The uncertainty importance measure of slope stability based on the moment-independent method

2019 ◽  
Vol 34 (1) ◽  
pp. 51-65 ◽  
Author(s):  
Zhaoxia Xu ◽  
Xiaoping Zhou ◽  
Qihu Qian
Keyword(s):  
Slope Stability ◽  
Independent Method ◽  
Importance Measure ◽  
The Moment ◽  
Uncertainty Importance

scholarly journals Parametric Sensitivity Analysis for Importance Measure on Failure Probability and Its Efficient Kriging Solution

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yishang Zhang ◽  
Yongshou Liu ◽  
Xufeng Yang
Keyword(s):  
Sensitivity Analysis ◽  
Failure Probability ◽  
Computational Effort ◽  
Importance Measure ◽  
Sensitivity Index ◽  
Reliability Engineering ◽  
Parametric Sensitivity ◽  
Distribution Parameters ◽  
The Moment ◽  
Sensitivity Indicator

The moment-independent importance measure (IM) on the failure probability is important in system reliability engineering, and it is always influenced by the distribution parameters of inputs. For the purpose of identifying the influential distribution parameters, the parametric sensitivity of IM on the failure probability based on local and global sensitivity analysis technology is proposed. Then the definitions of the parametric sensitivities of IM on the failure probability are given, and their computational formulae are derived. The parametric sensitivity finds out how the IM can be changed by varying the distribution parameters, which provides an important reference to improve or modify the reliability properties. When the sensitivity indicator is larger, the basic distribution parameter becomes more important to the IM. Meanwhile, for the issue that the computational effort of the IM and its parametric sensitivity is usually too expensive, an active learning Kriging (ALK) solution is established in this study. Two numerical examples and two engineering examples are examined to demonstrate the significance of the proposed parametric sensitivity index, as well as the efficiency and precision of the calculation method.

The trajectory importance measure of the shaping machine under stochastic excitation

2011 ◽  
Vol 226 (3) ◽  
pp. 808-815 ◽  
Author(s):  
L J Cui ◽  
Z Z Lu ◽  
C C Zhou
Keyword(s):  
Failure Probability ◽  
Computational Efficiency ◽  
Importance Measure ◽  
Stochastic Excitation ◽  
Input Uncertainty ◽  
Dynamic Reliability ◽  
Probability Density Evolution Method ◽  
Output Uncertainty ◽  
The Moment ◽  
Probability Density Evolution

Two trajectory importance measures, the trajectory importance measure based on variance and the moment-independent trajectory importance measure, are proposed to represent the time-variant effects of input uncertainty on the output uncertainty of the shaping machine under stochastic excitation in its work stroke, respectively. At the same time, the trajectory importance measure based on the failure probability is proposed to reflect the contribution of the input uncertainty on the dynamic reliability of the mechanism. These three trajectory importance measures provide different references to improve the performance and reliability of the mechanism from the time-variant perspective. As the probability density evolution method (PDEM) is employed to solve the proposed trajectory importance measures, it can improve the computational efficiency largely without losing precision. Results of the shaping mechanism illustrate the feasibility of the proposed trajectory importance measures and the veracity of the PDEM in solving the lathe mechanism.

A Hybrid Qualitative/Quantitative Uncertainty Importance Assessment Approach: Applications to Thermal-Hydraulics System Codes Calculations

2009 ◽  
Author(s):  
Mohammad Pourgol-Mohammad ◽  
Kamran Sepanloo
Keyword(s):  
Standard Deviation ◽  
Epistemic Uncertainty ◽  
Computational Time ◽  
Special Treatment ◽  
Importance Measure ◽  
Output Variable ◽  
Total Uncertainty ◽  
Uncertainty Range ◽  
Importance Assessment ◽  
Uncertainty Importance

Uncertainty importance is used to rank sources of uncertainty in the input variables for their degree of contribution to the uncertainty of the output variable(s). Such ranking is used to plan in reducing epistemic uncertainty in the output variable(s). In application to Thermal-Hydraulic calculations using RELAP5, TRAC and TRACE codes involving uncertainty, uncertainty ranking can be used to confirm the results of Phenomena Identification and Ranking Table (PIRT) utilized in available uncertainty quantification methodologies. Several methodologies have been developed to address uncertainty importance assessment. Existing methodologies for uncertainty importance are not practical for some applications such as some Thermal-Hydraulic calculations due to required computational time and resources. A new efficient uncertainty importance ranking method is proposed as part of a broader research conducted by the authors for comprehensive TH code uncertainty assessment. Given the computational complexities of the TH codes, the proposed uncertainty importance measure is defined in multiples of standard deviation (xσ) changes in a given input parameter or variable over the resulting changes in the standard deviation of output variable (such as a Figure of Merit). The total uncertainty range resulted from propagation of uncertainties is obtained from several available methodologies e.g., CSAU, GRS, UMAE and the recently proposed integrated methodology IMTHUA, proposed by the author. There are some difficulties in assessment of non-linearity of some input changes vs. variations in the output variables, which require special treatment. Different levels of input change (multiples of standard variation) are devised for accurate ranking of uncertainty contributors. Comparing the output change as a fraction of the overall uncertainty range will result in a ranking index to show the contribution of each uncertainty source. In this paper a brief overview of the importance analysis as well as the difference between uncertainty-importance vs. importance uncertainty will be first given. Current methodologies for uncertainty importance will be discussed and their applicability to TH analysis will be discussed. A description of the proposed methodology, along with an example of its application to LOFT LBLOCA uncertain parameters will be discussed.

scholarly journals The Moment-Independent Importance Analysis of Structural Seismic Requirements Based on Orthogonal Polynomial Estimation

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhaoxia Xu ◽  
Xiuzhen Wang
Keyword(s):  
Elastic Modulus ◽  
Yield Strength ◽  
Orthogonal Polynomial ◽  
Damping Ratio ◽  
Independent Method ◽  
Structural Quality ◽  
Seismic Demands ◽  
Importance Analysis ◽  
Polynomial Estimation ◽  
The Moment

The structural damping ratio, structural quality, yield strength, and elastic modulus of section steel, compressive strength, elastic modulus of concrete, yield strength, and elastic modulus of steel bars play important roles in the stability of the steel-reinforced concrete (SRC) frame structure, which are usually uncertain. However, their importance influence on the different seismic demands of SRC is rarely investigated simultaneously. In order to investigate the effects of the above parameters on four seismic demands (i.e., the top displacement, the maximum floor acceleration, the base shear force, and the maximum interstory displacement angle) of SRC frame structures, the orthogonal polynomial estimation method is first applied to the importance analysis of structural seismic demand based on the moment-independent method. Two engineering examples are performed to verify the accuracy and efficiency of the proposed method. The results have the characteristics of fast convergence and are in good agreement with those obtained by the moment-independent method based on kernel density estimation. The variance importance index based on Monte Carlo (MC) method is also calculated for comparison. The influence of each random variable on the four structural seismic demands is basically the same. Therefore, the accuracy and efficiency of the proposed method are proved sufficiently.

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