Published November 2021 | Version v1
Journal article

Optimization of the gravity support in CFETR vacuum vessel

  • 1. Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui 230031 (China)
  • 2. University of Science and Technology of China, Hefei, Anhui 230026 (China)

Description

Highlights: • An optimization procedure for the gravity supports of CFETR VV is described. • Design optimization is developed with Multi-Objective Genetic Algorithm (MOGA). • Single plate support design is proposed as an alternative design. • Proposed design has 120.6% increased buckling load factor and 24.7% reduced maximum stress compared with the initial design. The China Fusion Engineering Test Reactor (CFETR) is developed as the next tokamak device in China. The gravity support of CFETR VV is designed with a flexible plate structure to allow radial thermal expansion of the vacuum vessel (VV) system and to withstand various design loads. In this paper, the design optimization is developed with Multi-Objective Genetic Algorithm (MOGA) to balance design parameters contributing to stability and strength for the VV gravity support. In this optimization procedure, a parametric FE model is generated to study the structural response of the support corresponding to each design point. Besides, the effects of the design variables on objective function are quantitatively assessed using sensitivity analysis. Through the optimization procedure, optimal design parameters of the VV gravity support are obtained. Compared to the initial design, an improvement of about 50.4 and 401% for the peak stress and buckling load factor of the support plates, respectively.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.fusengdes.2021.112921

Additional details

Identifiers

DOI
10.1016/j.fusengdes.2021.112921;
PII
S0920379621006979;

Publishing Information

Journal Title
Fusion Engineering and Design
Journal Volume
172
Journal Page Range
vp.
ISSN
0920-3796
CODEN
FEDEEE

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.