SNUEI

On benchmarking of simulations of particle transport in ITER

2019 · Nuclear Fusion

저자

나용수 (Yong-Su Na), F. Koechl, A.R. Polevoi, C.S. Byun, D.H. Na, Jaemin Seo, Federico Felici, A. Fukuyama, Jeronimo Garcia, N. Hayashi, C. Kessel, Tim C. Luce, J.M. Park, F. M. Poli, O. Sauter, Adrianus C. C. Sips, P. Strand, Anna A Teplukhina, I. A. Voitsekhovitch, Apiwat Wisitsorasak, Xingqiu Yuan, The ITPA Topical Group on Integrated Operation Scenarios

연구주제

Magnetic confinement fusion research

NTIS 과학기술표준분류

에너지/자원만에너지·환경·원자력 확장

지원 과제·AI 키워드로 잡을 근거가 없어 분류하지 않았다.

AI 연구 키워드·방법

particle transport pellet fueling 토카막 운전 시나리오

code benchmarking 통합 수송 모델링

키워드 (OpenAlex)

particle transport ITER tokamak plasma code benchmarking pellet injection gas puff fueling H-mode density peaking

초록

We report results of benchmarking of core particle transport simulations by a collection of codes widely used in transport modelling of tokamak plasmas. Our analysis includes formulation of transport equations, difference between electron and ion solvers, comparison of modules of the pellet and edge gas fuelling on the ITER baseline scenario. During the first phase of benchmarking we address the particle transport effects in the stationary phase. Firstly, simulations are performed with identical sources, sinks, transport coefficients, and boundary conditions prescribed in the flattop H-mode phase. The transformation of ion particle transport equations is introduced so to directly compare their results to electron transport solvers. Secondly, the pellet fuelling models are benchmarked in various conditions to evaluate the dependency of the pellet deposition on the pellet volume, injection…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

이 문서와 연결된 페이지

교수 1

나용수

연구주제 1

Magnetic confinement fusion research

키워드 1

토카막 운전 시나리오

방법 1

통합 수송 모델링