Large-eddy simulation on two-liquid mixing in the horizontal leg and downcomer (the TAMU-CFD Benchmark), with respect to fluctuation behavior of liquid concentration

Abe, Satoshi; Okagaki, Yuria

Nuclear Engineering and Design, 404, p.112165_1 - 112165_14, 2023/04

https://doi.org/10.1016/j.nucengdes.2023.112165

Quantitative analysis of radioactivity distribution by imaging of high radiation field environment using gamma-ray imaging spectroscopy (Contract research); FY2019 Nuclear Energy Science & Technology and Human Resource Development Project

Collaborative Laboratories for Advanced Decommissioning Science; Kyoto University*

JAEA-Review 2020-044, 79 Pages, 2021/01

JAEA-Review-2020-044.pdf:4.39MB

The Collaborative Laboratories for Advanced Decommissioning Science (CLADS), Japan Atomic Energy Agency (JAEA), had been conducting the Nuclear Energy Science & Technology and Human Resource Development Project (hereafter referred to "the Project") in FY2019. The Project aims to contribute to solving problems in the nuclear energy field represented by the decommissioning of the Fukushima Daiichi Nuclear Power Station, Tokyo Electric Power Company Holdings, Inc. (TEPCO). For this purpose, intelligence was collected from all over the world, and basic research and human resource development were promoted by closely integrating/collaborating knowledge and experiences in various fields beyond the barrier of conventional organizations and research fields. The sponsor of the Project was moved from the Ministry of Education, Culture, Sports, Science and Technology to JAEA since the newly adopted proposals in FY2018. On this occasion, JAEA constructed a new research system where JAEA-academia collaboration is reinforced and medium-to-long term research/development and human resource development contributing to the decommissioning are stably and consecutively implemented. Among the adopted proposals in FY2018, this report summarizes the research results of the "Quantitative analysis of radioactivity distribution by imaging of high radiation field environment using gamma-ray imaging spectroscopy" Conducted in FY2019. In this study, a gamma-ray imaging detector, ETCC, will be improved to operate under high dose conditions, and a portable system will be constructed to be installed in the Fukushima Daiichi Nuclear PowerStation (1F). In addition, the development and combination of ETCC-based quantitative radioactivity distribution analysis methods will lead to innovative advances in the six key issues to be solved for the decommissioning of the 1F. This system will enable us to quantitatively visualize the three-dimensional radiation distribution and its origin.

Underlying mechanism of numerical instability in Large-Eddy Simulation of turbulent flows

Ida, Masato; Taniguchi, Nobuyuki*

Physical Review E, 69(4), p.046701_1 - 046701_9, 2004/04

https://doi.org/10.1103/PhysRevE.69.046701

This paper extends our recent theoretical work concerning the feasibility of stable and accurate computation of turbulence using a large eddy simulation. In our previous paper, it was shown, based on a simple assumption regarding the instantaneous streamwise velocity, that the application of the Gaussian filter to the Navier-Stokes equations can result in the appearance of a numerically unstable term. In the present paper, based on assumptions regarding the statistically averaged velocity, we show that in several situations, the shears appearing in the statistically averaged velocity field numerically destabilize the fluctuation components because of the derivation of a numerically unstable term that represents negative diffusion in a fixed direction. This finding can explain the problematic numerical instability that has been encountered in large eddy simulations of wall-bounded flows. The present result suggests that if there is no failure in modeling, the resulting subgrid-scale model can still have unstable characteristics.

Large-eddy simulation of plume dispersion during the Fukushima Daiichi Nuclear Power Plant accident by coupling with a meso-scale meteorological simulation model

Nakayama, Hiromasa; Takemi, Tetsuya*; Nagai, Haruyasu

no journal, , 

A significant amount of radioactive material was accidentally discharged into the atmosphere from the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) from March 12, 2011. In conducting regional-scale atmospheric dispersion simulations, the nuclear emergency response system based on a meso-scale meteorological model (MM) was used. However, it is impossible to conduct detailed simulations of plume dispersion considering the turbulent effects in a local-scale because buildings, structures, and local terrain variability are not explicitly represented at high grid resolutions in those models. Therefore, an approach to couple an LES-based CFD model with a MM model should be promising. In this study, first we conduct LESs of plume dispersion around the FDNPP under a constant meteorological condition by prescribing constant mean wind velocities and directions at the inlet boundary condition, and then do them under a varying meteorological condition by coupling with a MM model. Our objective is to compare plume dispersion patterns under those different meteorological conditions and evaluate the effectiveness of the coupling computational method.

Particle filter for Large-eddy Simulations of turbulent boundary-layer flow generation based on observations

Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Nakayama, Hiromasa; Shimokawabe, Takashi*; Aoki, Takayuki*

no journal, , 

This paper presents a novel data assimilation method in realistic turbulent boundary layer simulations for the realization of a wind digital twin. We have developed a plume dispersion simulation code named CityLBM based on a lattice Boltzmann method. CityLBM enables a real time ensemble simulation for several km square area by applying locally mesh-refinement method on GPU supercomputers. Mesoscale wind boundary conditions produced by a Weather Research and Forecasting Model are given as boundary conditions in CityLBM by using a nudging data assimilation method. In this study, we propose a dynamic nudging data assimilation method, where a particle filter optimizes the nudging coefficient based on the observation data. This approach gave reasonable agreements in vertical profiles of the wind speed, the wind direction, and the turbulent intensity compared to the observation data throughout the day, and enabled all-day simulations, where atmospheric conditions change significantly.