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Grid-Enabled Mutation-Based Genetic Algorithm to Optimise Nuclear Fusion Devices

机译:基于网格的基于变异的遗传算法优化核聚变装置

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摘要

Fusion community is becoming more important as long as fusion energy is considered the next generation of energy. However, many problems are presented in fusion devices. One of these problems consists of improving the equilibrium of confined plasma. Some modelling tools can be used to improve the equilibrium, but the computational cost of these tools and the number of different configurations to simulate make impossible to perform the required tests to obtain optimal designs. With grid computing we have the computational resources needed for running all these tests and with genetic algorithms (GAs) we can look for an approximate result without exploring all the solution space. This work joins all these ideas. The obtained results are very encouraging.
机译:只要聚变能被视为下一代能源,聚变界就变得越来越重要。但是,在融合装置中存在许多问题。这些问题之一包括改善受限血浆的平衡。可以使用某些建模工具来改善平衡,但是这些工具的计算成本以及要模拟的不同配置的数量使得无法执行所需的测试以获得最佳设计。使用网格计算,我们拥有运行所有这些测试所需的计算资源,使用遗传算法(GA),我们可以寻找近似结果而无需探索所有解决方案空间。这项工作结合了所有这些想法。获得的结果非常令人鼓舞。

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