Volumetric recombination in EMC3-EIRENE: Implementation and first application to the pre-fusion power operation phase in ITER

2021 ◽  
Vol 28 (10) ◽  
pp. 102503
Author(s):  
H. Frerichs ◽  
Y. Feng ◽  
X. Bonnin ◽  
R. A. Pitts ◽  
D. Reiter ◽  
...  
Keyword(s):  
Fusion Power ◽  
Power Operation ◽  
Operation Phase

Modelling one-third field operation in the ITER pre-fusion power operation phase

2019 ◽  
Vol 59 (12) ◽  
pp. 126014 ◽  
Author(s):  
M. Schneider ◽  
A.R. Polevoi ◽  
S.H. Kim ◽  
A. Loarte ◽  
S.D. Pinches ◽  
...  
Keyword(s):  
Fusion Power ◽  
Field Operation ◽  
Power Operation ◽  
Operation Phase

H-mode plasmas in the Pre-Fusion Power Operation 1 phase of the ITER Research Plan

2021 ◽  
Author(s):  
Alberto Loarte ◽  
Alexei R Polevoi ◽  
Mireille Schneider ◽  
Simon D Pinches ◽  
Emiliano Fable ◽  
...  
Keyword(s):  
Fusion Power ◽  
Research Plan ◽  
Power Operation

Prediction of divertor heat flux width for ITER Pre-Fusion Power Operation using BOUT++ transport code

2021 ◽  
Author(s):  
Xiaoxue He ◽  
Xueqiao Xu ◽  
Zeyu Li ◽  
Ben Zhu ◽  
Yue Liu
Keyword(s):  
Heat Flux ◽  
Thermal Diffusivity ◽  
Transport Coefficients ◽  
Poloidal Magnetic Field ◽  
Fusion Power ◽  
Drift Model ◽  
Transport Code ◽  
Initial Plasma ◽  
Power Operation ◽  
Major Radius

Abstract Prediction of divertor heat flux width is performed for the first and the second Pre-Fusion Power Operation (PFPO) phases specified in the new ITER Research Plan using BOUT++ transport code [Li N.M. et al 2018 Comput. Phys. Commun. 228 69–82]. The initial plasma profiles inside the separatrix are taken from CORSICA scenario studies. Transport coefficients in transport code are calculated by inverting the plasma profiles inside the separatrix and are assumed to be constants in the scrape-off-layer (SOL). An anomalous thermal diffusivity scan is performed with E×B and magnetic drifts. The results in two scenarios identify two distinct regimes: a drift dominant regime when diffusivity is smaller than the respective critical diffusivity χc and a turbulence dominant regime when diffusivity is larger than it. The Goldston heuristic drift model and the ITPA multi-machine experimental scaling yield a lower limit of the width λq. From transport simulations, we obtain the critical diffusivity χc = 0.5 m2⁄ s in 5MA/1.77T PFPO-1 scenario and χc = 0.3 m2⁄ s in 7.5MA/2.65T PFPO-2 scenario. Separatrix temperature and collisionality also have a significant impact on the heat flux width in the drift dominant regime. The investigation clearly yields a scaling for critical thermal diffusivity χc ∝ A½ ⁄ ((Z(1+Z)½ Bp 2)) using ITER scenarios with fixed safety factor q95, major radius R, aspect ratio R/a, and the separatrix temperature T, as well as established the connection with CFETR and C-Mod discharges. This scaling implies that for a given tokamak device with q95, R, R/a, and T fixed, a reduction of poloidal magnetic field by a factor of 3 leads to a 9 times higher critical value of thermal diffusivity χc, possibly yielding a transition from turbulence to drift dominant regime.

Assessing the effectiveness of renewable energy sector support mechanisms

2020 ◽  
Vol 26 (6) ◽  
pp. 1392-1413
Author(s):  
S.V. Ratner
Keyword(s):  
Renewable Energy ◽  
Project Management ◽  
Wind Power ◽  
Learning By Doing ◽  
Comprehensive Analysis ◽  
Incentive Mechanisms ◽  
Support Programme ◽  
Support Mechanisms ◽  
Generating Equipment ◽  
Operation Phase

Subject. This article discusses the effectiveness of government programmes to support renewable energy and whether they should continue to be implemented. Objectives. The article aims to conduct a comprehensive analysis of the changes in solar and wind power projects under the State support programme within the period from 2014 to 2019 and assess the effectiveness of the acting incentive mechanisms. Methods. For the study, I used the Learning-by-Doing theory and Project Management principles and methods. Results. The article proposes to consider the local content of the projects implemented as the key effectiveness indicator of the renewable energy support programme in Russia. For solar projects, this figure is currently significantly higher than the planned one, and it corresponds to the planned one for wind projects. In general, therefore, the programme can be considered effective. Conclusions. Further improvements in renewable energy support mechanisms should take into account the need to drastically increase the pace of training in the full cycle of the renewable energy project, including the operation phase of generating equipment and the supply of electricity to the grid.

scholarly journals Machine learning and simulation-based surrogate modeling for improved process chain operation

2021 ◽  
Author(s):  
André Hürkamp ◽  
Sebastian Gellrich ◽  
Antal Dér ◽  
Christoph Herrmann ◽  
Klaus Dröder ◽  
...  
Keyword(s):  
Surrogate Modeling ◽  
Temperature History ◽  
Injection Molding Process ◽  
Process Chain ◽  
Molding Process ◽  
Whole Process ◽  
Virtual Production ◽  
Sensor Model ◽  
Fast Prediction ◽  
Operation Phase

AbstractIn this contribution, a concept is presented that combines different simulation paradigms during the engineering phase. These methods are transferred into the operation phase by the use of data-based surrogates. As an virtual production scenario, the process combination of thermoforming continuous fiber-reinforced thermoplastic sheets and injection overmolding of thermoplastic polymers is investigated. Since this process is very sensitive regarding the temperature, the volatile transfer time is considered in a dynamic process chain control. Based on numerical analyses of the injection molding process, a surrogate model is developed. It enables a fast prediction of the product quality based on the temperature history. The physical model is transferred to an agent-based process chain simulation identifying lead time, bottle necks and quality rates taking into account the whole process chain. In the second step of surrogate modeling, a feasible soft sensor model is derived for quality control over the process chain during the operation stage. For this specific uses case, the production rejection can be reduced by 12% compared to conventional static approaches.

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