scholarly journals Two-step Monte Carlo sensitivity analysis of alpha- and gamma-eigenvalues with the differential operator sampling method

2019 ◽  
Vol 133 ◽  
pp. 100-109 ◽  
Author(s):  
Toshihiro Yamamoto ◽  
Hiroki Sakamoto
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Differential Operator ◽  
Sampling Method

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.

scholarly journals GENERALIZED SENSITIVITY ANALYSIS CAPABILITY WITH THE DIFFERENTIAL OPERATOR METHOD IN RMC CODE

2021 ◽  
Vol 247 ◽  
pp. 15020
Author(s):  
Guanlin Shi ◽  
Conglong Jia ◽  
Kan Wang ◽  
Quan Cheng
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Differential Operator ◽  
Response Function ◽  
Operator Method ◽  
Monte Carlo Code ◽  
Transport Mode ◽  
Continuous Energy ◽  
Relative Standard ◽  
Monte Carlo Transport

Sensitivity analysis is an important way for us to know how the input parameters will affect the output of a system. Therefore, recently, there is an increased interest in developing sensitivity analysis methods in continuous-energy Monte Carlo Code due to the fact that Monte Carlo method can perform high-fidelity simulations of nuclear reactor. Previous studies mainly focused on developing sensitivity analysis method suitable for analyze eigenvalue. There are relatively few researches for performing sensitivity analysis of generalized response function by using continuous-energy Monte Carlo code. So, in this work, the differential operator method (DOM) has been investigated and implemented in continuous-energy Reactor Monte Carlo code (RMC) to perform sensitivity analysis of generalized response function in the form of ratios of reaction rate. The DOM implemented in RMC is based on the analog Monte Carlo transport mode and non-analog Monte Carlo transport mode. The correctness of the newly implemented method has been verified by comparing the results with those calculated by using the collision history-based method through the Jezeble and Flattop benchmark problems. In general, the results given by the DOM agree well with those obtained by the collision history-based method with an accuracy of 5%. Moreover, it is also shown that the non-analog Monte Carlo transport mode can obtain lower relative standard deviation of the sensitivity coefficients than the analog Monte Carlo transport mode.

Analysis of Pose Accuracy Reliability and Sensitivity for Six Degrees Freedom Welding Robot

2012 ◽  
Vol 271-272 ◽  
pp. 1506-1510 ◽  
Author(s):  
Jia Li ◽  
Ye Li ◽  
Meng Zhao ◽  
Shuai Chen
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Sampling Method ◽  
Joint Angle ◽  
Simulation Analysis ◽  
Joint Space ◽  
Monte Carlo Sampling ◽  
Prototype Model ◽  
Welding Robot ◽  
Manufacturing Tolerances

With the continuous development of industrial automation, robots are applied to various fields of industry increasingly, and the robot pose accuracy become an important issues. Through the establishment of the robot parameterized virtual prototype model, the error of bar length, joint angle and joint space have been taken into account, and the Monte Carlo sampling method is used to process a number of simulation analysis. The reliable probability which is given within the error limits is calculated, and finally through sensitivity analysis, the conclusion is drawn that different error factors influent the robot end error differently, which have a certain significance for the allocation of the manufacturing tolerances of the robot and trajectory planning.

Sensitivity analysis of a Monte Carlo atmospheric diffusion model

1988 ◽  
Vol 11 (1) ◽  
pp. 13-28 ◽  
Author(s):  
D. Anfossi ◽  
G. Brusasca ◽  
G. Tinarelli
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Diffusion Model ◽  
Atmospheric Diffusion

scholarly journals Drone Ground Impact Footprints with Importance Sampling: Estimation and Sensitivity Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 3871
Author(s):  
Jérôme Morio ◽  
Baptiste Levasseur ◽  
Sylvain Bertrand
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo ◽  
Importance Sampling ◽  
Loss Of Control ◽  
Minimum Volume ◽  
Multiple Importance Sampling ◽  
Impact Position ◽  
Engine Failure ◽  
Main Engine ◽  
Ground Impact

This paper addresses the estimation of accurate extreme ground impact footprints and probabilistic maps due to a total loss of control of fixed-wing unmanned aerial vehicles after a main engine failure. In this paper, we focus on the ground impact footprints that contains 95%, 99% and 99.9% of the drone impacts. These regions are defined here with density minimum volume sets and may be estimated by Monte Carlo methods. As Monte Carlo approaches lead to an underestimation of extreme ground impact footprints, we consider in this article multiple importance sampling to evaluate them. Then, we perform a reliability oriented sensitivity analysis, to estimate the most influential uncertain parameters on the ground impact position. We show the results of these estimations on a realistic drone flight scenario.

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