scholarly journals Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Hyung Jin Shim ◽  
Sang Hoon Jang ◽  
Soo Min Kang
Keyword(s):  
Monte Carlo ◽  
Iteration Method ◽  
System Analysis ◽  
Neutron Transport ◽  
Analytic Solutions ◽  
Source Distribution ◽  
Iteration Algorithm ◽  
Driven System ◽  
Accelerator Driven System ◽  
Subcritical System

Theα-kiteration method which searches the fundamental mode alpha-eigenvalue via iterative updates of the fission source distribution has been successfully used for the Monte Carlo (MC) alpha-static calculations of supercritical systems. However, theα-kiteration method for the deep subcritical system analysis suffers from a gigantic number of neutron generations or a huge neutron weight, which leads to an abnormal termination of the MC calculations. In order to stably estimate the prompt neutron decay constant (α) of prompt subcritical systems regardless of subcriticality, we propose a new MC alpha-static calculation method named as theαiteration algorithm. The new method is derived by directly applying the power method for theα-mode eigenvalue equation and its calculation stability is achieved by controlling the number of time source neutrons which are generated in proportion toαdivided by neutron speed in MC neutron transport simulations. The effectiveness of theαiteration algorithm is demonstrated for two-group homogeneous problems with varying the subcriticality by comparisons with analytic solutions. The applicability of the proposed method is evaluated for an experimental benchmark of the thorium-loaded accelerator-driven system.

scholarly journals Comparative Analysis of Reactivity Calculations for the CERMET Fueled ADS with Serpent and MCNP6 Codes

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Vu Thanh Mai ◽  
Donny Hartanto ◽  
Pham Nhu Viet Ha ◽  
Nguyen Thi Dung ◽  
Bui Thi Hoa ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Comparative Analysis ◽  
Nuclear Waste ◽  
Inherent Safety ◽  
Fuel Temperature ◽  
Safety Feature ◽  
Temperature Feedback ◽  
Driven System ◽  
Accelerator Driven System ◽  
Good Agreement

The ADS (accelerator driven system) is recognized as a promising system to annihilate the radioactivity of nuclear waste with its inherent safety feature and waste transmutation potential. Thus, conceptual designs of ADS are widely carrying out. In order to verify the accuracy of an innovative ADS core modeling by using simulation codes, the reactivity calculations of CERMET fueled ADS were conducted using two Monte Carlo codes, Serpent and MCNP6 with ENDF/B-VII.0 library. The comparison shows a good agreement between two codes including the eigenvalue (less than 50 pcm) and fuel temperature feedback (discrepancy is within the standard deviation). It implies that the ADS was modelled successfully and can be used for further investigation.  Keywords: CERMET fueled ADS, Serpent code, MCNP6, reactivity calculation.

scholarly journals Accelerator-Driven System Analysis by Using Different Nuclear Data Libraries

2013 ◽  
Vol 38 (2) ◽  
pp. 71
Author(s):  
T. Sugawara ◽  
Ts. Zolbadral ◽  
K. Nishihara ◽  
K. Tsujimoto
Keyword(s):  
System Analysis ◽  
Nuclear Data ◽  
Driven System ◽  
Accelerator Driven System ◽  
Data Libraries ◽  
Nuclear Data Libraries

scholarly journals SUPER-HISTORY METHODS FOR ADJOINT-WEIGHTED TALLIES IN MONTE CARLO TIME EIGENVALUE CALCULATIONS

2021 ◽  
Vol 247 ◽  
pp. 04008
Author(s):  
F. Filiciotto ◽  
A. Jinaphanh ◽  
A. Zoia
Keyword(s):  
Monte Carlo ◽  
Eigenvalue Problems ◽  
Neutron Transport ◽  
Computation Time ◽  
Nuclear Data ◽  
Analytic Solutions ◽  
Benchmark Problems ◽  
Probability Method ◽  
Fission Probability ◽  
Transport Problems

Time eigenvalues emerge in several key applications related to neutron transport problems, including reactor start-up and reactivity measurements. In this context, experimental validation and uncertainty quantification would demand to assess the variation of the dominant time eigenvalue in response to a variation of nuclear data. Recently, we proposed the use of a Generalized Iterated Fission Probability method (G-IFP) to compute adjoint-weighted tallies, such as kinetic parameters, perturbations and sensitivity coefficients, for Monte Carlo time (or alpha) eigenvalue calculations. With the massive use of parallel Monte Carlo calculations, it would be therefore useful to trade the memory burden of the G-IFP method (which is comparable to that of the standard IFP method for k-eigenvalue problems) for computation time and to rely on history-based schemes for such adjoint-weighted tallies. For this purpose, we investigate the use of the super-history method as applied to estimating adjoint-weighted tallies within the α-k power iteration, based on previous work on k-eigenvalue problems. Verification of the algorithms is performed on some simple preliminary tests where analytic solutions exist. In addition, the performances of the proposed method are assessed by comparing the super-history and the G-IFP methods for the same sets of benchmark problems.

scholarly journals Monte Carlo Analysis of the Accelerator-Driven System at Kyoto University Research Reactor Institute

2016 ◽  
Vol 48 (2) ◽  
pp. 304-317 ◽  
Author(s):  
Wonkyeong Kim ◽  
Hyun Chul Lee ◽  
Cheol Ho Pyeon ◽  
Ho Cheol Shin ◽  
Deokjung Lee
Keyword(s):  
Monte Carlo ◽  
Research Reactor ◽  
Monte Carlo Analysis ◽  
University Research ◽  
Driven System ◽  
Accelerator Driven System ◽  
Reactor Institute

Markov Jump Linear System Analysis of a Microgrid Operating in Islanded and Grid Tied Modes

2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball
Keyword(s):  
Monte Carlo ◽  
Power Systems ◽  
Power System ◽  
System Analysis ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Markov Jump ◽  
Numerical Application ◽  
Conditional Moments ◽  
Markov Jump Linear Systems

<div>The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to</div><div>stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.</div>

scholarly journals Analysis of the Accelerator-Driven System Fuel Assembly during the Steam Generator Tube Rupture Accident

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1818
Author(s):  
Di-Si Wang ◽  
Bo Liu ◽  
Sheng Yang ◽  
Bin Xi ◽  
Long Gu ◽  
...  
Keyword(s):  
Fuel Assembly ◽  
Steam Generator ◽  
Metal Flow ◽  
Maximum Temperature ◽  
Steam Generator Tube ◽  
Driven System ◽  
Fuel Assemblies ◽  
Accelerator Driven System ◽  
The Impact ◽  
Steam Bubble

China is developing an ADS (Accelerator-Driven System) research device named the China initiative accelerator-driven system (CiADS). When performing a safety analysis of this new proposed design, the core behavior during the steam generator tube rupture (SGTR) accident has to be investigated. The purpose of our research in this paper is to investigate the impact from different heating conditions and inlet steam contents on steam bubble and coolant temperature distributions in ADS fuel assemblies during a postulated SGTR accident by performing necessary computational fluid dynamics (CFD) simulations. In this research, the open source CFD calculation software OpenFOAM, together with the two-phase VOF (Volume of Fluid) model were used to simulate the steam bubble behavior in heavy liquid metal flow. The model was validated with experimental results published in the open literature. Based on our simulation results, it can be noticed that steam bubbles will accumulate at the periphery region of fuel assemblies, and the maximum temperature in fuel assembly will not overwhelm its working limit during the postulated SGTR accident when the steam content at assembly inlet is less than 15%.

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