scholarly journals Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6420
Author(s):  
Soha Saad ◽  
Florence Ossart ◽  
Jean Bigeon ◽  
Etienne Sourdille ◽  
Harold Gance
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Supply Voltage ◽  
Nonlinear Models ◽  
System Optimization ◽  
Incident Management ◽  
Test Case ◽  
Technical Standards ◽  
Speed Reduction ◽  
Global Sensitivity

The adjustment of rail traffic in the event of an electrical infrastructure disruption presents an important decision-making process for the smooth operation of the network. Railway systems are complex, and their analysis relies on expensive simulations, which makes incident management difficult. This paper proposes the use of sensitivity analysis in order to evaluate the influence of different traffic adjustment actions (e.g., spacing between trains and speed reduction) on the train supply voltage, which must never drop below the critical value prescribed by technical standards. Three global sensitivity analysis methods dedicated to black box, multivariate, nonlinear models are considered: generalized Sobol indices, energy distance-based indices, and regional sensitivity analysis. The three methods are applied to a simple traffic rescheduling test case and give similar results, but at different costs. Regional sensitivity analysis appears to be the most suitable method for the present application: it is easy to implement, rather fast, and accounts for constraints on the system output (a key feature for electrical incident management). The application of this method to a test case representative of a real rescheduling problem shows that it provides the information needed by the traffic manager to reschedule traffic in an efficient way. The same type of approach can be used for any power system optimization problem with the same characteristics.

Investigation of the uncertainty of the in-plane mechanical properties of composite laminates

2011 ◽  
Vol 226 (7) ◽  
pp. 1739-1750 ◽  
Author(s):  
Tian Longfei ◽  
Lu Zhenzhou ◽  
Hao Wenrui
Keyword(s):  
Mechanical Properties ◽  
Sensitivity Analysis ◽  
Composite Laminates ◽  
Global Sensitivity Analysis ◽  
Nonlinear Models ◽  
Analysis Method ◽  
Global Sensitivity ◽  
Response Variance ◽  
Sensitivity Analysis Method ◽  
Input Variables

The uncertainty of the in-plane mechanical properties of the laminate used in an aircraft wing structure is investigated. Global sensitivity analysis is used to identify the source of the uncertainties of the response performance. Due to the limitations of the existing global sensitivity analysis method for nonlinear models with correlated input variables, a new one using nonlinear regression is proposed. Furthermore, a contribution matrix is defined for engineering convenience. Two nonlinear numerical examples are employed in this article to demonstrate the ability of the proposed global sensitivity analysis method. After applying the proposed global sensitivity analysis method to the laminate model, the contribution matrices are obtained; from these matrices, researchers can identify the dominant variance contributions that contribute the most to the response variance. Factor analysis is then employed to analyze the global sensitivity analysis results and determine the most efficient methods to decrease the variances of the in-plane elastic constants. Monte Carlo simulation is used to demonstrate the efficiency of the methods in decreasing the variances.

Global sensitivity analysis of the ADAM dispersion module: Jack Rabbit II test case

2020 ◽  
Vol 240 ◽  
pp. 117586
Author(s):  
Luciano Fabbri ◽  
Maureen Heraty Wood ◽  
Ivano Azzini ◽  
Rossana Rosati
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Test Case ◽  
Global Sensitivity ◽  
Dispersion Module

scholarly journals Time-Dependent Global Sensitivity Analysis for Long-Term Degeneracy Model Using Polynomial Chaos

2014 ◽  
Vol 6 ◽  
pp. 719825 ◽  
Author(s):  
Jianbin Guo ◽  
Shaohua Du ◽  
Yao Wang ◽  
Shengkui Zeng
Keyword(s):  
Sensitivity Analysis ◽  
Polynomial Chaos ◽  
Global Sensitivity Analysis ◽  
Time Dependent ◽  
Accurate Information ◽  
Test Case ◽  
Sobol Indices ◽  
Global Sensitivity ◽  
Mechanism Model

Global sensitivity is used to quantify the influence of uncertain model inputs on the output variability of static models in general. However, very few approaches can be applied for the sensitivity analysis of long-term degeneracy models, as far as time-dependent reliability is concerned. The reason is that the static sensitivity may not reflect the completed sensitivity during the entire life circle. This paper presents time-dependent global sensitivity analysis for long-term degeneracy models based on polynomial chaos expansion (PCE). Sobol’ indices are employed as the time-dependent global sensitivity since they provide accurate information on the selected uncertain inputs. In order to compute Sobol’ indices more efficiently, this paper proposes a moving least squares (MLS) method to obtain the time-dependent PCE coefficients with acceptable simulation effort. Then Sobol’ indices can be calculated analytically as a postprocessing of the time-dependent PCE coefficients with almost no additional cost. A test case is used to show how to conduct the proposed method, then this approach is applied to an engineering case, and the time-dependent global sensitivity is obtained for the long-term degeneracy mechanism model.

Sign in / Sign up

Export Citation Format

Share Document