Pyrokinetics - A Python library to standardise gyrokinetic analysis

B. Patel, Peter Hill, Liam Pattinson, M. Giacomin, A. Bokshi, Daniel Kennedy, H. Dudding, J. Parisi, Tom F. Neiser, Ajay C. Jayalekshmi, David Dickinson, Juan Ruiz Ruiz
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引用次数: 1

Abstract

Fusion energy offers the potential for a near limitless source of low-carbon energy and is often regarded as a solution for the world’s long-term energy needs. To realise such a scenario requires the design of high-performance fusion reactors capable of maintaining the extreme conditions necessary to enable fusion. Turbulence is typically the dominant source of transport in magnetically-confined fusion plasmas, accounting for the majority of the particle and heat losses. Gyrokinetic modelling aims to quantify the level of turbulent transport encountered in fusion reactors and can be used to understand the major drivers of turbulence. The realisation of fusion critically depends on understanding how to mitigate turbulent transport, and thus requires high levels of confidence in the predictive tools being employed. Many different gyrokinetic modelling codes are available and Pyrokinetics aims to standardise the analysis of such computationally demanding simulations
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Pyrokinetics - 用于标准化动力学分析的 Python 库
聚变能提供了近乎无限的低碳能源,通常被视为解决世界长期能源需求的方案。要实现这一设想,需要设计出能够维持聚变所需的极端条件的高性能聚变反应堆。湍流通常是磁约束聚变等离子体中的主要传输源,占粒子和热损失的绝大部分。陀螺动力学建模旨在量化聚变反应堆中遇到的湍流传输水平,并可用于了解湍流的主要驱动因素。核聚变的实现在很大程度上取决于对如何减缓湍流传输的理解,因此需要对所使用的预测工具有高度的信心。目前有许多不同的陀螺动力学建模代码,Pyrokinetics 的目标是使这些计算要求极高的模拟分析标准化。
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