response surface plot as linearity for different excitation levels,and they are converted into equivalent stiffness and damping coefficient for each resonant response.Finally,the HBM with first-order expansion is utilized for identification of stiffness and damping coefficient of nonlinear systems.The classical nonlinear systems are applied in the numerical simulation as the example,which is used to verify its effectiveness and accuracy.An application of this technique for nonlinearity identification by experimental setup is also illustrated.展开更多
文摘In this paper, we are interested to find the most sensitive parameter, local and global stability of ovarian tumor growth model. For sensitivity analysis, we use Latin Hypercube Sampling (LHS) method to generate sample points and Partial Rank Correlation Coefficient (PRCC) method, uses those sample points to find out which parameters are important for the model. Based on our findings, we suggest some treatment strategies. We investigate the sensitivity of the parameters for tumor volume, <em>y</em>, cell nutrient density, <em>Q</em> and maximum tumor size, <em>ymax</em>. We also use Scatter Plot method using LHS samples to show the consistency of the results obtained by using PRCC. Moreover, we discuss the qualitative analysis of ovarian tumor growth model investigating the local and global stability.
文摘With rigorous dynamic performance of mechanical products,it is important to identify dynamic parameters exactly.In this paper,a response surface plotting method is proposed and it can be applied to identify the dynamic parameters of some nonlinear systems.The method is based on the principle of harmonic balance method(HBM).The nonlinear vibration system behaves linearly under the steady-state response amplitude,which presents the equivalent stiffness and damping coefficient.The response surface plot is over two-dimensional space,which utilizes excitation as the vertical axis and the frequency as the horizontal axis.It can be applied to observe the output vibration response data.The modal parameters are identified by the response surface plot as linearity for different excitation levels,and they are converted into equivalent stiffness and damping coefficient for each resonant response.Finally,the HBM with first-order expansion is utilized for identification of stiffness and damping coefficient of nonlinear systems.The classical nonlinear systems are applied in the numerical simulation as the example,which is used to verify its effectiveness and accuracy.An application of this technique for nonlinearity identification by experimental setup is also illustrated.
