Abstract

The physical design of the fusion target is an important part of controlled thermonuclear fusion, and the geometric model and material selection of the target is also critical to achieving fusion ignition. We have modularised the target and introduced digital modeling, edge computing, and deep learning technologies to build a data-driven hybrid computing framework. We construct physical models and integrate them into a unified digital model of a multi-domain system; simulate and iteratively modify the physical model, and use edge computing technologies for information modeling. Edge computing is well applied to the calculation of each module of the target. Each module is both correlated and independent, and the values of the fusion ignition temperature and density achieved in the target are obtained, and the neutron products in the ignition and main fuel regions are 1016 - 1017 and 1019 respectively. This will be an important reference value for the design of actual fusion targets.

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