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Use of EPICS and Python technology for the development of a computational toolkit for high heat flux testing of plasma facing components

机译:使用EPICS和Python技术开发计算工具包,以对等离子组件进行高热通量测试

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The high heat flux testing and characterization of the divertor and first wall components are a challenging engineering problem of a tokamak. These components are subject to steady state and transient heat load of high magnitude. Therefore, the accurate prediction and control of the cooling parameters is crucial to prevent burnout. The prediction of the cooling parameters is based on the numerical solution of the critical heat flux (CHF) model. In a test facility for high heat flux testing of plasma facing components (PFC), the integration of computations and experimental control is an essential requirement. Experimental physics and industrial control system (EPICS) provides powerful tools for steering controls, data simulation, hardware interfacing and wider usability. Python provides an open source alternative for numerical computations and scripting. We have integrated these two open source technologies to develop a graphical software for a typical high heat flux experiment. The implementation uses EPICS based tools namely IOC (I/O controller) server, control system studio (CSS) and Python based tools namely Numpy, Scipy, Matplotlib and NOSE. EPICS and Python are integrated using PyEpics library. This toolkit is currently under operation at high heat flux test facility at Institute for Plasma Research (IPR) and is also useful for the experimental labs working in the similar research areas. The paper reports the software architectural design, implementation tools and rationale for their selection, test and validation. (C) 2016 Elsevier B.V. All rights reserved.
机译:偏滤器和第一壁组件的高热通量测试和表征是托卡马克的一个具有挑战性的工程问题。这些组件要承受稳态和高瞬态热负荷。因此,冷却参数的准确预测和控制对于防止烧坏至关重要。冷却参数的预测基于临界热通量(CHF)模型的数值解。在用于等离子体组件(PFC)的高热通量测试的测试设备中,计算和实验控制的集成是必不可少的要求。实验物理和工业控制系统(EPICS)为转向控制,数据模拟,硬件接口和更广泛的可用性提供了强大的工具。 Python为数值计算和脚本编写提供了开源替代方案。我们已经集成了这两种开源技术,以开发用于典型的高热通量实验的图形软件。该实现使用基于EPICS的工具,即IOC(I / O控制器)服务器,控制系统工作室(CSS)和基于Python的工具,即Numpy,Scipy,Matplotlib和NOSE。 EPICS和Python使用PyEpics库集成。该工具包目前正在等离子研究所(IPR)的高热通量测试设施中运行,也可用于从事类似研究领域的实验实验室。本文报告了软件架构设计,实现工具以及选择,测试和验证的原理。 (C)2016 Elsevier B.V.保留所有权利。

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