Monte Carlo sensitivity analysis method for the effective delayed neutron fraction with the differential operator sampling method

2020 ◽  
Vol 140 ◽  
pp. 107108
Author(s):  
Toshihiro Yamamoto ◽  
Hiroki Sakamoto
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Differential Operator ◽  
Sampling Method ◽  
Analysis Method ◽  
Delayed Neutron ◽  
Sensitivity Analysis Method

A Fast Approximate Method for Reliability Sensitivity Based on Markov Chain Simulation

2007 ◽  
Vol 353-358 ◽  
pp. 1005-1008
Author(s):  
Xiu Kai Yuan ◽  
Zhen Zhou Lu
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Markov Chain ◽  
Weighted Regression ◽  
Analysis Method ◽  
Reliability Sensitivity ◽  
Reliability Sensitivity Analysis ◽  
Failure Region ◽  
Sensitivity Analysis Method ◽  
Distribution Parameters

On the basis of Markov chain simulation, an efficient method is presented to analyze reliability sensitivity of structure. In the presented method, Markov chain is employed to draw the samples distributed in the failure region, and these samples are fitted in a form of hyperplane by the weighted regression. By use of the regressed hyperplane, it is convenient to complete the sensitivities of the failure probability with respect to the distribution parameters of basic random variables by the available method. The presented method is applied to some examples to validate its accuracy and efficiency. The obtained results show that the presented reliability sensitivity analysis method is far more efficient than Monte Carlo based method.

A Feasible Delay Margin Sensitivity Analysis Method

2021 ◽  
pp. 1-1
Author(s):  
Chongtao Li ◽  
Yulei Cao ◽  
Chao Duan ◽  
Kun Zhang
Keyword(s):  
Sensitivity Analysis ◽  
Analysis Method ◽  
Sensitivity Analysis Method ◽  
Delay Margin

Efficient Sensitivity Analysis for Multibody Dynamics Systems Using an Iterative Steps Method With Application in Topology Optimization

2011 ◽  
Author(s):  
Guang Dong ◽  
Zheng-Dong Ma ◽  
Gregory Hulbert ◽  
Noboru Kikuchi ◽  
Sudhakar Arepally ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Topology Optimization ◽  
Multibody Dynamics ◽  
Optimization Problem ◽  
Finite Difference Methods ◽  
Analysis Method ◽  
Topology Optimization Problem ◽  
Design Variables ◽  
Sensitivity Analysis Method ◽  
Rotational Motions

Efficient and reliable sensitivity analyses are critical for topology optimization, especially for multibody dynamics systems, because of the large number of design variables and the complexities and expense in solving the state equations. This research addresses a general and efficient sensitivity analysis method for topology optimization with design objectives associated with time dependent dynamics responses of multibody dynamics systems that include nonlinear geometric effects associated with large translational and rotational motions. An iterative sensitivity analysis relation is proposed, based on typical finite difference methods for the differential algebraic equations (DAEs). These iterative equations can be simplified for specific cases to obtain more efficient sensitivity analysis methods. Since finite difference methods are general and widely used, the iterative sensitivity analysis is also applicable to various numerical solution approaches. The proposed sensitivity analysis method is demonstrated using a truss structure topology optimization problem with consideration of the dynamic response including large translational and rotational motions. The topology optimization problem of the general truss structure is formulated using the SIMP (Simply Isotropic Material with Penalization) assumption for the design variables associated with each truss member. It is shown that the proposed iterative steps sensitivity analysis method is both reliable and efficient.

Research on Monte Carlo Perturbation Calculation Methods Applied in Reactor Physics

2009 ◽  
Author(s):  
Ze-guang Li ◽  
Kan Wang ◽  
Gang-lin Yu
Keyword(s):  
Monte Carlo ◽  
Differential Operator ◽  
Sampling Method ◽  
Perturbation Methods ◽  
Calculation Model ◽  
Perturbation Calculation ◽  
Reactor Physics ◽  
Tracking Method ◽  
Monte Carlo Techniques ◽  
Sensitivity Studies

In the reactor design and analysis, there is often a need to calculate the effects caused by perturbations of temperature, components and even structure of reactors on reactivity. And in sensitivity studies, uncertainty analysis of target quantities and unclear data adjustment, perturbation calculations are also widely used. To meet the need of different types of reactors (complex, multidimensional systems), Monte Carlo perturbation methods have been developed. In this paper, several kinds of perturbation methods are investigated. Specially, differential operator sampling method and correlated tracking method are discussed in details. MCNP’s perturbation calculation capability is discussed by calculating certain problems, from which some conclusions are obtained on the capabilities of the differential operator sampling method used in the perturbation calculation model of MCNP. Also, a code using correlated tracking method has been developed to solve certain problems with cross-section changes, and the results generated by this code agree with the results generated by straightforward Monte Carlo techniques.

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