scholarly journals NEUTRONIC MODELING STRATEGIES FOR A LIQUID FUEL TRANSIENT CALCULATION

2021 ◽  
Vol 247 ◽  
pp. 06013
Author(s):  
J.A. Blanco ◽  
P. Rubiolo ◽  
E. Dumonteil
Keyword(s):  
Monte Carlo ◽  
Molten Salt ◽  
Numerical Scheme ◽  
Liquid Fuel ◽  
Computational Cost ◽  
Thermal Hydraulics ◽  
Numerical Tool ◽  
Criticality Accidents

Framework • A detailed and highly flexible numerical tool to study criticality accidents has been developed • The tool implements a Multi-Physics coupling using neutronics, thermal-hydraulics and thermal-mechanics models based on Open FOAM and SERPENT codes • Two neutronics models: Quasi-Static Monte Carlo and SPN Objective: In this work a system composed by a 2D square liquid fuel cavity filled with a fuel molten salt has been used to: • Investigate the performance of the tool’s thermal-hydraulics and neutronics solvers coupling numerical scheme • Evaluate possible strategies for the implementation of the Quasi-Static (QS) method with the Monte Carlo (MC) neutronics code • Compare the QS-MC approach precision and computational cost against the Simplified P3 (SP3) method

COUPLE, A Time-Dependent Coupled Neutronics and Thermal-Hydraulics Code, and its Application to MSFR

2014 ◽  
Author(s):  
Dalin Zhang ◽  
Zhi-Gang Zhai ◽  
Andrei Rineiski ◽  
Zhangpeng Guo ◽  
Chenglong Wang ◽  
...  
Keyword(s):  
Molten Salt ◽  
Liquid Fuel ◽  
Time Dependent ◽  
Molten Salt Reactor ◽  
Thermal Hydraulics ◽  
Delayed Neutron ◽  
Fuel Flow ◽  
Reactor Optimization ◽  
Fuel Characteristics ◽  
Significant Attention

Molten salt reactor (MSR) using liquid fuel is one of the Generation-IV candidate reactors. Its liquid fuel characteristics are fundamentally different from those of the conventional solid-fuel reactors, especially the much stronger neutronics and thermal hydraulics coupling is drawing significant attention. In this study, the fundamental thermal hydraulic model, neutronic model, and some auxiliary models were established for the liquid-fuel reactors, and a time-dependent coupled neutronics and thermal hydraulics code named COUPLE was developed to solve the mathematic models by the numerical method. After the code was verified, it was applied to the molten salt fast reactor (MSFR) to perform the steady state calculation. The distributions of the neutron fluxes, delayed neutron precursors, velocity, and temperature were obtained and presented. The results show that the liquid fuel flow affects the delayed neutron precursors significantly, while slightly influences the neutron fluxes. The flow in the MSFR core generates a vortex near the fertile tank, which leads to the maximal temperature about 1100 K at the centre of the vortex. The results can provide some useful information for the reactor optimization.

The Soft Ion Model in Monte Carlo Simulation of Molten Salts

1988 ◽  
Vol 43 (2) ◽  
pp. 129-132
Author(s):  
C. Margheritis ◽  
C. Sinistri
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Molten Salt ◽  
Molten Salts ◽  
Computational Cost ◽  
Coulomb Energy ◽  
Numerical Application ◽  
Polarization Energy ◽  
Simple Evaluation ◽  
Salt Systems

Abstract This paper describes a method for a simple evaluation of the polarization energy in molten salt systems, by which it is possible to go, without heavy computational cost, from the rigid to the soft ion model. The method is based on the observation that, within the movements of single ions in the Monte Carlo chain, the deviation of the polarization energy is a linear function of the deviation of the Coulomb energy.An extended numerical application has been carried out for molten Lil at 800, 1200 and 1453 (b. p.) K. The parameters that are mostly affected by the used model are put into evidence.

Multilevel Monte Carlo by using the Halton sequence

2020 ◽  
Vol 26 (3) ◽  
pp. 193-203
Author(s):  
Shady Ahmed Nagy ◽  
Mohamed A. El-Beltagy ◽  
Mohamed Wafa
Keyword(s):  
Monte Carlo ◽  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Computational Cost ◽  
Random Numbers ◽  
Multilevel Monte Carlo ◽  
Halton Sequence ◽  
Random Generator ◽  
Mc Simulation ◽  
Multilevel Monte Carlo Method

AbstractMonte Carlo (MC) simulation depends on pseudo-random numbers. The generation of these numbers is examined in connection with the Brownian motion. We present the low discrepancy sequence known as Halton sequence that generates different stochastic samples in an equally distributed form. This will increase the convergence and accuracy using the generated different samples in the Multilevel Monte Carlo method (MLMC). We compare algorithms by using a pseudo-random generator and a random generator depending on a Halton sequence. The computational cost for different stochastic differential equations increases in a standard MC technique. It will be highly reduced using a Halton sequence, especially in multiplicative stochastic differential equations.

A new weighted fraction Monte Carlo method for particle coagulation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiao Jiang ◽  
Tat Leung Chan
Keyword(s):  
Monte Carlo ◽  
Design Methodology ◽  
Computational Cost ◽  
Particle Coagulation ◽  
Content Type ◽  
Aerosol Dynamics ◽  
Stochastic Error ◽  
Adjustable Weight ◽  
Initial Distributions ◽  
Coagulation Kernel

Purpose The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method. Design/methodology/approach The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme. Findings Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated. Originality Value Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

Coupled neutronics and thermal-hydraulics simulation of molten salt reactors based on OpenMC/TANSY

2017 ◽  
Vol 109 ◽  
pp. 260-276 ◽  
Author(s):  
Tianliang Hu ◽  
Liangzhi Cao ◽  
Hongchun Wu ◽  
Xianan Du ◽  
Mingtao He
Keyword(s):  
Molten Salt ◽  
Thermal Hydraulics

Coupled Analysis of Thermal Hydraulics and Neutronics for a Molten Salt Reactor

2017 ◽  
Author(s):  
Jian Ge ◽  
Dalin Zhang ◽  
Wenxi Tian ◽  
Suizheng Qiu ◽  
G. H. Su
Keyword(s):  
Molten Salt ◽  
Nuclear Reactor ◽  
Coupled Analysis ◽  
Molten Salt Reactor ◽  
Thermal Hydraulics ◽  
Delayed Neutron ◽  
Analysis Model ◽  
Liquid Salt ◽  
Energy Equations ◽  
Volume Method

As one of the six selected optional innovative nuclear reactor in the generation IV International Forum (GIF), the Molten Salt Reactor (MSR) adopts liquid salt as nuclear fuel and coolant, which makes the characteristics of thermal hydraulics and neutronics strongly intertwined. Coupling analysis of neutronics and thermal hydraulics has received considerable attention in recent years. In this paper, a new coupling method is introduced based on the Finite Volume Method (FVM), which is widely used in the Computational Fluid Dynamics (CFD) methodology. Neutron diffusion equations and delayed neutron precursors balance equations are discretized and solved by the commercial CFD package FLUENT, along with continuity, momentum and energy equations simultaneously. A Temporal And Spatial Neutronics Analysis Model (TASNAM) is developed using the User Defined Functions (UDF) and User Defined Scalar (UDS) in FLUENT. A neutronics benchmark is adopted to demonstrate the solution capability for neutronics problems using the method above. Furthermore, a steady state coupled analysis of neutronics and thermal hydraulics for the Molten Salt Advanced Reactor Transmuter (MOSART) is performed. Two groups of neutrons and six groups of delayed neutron precursors are adopted. Distributions of the liquid salt velocity, temperature, neutron flux and delayed neutron precursors in the core are obtained and analyzed. This work can provide some valuable information for the design and research of MSRs.

scholarly journals On Dynamic Parallelization of Multilevel Monte Carlo Algorithm

2020 ◽  
Vol 20 (6) ◽  
pp. 116-125
Author(s):  
Nikolay Shegunov ◽  
Oleg Iliev
Keyword(s):  
Monte Carlo ◽  
Numerical Simulations ◽  
Random Fields ◽  
Stochastic Partial Differential Equations ◽  
Computational Cost ◽  
Monte Carlo Algorithm ◽  
Multilevel Monte Carlo ◽  
Deterministic Problem ◽  
Speed Up ◽  
Main Components

AbstractMultiLevel Monte Carlo (MLMC) attracts great interest for numerical simulations of Stochastic Partial Differential Equations (SPDEs), due to its superiority over the standard Monte Carlo (MC) approach. MLMC combines in a proper manner many cheap fast simulations with few slow and expensive ones, the variance is reduced, and a significant speed up is achieved. Simulations with MC/MLMC consist of three main components: generating random fields, solving deterministic problem and reduction of the variance. Each part is subject to a different degree of parallelism. Compared to the classical MC, MLMC introduces “levels” on which the sampling is done. These levels have different computational cost, thus, efficiently utilizing the parallel resources becomes a non-trivial problem. The main focus of this paper is the parallelization of the MLMC Algorithm.

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