Application of multiplicative dimensional reduction method for uncertainty quantification and sensitivity analysis of MEMS electrostatic actuators

2017 ◽  
Vol 76-77 ◽  
pp. 619-625
Author(s):  
Pham Luu Trung Duong ◽  
Trong Toan Tran ◽  
Nagarajan Raghavan
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Dimensional Reduction ◽  
Reduction Method ◽  
Electrostatic Actuators ◽  
Dimensional Reduction Method

The quadratic dimensional reduction method for parameter identification

2019 ◽  
Vol 73 ◽  
pp. 425-436 ◽  
Author(s):  
Matthew Poole ◽  
Rua Murray ◽  
Shaun M. Davidson ◽  
Paul D. Docherty
Keyword(s):  
Parameter Identification ◽  
Dimensional Reduction ◽  
Reduction Method ◽  
Dimensional Reduction Method

Dual mixed refrigerant LNG process: Uncertainty quantification and dimensional reduction sensitivity analysis

2019 ◽  
Vol 250 ◽  
pp. 1446-1456 ◽  
Author(s):  
Muhammad Abdul Qyyum ◽  
Pham Luu Trung Duong ◽  
Le Quang Minh ◽  
Sanggyu Lee ◽  
Moonyong Lee
Keyword(s):  
Sensitivity Analysis ◽  
Uncertainty Quantification ◽  
Dimensional Reduction ◽  
Process Uncertainty

Computationally Efficient Reliability Analysis of Mechanisms Based on a Multiplicative Dimensional Reduction Method

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Xufang Zhang ◽  
Mahesh D. Pandey ◽  
Yimin Zhang
Keyword(s):  
Reliability Analysis ◽  
Dimensional Reduction ◽  
System Reliability ◽  
Reduction Method ◽  
Maximum Output ◽  
Computationally Efficient ◽  
Output Error ◽  
System Reliability Analysis ◽  
Dimensional Reduction Method ◽  
Fractional Moments

The paper presents a computationally efficient method for system reliability analysis of mechanisms. The reliability is defined as the probability that the output error remains within a specified limit in the entire target trajectory of the mechanism. This mechanism reliability problem is formulated as a series system reliability analysis that can be solved using the distribution of maximum output error. The extreme event distribution is derived using the principle maximum entropy (MaxEnt) along with the constraints specified in terms of fractional moments. To optimize the computation of fractional moments of a multivariate response function, a multiplicative form of dimensional reduction method (M-DRM) is developed. The main benefit of the proposed approach is that it provides full probability distribution of the maximal output error from a very few evaluations of the trajectory of mechanism. The proposed method is illustrated by analyzing the system reliability analysis of two planar mechanisms. Examples presented in the paper show that the results of the proposed method are fairly accurate as compared with the benchmark results obtained from the Monte Carlo simulations.

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