scholarly journals Variational methods and speed-up of Monte Carlo perturbation computations for optimal design in nuclear systems

2019 ◽  
Vol 34 (3) ◽  
pp. 211-221
Author(s):  
Zafar Koreshi ◽  
Hamda Khan ◽  
Muhammad Yaqub
Keyword(s):  
Monte Carlo ◽  
Variational Methods ◽  
Nuclear Reactor ◽  
Critical Mass ◽  
Reactor Core ◽  
Radiation Shielding ◽  
Optimization Simulation ◽  
Nuclear Systems ◽  
Optimal Mix ◽  
Optimal Material

Seeking optimal material distribution in a nuclear system to maximize a response function of interest has been a subject of considerable interest in nuclear engineering. Examples are the optimal fuel distribution in a nuclear reactor core to achieve uniform burnup using minimum critical mass and the use of composite materials with an optimal mix of constituent elements in detection systems and radiation shielding. For such studies, variational methods have been found to be useful but, they have been used for standalone analyses often restricted to idealized models, while more elaborate design studies have required computationally expensive Monte Carlo simulations ill-suited to iterative schemes for optimization. Such an inherent disadvantage of Monte Carlo methods changed with the development of perturbation algorithms but, their efficiency is still dependent on the reference configuration for which a hit-and-trial approach is often used. In the first illustrative example, this paper explores the computational speedup for a bare cylindrical reactor core, achievable by using a variational result to enhance the computational efficiency of Monte Carlo design optimization simulation. In the second example, the effect of non-uniform material density in a fixed-source problem, applicable to optimal moderator and radiation shielding, is presented. While applications of this work are numerous, the objective of this paper is to present preliminary variational results as inputs to elaborate stochastic optimization by Monte Carlo simulation for large and realistic systems.

Preliminary Core Design and Optimization Analysis of Travelling Wave Reactor

2014 ◽  
Vol 1070-1072 ◽  
pp. 357-360
Author(s):  
Dao Xiang Shen ◽  
Yao Li Zhang ◽  
Qi Xun Guo
Keyword(s):  
Monte Carlo ◽  
Rational Design ◽  
Nuclear Reactor ◽  
Reactor Core ◽  
Travelling Wave ◽  
Optimization Analysis ◽  
Design And Optimization ◽  
Uranium Fuel ◽  
Enriched Uranium ◽  
Ignition Zone

A travelling wave reactor (TWR) is an advanced nuclear reactor which is capable of running for decades given only depleted uranium fuel, it is considered one of the most promising solutions for nonproliferation. A preliminary core design was proposed in this paper. The calculation was performed by Monte Carlo method. The burning mechanism of the reactor core design was studied. Optimization on the ignition zone was performed to reduce the amount of enriched uranium initially deployed. The results showed that the preliminary core design was feasible. The optimization analysis showed that the amount of enriched uranium could be reduced under rational design.

scholarly journals AI-based design of a nuclear reactor core

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vladimir Sobes ◽  
Briana Hiscox ◽  
Emilian Popov ◽  
Rick Archibald ◽  
Cory Hauck ◽  
...  
Keyword(s):  
Nuclear Reactor ◽  
Rapid Development ◽  
Reactor Core ◽  
Systems Design ◽  
Axial Direction ◽  
Arbitrary Geometry ◽  
Oak Ridge ◽  
Geometry Design ◽  
Nuclear Systems ◽  
Nuclear Reactor Core

AbstractThe authors developed an artificial intelligence (AI)-based algorithm for the design and optimization of a nuclear reactor core based on a flexible geometry and demonstrated a 3× improvement in the selected performance metric: temperature peaking factor. The rapid development of advanced, and specifically, additive manufacturing (3-D printing) and its introduction into advanced nuclear core design through the Transformational Challenge Reactor program have presented the opportunity to explore the arbitrary geometry design of nuclear-heated structures. The primary challenge is that the arbitrary geometry design space is vast and requires the computational evaluation of many candidate designs, and the multiphysics simulation of nuclear systems is very time-intensive. Therefore, the authors developed a machine learning-based multiphysics emulator and evaluated thousands of candidate geometries on Summit, Oak Ridge National Laboratory’s leadership class supercomputer. The results presented in this work demonstrate temperature distribution smoothing in a nuclear reactor core through the manipulation of the geometry, which is traditionally achieved in light water reactors through variable assembly loading in the axial direction and fuel shuffling during refueling in the radial direction. The conclusions discuss the future implications for nuclear systems design with arbitrary geometry and the potential for AI-based autonomous design algorithms.

scholarly journals Multiobjective Core Reloading Pattern Optimization of PARR-1 Using Modified Genetic Algorithm Coupled with Monte Carlo Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Nadeem Shaukat ◽  
Ammar Ahmad ◽  
Bukhtiar Mohsin ◽  
Rustam Khan ◽  
Salah Ud-Din Khan ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Nuclear Reactor ◽  
Computational Cost ◽  
Reactor Core ◽  
Reactor Physics ◽  
Irradiation Site ◽  
Loading Pattern ◽  
Intelligent Technique ◽  
Safety Constraints ◽  
The Given

In order to maximize both the life cycle and efficiency of a reactor core, it is essential to find the optimum loading pattern. In the case of research reactors, a loading pattern can also be optimized for flux at an irradiation site. Therefore, the development of a general-use methodology for core loading optimization would be very valuable. In this paper, general-use multiobjective core reloading pattern optimization is performed using modified genetic algorithms (MGA). The developed strategy can be applied for the constrained optimization of research and power reactor cores. For an optimal reactor core reloading design strategy, an intelligent technique GA is coupled with the Monte Carlo (MC) code SuperMC developed by the FDS team in China for nuclear reactor physics calculations. An optimal loading pattern can be depicted as a configuration that has the maximum keff and maximum thermal fluxes in the core of the given fuel inventory keeping in view the safety constraints such as limitation on power peaking factor. The optimized loading patterns for Pakistan Research Reactor-1 (PARR-1) have been recommended using the implemented strategy by considering the constraint optimization, i.e., to maximize the keff or maximum thermal neutron flux while maintaining low power peaking factor. It has been observed that the developed intelligent strategy performs these tasks with a reasonable computational cost.

scholarly journals TOWARDS ZERO-VARIANCE SCHEMES FOR KINETIC MONTE-CARLO SIMULATIONS

2021 ◽  
Vol 247 ◽  
pp. 04010
Author(s):  
Davide Mancusi ◽  
Andrea Zoia
Keyword(s):  
Monte Carlo ◽  
Variance Reduction ◽  
Nuclear Reactor ◽  
Kinetic Monte Carlo ◽  
Reactor Core ◽  
Transport Problem ◽  
Time Dependent ◽  
Reactor Kinetics ◽  
Reduction Techniques ◽  
Dependent Transport

The solution of the time-dependent transport problem for neutrons and precursors in a nuclear reactor is hard to treat in a naive Monte-Carlo framework because of the largely different time scales associated to the prompt-fission chains and to the decay of precursors. The increasing computer power and the development of variance-reduction techniques specific for reactor kinetics have recently unlocked the possibility to calculate reference solutions to the time-dependent transport problem. However, the application of time-dependent Monte Carlo to large systems (i.e., a full reactor core) is still stifled by the enormous computational requirements. In this paper, we formulate the construction of an optimal Monte-Carlo strategy (in the sense that it results in a zero-variance estimator) for a specific observable in time-dependent transport, in analogy with the existing schemes for stationary problems. As far as we are aware, zero-variance Monte-Carlo schemes for neutron-precursor kinetics have never been proposed before. We verify our construction with numerical calculations for a benchmark transport problem.

scholarly journals Correlated Production and Analog Transport of Fission Neutrons and Photons using Fission Models FREYA, FIFRELIN and the Monte Carlo Code TRIPOLI-4® .

2018 ◽  
Vol 170 ◽  
pp. 01019
Author(s):  
Jérôme M. Verbeke ◽  
Odile Petit ◽  
Abdelhazize Chebboubi ◽  
Olivier Litaize
Keyword(s):  
Monte Carlo ◽  
Reactor Core ◽  
Radiation Shielding ◽  
Model Parameters ◽  
Monte Carlo Code ◽  
Coincidence Counting ◽  
Angular Correlations ◽  
Fission Neutrons ◽  
Nuclear Instrumentation ◽  
Monte Carlo Transport

Fission modeling in general-purpose Monte Carlo transport codes often relies on average nuclear data provided by international evaluation libraries. As such, only average fission multiplicities are available and correlations between fission neutrons and photons are missing. Whereas uncorrelated fission physics is usually sufficient for standard reactor core and radiation shielding calculations, correlated fission secondaries are required for specialized nuclear instrumentation and detector modeling. For coincidence counting detector optimization for instance, precise simulation of fission neutrons and photons that remain correlated in time from birth to detection is essential. New developments were recently integrated into the Monte Carlo transport code TRIPOLI-4 to model fission physics more precisely, the purpose being to access event-by-event fission events from two different fission models: FREYA and FIFRELIN. TRIPOLI-4 simulations can now be performed, either by connecting via an API to the LLNL fission library including FREYA, or by reading external fission event data files produced by FIFRELIN beforehand. These new capabilities enable us to easily compare results from Monte Carlo transport calculations using the two fission models in a nuclear instrumentation application. In the first part of this paper, broad underlying principles of the two fission models are recalled. We then present experimental measurements of neutron angular correlations for 252Cf(sf) and 240Pu(sf). The correlations were measured for several neutron kinetic energy thresholds. In the latter part of the paper, simulation results are compared to experimental data. Spontaneous fissions in 252Cf and 240Pu are modeled by FREYA or FIFRELIN. Emitted neutrons and photons are subsequently transported to an array of scintillators by TRIPOLI-4 in analog mode to preserve their correlations. Angular correlations between fission neutrons obtained independently from these TRIPOLI-4 simulations, using either FREYA or FIFRELIN, are compared to experimental results. For 240Pu(sf), the measured correlations were used to tune the model parameters.

Sign in / Sign up

Export Citation Format

Share Document