Hybrid RPT Method On Double-Heterogeneous System Containing Dispersed Fuel Particles and Burnable Poison Particles

2021 ◽  
Author(s):  
Lei Lou ◽  
Xiaoming Chai ◽  
Dong Yao ◽  
Xingjie Peng ◽  
Mancang Li ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Heterogeneous System ◽  
New Method ◽  
Equivalent Transformation ◽  
Particle Sizes ◽  
Particle Type ◽  
Burnable Poison ◽  
Different Types ◽  
Fuel Particles ◽  
Type Fuel

Abstract In this paper it was found that for DH systems containing both particle-dispersed fuel and particle-dispersed burnable poison, the TRRPT method may be invalid in some situation. In his paper a new method named Hybrid RPT (HRPT) method has been proposed for DH systems containing both particle-dispersed fuel and particle-dispersed burnable poisons. And then the HRPT are analyzed and studied on the equivalent transformation range of DH systems comparing with the TRRPT method and the IRPT method. It was found that the HRPT method not only has a wider equivalent transformation range of DH systems than the TRRPT method, but also has higher calculation accuracy than the IRPT method. Results of depletion calculations for different types, different volume fractions and different particle sizes of burnable poisons particles dispersed the DH systems with dispersed particle-type fuel and the comparison with Monte Carlo results of grain models have proved the effectiveness and applicability of HRPT method.

scholarly journals The Ring RPT Method for DH Systems Containing Dispersed Particle-Type of Fuel and Burnable Poisons

2021 ◽  
Vol 9 ◽  
Author(s):  
Lei Lou ◽  
Xingjie Peng ◽  
Xiaoming Chai ◽  
Dong Yao ◽  
Mancang Li ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Cross Section ◽  
Volume Fraction ◽  
Homogenization Method ◽  
Particle Type ◽  
Burnable Poison ◽  
Physical Transformation ◽  
Different Types ◽  
Double Heterogeneity ◽  
Type Fuel

Because dispersed particle-type fuel and burnable poisons both have double heterogeneity (DH), using the traditional volumetric homogenization method (VHM) to treat DH systems will bring about large reactivity calculation deviation. The improved reactivity-equivalent physical transformation (IRPT) method can be applied to DH systems which have both dispersed particle-type fuel and burnable poisons because of the features of simplicity and high calculation accuracy. In this article, the calculations show that the IRPT method becomes invalid for some DH systems when the volume fraction of dispersed particle-type burnable poisons is relatively high or the absorb cross section of burnable poison particles is relatively large. Then the two-step ring reactivity-equivalent physical transformation (TRRPT) method is proposed to be applied to the DH systems with both dispersed particle-type fuel and burnable poisons. Results of reactivity at zero burnup and depletion calculations for different types of dispersed particle-type fuel and burnable poisons and the comparison with Monte Carlo results of grain models prove the validity of the TRRPT method, and it has been proven that the TRRPT method has higher accuracy in reactivity calculation and a wider scope of transformation than the IRPT method.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

Evaluation of Measurement Uncertainties for Pneumatic Multi-Hole Probes Using a Monte Carlo Method

2016 ◽  
Author(s):  
Magnus Hölle ◽  
Christian Bartsch ◽  
Peter Jeschke
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Compressible Flows ◽  
Uncertainty Evaluation ◽  
Calibration Data ◽  
Input Quantity ◽  
Parameter Evaluation ◽  
Polynomial Curve ◽  
Different Types ◽  
Measurement Uncertainties

The subject of this paper is a statistical method for the accurate evaluation of the uncertainties for pneumatic multi-hole probe measurements. The method can be applied to different types of evaluation algorithms and is suitable for steady flowfield measurements in compressible flows. The evaluation of uncertainties is performed by a Monte Carlo method (MCM), which is based on the statistical law of large numbers. Each input quantity, including calibration and measurement quantities, is randomly varied on the basis of its corresponding probability density function (PDF) and propagated through the deterministic parameter evaluation algorithm. Other than linear Taylor series based uncertainty evaluation methods, MCM features several advantages. On the one hand, MCM does not suffer from lower-order expansion errors and can therefore reproduce nonlinearity effects. On the other hand, different types of PDFs can be assumed for the input quantities and the corresponding coverage intervals can be calculated for any coverage probability. To demonstrate the uncertainty evaluation, a calibration and subsequent measurements in the wake of an airfoil with a 5-hole probe are performed. MCM is applied to different parameter evaluation algorithms. It is found that the MCM approach presented cannot be applied to polynomial curve fits, if the differences between the calibration data and the polynomial curve fits are of the same order of magnitude compared to the calibration uncertainty. Since this method has not yet been used for the evaluation of measurement uncertainties for pneumatic multi-hole probes, the aim of the paper is to present a highly accurate and easy-to-implement uncertainty evaluation method.

Performance assessment of the complex repairable system with n-identical units under (k-out-of-n: G) scheme and copula linguistic repair approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
V. V. Singh ◽  
Abubakkar Idris Mohhammad ◽  
Kabiru Hamisu Ibrahim ◽  
Ibrahim Yusuf
Keyword(s):  
Complex System ◽  
Design Methodology ◽  
New Method ◽  
Social Implications ◽  
Repairable System ◽  
Variable Technique ◽  
Content Type ◽  
Different Types ◽  
Theoretical Assessment ◽  
Practical Implications

PurposeThis paper analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The computed results are more supportable for repairable system performability analysis.Design/methodology/approachIn this paper, the authors have analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The supplementary variable technique has employed for analyzing the performance of the system.FindingsReliability measures have been computed for different types of configuration. It generalized the results for purely series and purely parallel configurations.Research limitations/implicationsThis research may be beneficial for industrial system performances whereas a k-out-of-n-type configuration exists.Practical implicationsNot sure as it is a theoretical assessment.Social implicationsThis research may not have social implications.Originality/valueThis work is the sole work of authors that have not been communicated to any other journal before.

scholarly journals Nesting Monte Carlo for high-dimensional non-linear PDEs

2018 ◽  
Vol 24 (4) ◽  
pp. 225-247 ◽  
Author(s):  
Xavier Warin
Keyword(s):  
Monte Carlo ◽  
Deep Learning ◽  
High Dimension ◽  
Analytical Solutions ◽  
New Method ◽  
Computational Time ◽  
High Dimensional ◽  
Learning Methods ◽  
Lipschitz Constants ◽  
Linear Pdes

Abstract A new method based on nesting Monte Carlo is developed to solve high-dimensional semi-linear PDEs. Depending on the type of non-linearity, different schemes are proposed and theoretically studied: variance error are given and it is shown that the bias of the schemes can be controlled. The limitation of the method is that the maturity or the Lipschitz constants of the non-linearity should not be too high in order to avoid an explosion of the computational time. Many numerical results are given in high dimension for cases where analytical solutions are available or where some solutions can be computed by deep-learning methods.

The fifth virial coefficient of a fluid of hard spheres

1964 ◽  
Vol 279 (1377) ◽  
pp. 147-160 ◽  
Keyword(s):  
Monte Carlo ◽  
Numerical Integration ◽  
Virial Coefficient ◽  
Monte Carlo Calculation ◽  
Hard Spheres ◽  
Cluster Integrals ◽  
Different Types

The fifth virial coefficient of a fluid of hard spheres is a sum of 238 irreducible cluster integrals of 10 different types. The values of 5 of these types (152 integrals) are obtained analytically, the contributions of a further 4 types (85 integrals) are obtained by a com­bination of analytical and numerical integration, and 1 integral is calculated by an approximation. The result is E = (0·1093 ± 0·0007) b 4 , b = 2/3 πN A σ 3 , where σ is the diameter of a sphere. A combination of the values of 237 of the cluster integrals obtained in this paper with the value of one integral obtained independently by Katsura & Abe from a Monte Carlo calculation yields E = (0·1101 ± 0·0003) b 4 .

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