scholarly journals Critical Buckling Generation of TCA Benchmark by the B1 Theory-Augmented Monte Carlo Calculation and Estimation of Uncertainties

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2578
Author(s):  
Ho Jin Park ◽  
Jin Young Cho
Keyword(s):  
Monte Carlo ◽  
Vertical Direction ◽  
Benchmark Problems ◽  
Section Data ◽  
Critical Experiment ◽  
Basic Equations ◽  
Nodal Diffusion ◽  
New Formulation ◽  
Estimation Of Uncertainties ◽  
Mc Method

The Korea Atomic Energy Research Institute (KAERI) has developed the DeCART2D 2-dimensional (2D) method of characteristics (MOC) transport code and the MASTER nodal diffusion code and has established its own two-step procedure. For design code licensing, KAERI prepared a critical experiment on the verification and validation (V&V) of the DeCART2D code. DeCART2D is able to perform the MOC calculation only for 2D nuclear fuel systems, such as the fuel assembly. Therefore, critical buckling in the vertical direction is essential for comparison between the results of experiments and DeCART2D. In this study, the B1 theory-augmented Monte Carlo (MC) method was adopted for the generation of critical buckling. To examine critical buckling using the B1 theory-augmented MC method, TCA critical experiment benchmark problems were considered. Based on the TCA benchmark results, it was confirmed that the DeCART2D code with the newly-generated critical buckling predicts the criticality very well. In addition, the critical buckling generated by the B1 theory-augmented MC method was bound to uncertainties. Therefore, utilizing basic equations (e.g., SNU S/U formulation) linking input uncertainties to output uncertainties, a new formulation to estimate the uncertainties of the newly generated critical buckling was derived. This was then used to compute the uncertainties of the critical buckling for a TCA critical experiment, under the assumption that nuclear cross-section data have uncertainties.

QMC integration errors and quasi-asymptotics

2020 ◽  
Vol 26 (3) ◽  
pp. 171-176
Author(s):  
Ilya M. Sobol ◽  
Boris V. Shukhman
Keyword(s):  
Monte Carlo ◽  
Error Estimate ◽  
Numerical Experiments ◽  
Probable Error ◽  
Quasi Monte Carlo ◽  
Integration Error ◽  
Asymptotic Error ◽  
Dimensional Cube ◽  
Integration Errors ◽  
Mc Method

AbstractA crude Monte Carlo (MC) method allows to calculate integrals over a d-dimensional cube. As the number N of integration nodes becomes large, the rate of probable error of the MC method decreases as {O(1/\sqrt{N})}. The use of quasi-random points instead of random points in the MC algorithm converts it to the quasi-Monte Carlo (QMC) method. The asymptotic error estimate of QMC integration of d-dimensional functions contains a multiplier {1/N}. However, the multiplier {(\ln N)^{d}} is also a part of the error estimate, which makes it virtually useless. We have proved that, in the general case, the QMC error estimate is not limited to the factor {1/N}. However, our numerical experiments show that using quasi-random points of Sobol sequences with {N=2^{m}} with natural m makes the integration error approximately proportional to {1/N}. In our numerical experiments, {d\leq 15}, and we used {N\leq 2^{40}} points generated by the SOBOLSEQ16384 code published in 2011. In this code, {d\leq 2^{14}} and {N\leq 2^{63}}.

scholarly journals Monte Carlo Simulation for Economic Analysis of Hydropower Pumped Storage Project in Nepal

2013 ◽  
Vol 12 ◽  
pp. 39-44 ◽  
Author(s):  
Kaspar Vereide ◽  
Leif Lia ◽  
Laras Ødegård
Keyword(s):  
Monte Carlo ◽  
Economic Analysis ◽  
Net Present Value ◽  
Simulation Method ◽  
Construction Costs ◽  
Energy And Environment ◽  
Pumped Storage ◽  
High Degree ◽  
Mc Method

Investments in hydropower pumped storage projects (PSP) are subjected to a high degree of uncertainty. In addition to normal uncertainties in hydropower schemes, the profit of a pumped storage scheme is dependent on the margin between power prices for buying and selling, which is difficult to predict without a power purchase agreement (PPA). A PSP without a PPA and without known construction costs requires quantification of the uncertainties in order to make qualified decisions before investing in such projects. This article demonstrates the advantages of using Monte Carlo (MC) simulations as a tool in the economic analysis of PSPs. The method has been tested on a case study, namely the Tamakoshi-3 Hydropower Project (HPP) in Nepal. The MC method is used to calculate the probability distribution of the net present value of installing reversible units in the Tamakoshi-3 HPP. The calculations show that PSPs may be profitable in Nepal, given a beneficial development of the power market. The MC method is considered to be a useful tool for economic analysis of PSPs. In this case study of installing reversible units in the Tamakoshi-3 HPP, there are many uncertainties, which the MC simulation method is able to quantify. Hydro Nepal; Journal of Water, Energy and Environment Vol. 12, 2013, January Page: 39-44DOI: http://dx.doi.org/10.3126/hn.v12i0.9031 Uploaded Date : 10/29/2013

scholarly journals Monte Carlo simulations and n-p differential scattering data measured with Proton Recoil Telescopes

2020 ◽  
Vol 239 ◽  
pp. 01024
Author(s):  
N. Terranova ◽  
O. Aberle ◽  
V. Alcayne ◽  
S. Amaducci ◽  
J. Andrzejewski ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Cross Section ◽  
Fission Cross Section ◽  
Particle Identification ◽  
Scattering Data ◽  
Section Data ◽  
Technology Applications ◽  
Primary Reference ◽  
Proton Recoil

The neutron-induced fission cross section of 235U, a standard at thermal energy and between 0.15 MeV and 200 MeV, plays a crucial role in nuclear technology applications. The long-standing need of improving cross section data above 20 MeV and the lack of experimental data above 200 MeV motivated a new experimental campaign at the n_TOF facility at CERN. The measurement has been performed in 2018 at the experimental area 1 (EAR1), located at 185 m from the neutron-producing target (the experiment is presented by A. Manna et al. in a contribution to this conference). The 235U(n,f) cross section from 20 MeV up to about 1 GeV has been measured relative to the 1H(n,n)1H reaction, which is considered the primary reference in this energy region. The neutron flux impinging on the 235U sample (a key quantity for determining the fission events) has been obtained by detecting recoil protons originating from n-p scattering in a C2H4 sample. Two Proton Recoil Telescopes (PRT), consisting of several layers of solid-state detectors and fast plastic scintillators, have been located at proton scattering angles of 25.07° and 20.32°, out of the neutron beam. The PRTs exploit the ΔE-E technique for particle identification, a basic requirement for the rejection of charged particles from neutron-induced reactions in carbon. Extensive Monte Carlo simulations were performed to characterize proton transport through the different slabs of silicon and scintillation detectors, to optimize the experimental set-up and to deduce the efficiency of the whole PRT detector. In this work we compare measured data collected with the PRTs with a full Monte Carlo simulation based on the Geant-4 toolkit.

Monte Carlo study of photoneutron production in U-235 following perturbations in cross section data

2009 ◽  
Vol 36 (3) ◽  
pp. 393-398 ◽  
Author(s):  
S.D. Clarke ◽  
S.A. Pozzi ◽  
M. Flaska ◽  
T.J. Downar
Keyword(s):  
Monte Carlo ◽  
Cross Section ◽  
Monte Carlo Study ◽  
Cross Section Data ◽  
Section Data
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