Research on the efficient process-oriented structural optimization method of the large-scale vacuum cryostat for fusion reactors

被引:0
|
作者
Yu, Qingzhou [1 ,2 ]
Xu, Hao [1 ]
Chen, Zhaoxi [1 ]
Yang, Qingxi [1 ]
机构
[1] Chinese Acad Sci, Hefei Inst Phys Sci, Inst Plasma Phys, Hefei 230031, Peoples R China
[2] Univ Sci & Technol China, Hefei 230026, Peoples R China
关键词
vacuum cryostat; CERS; parametric modeling; response surface optimization; structural integrity analysis; TF COIL STRUCTURE; DESIGN OPTIMIZATION; CONCEPTUAL DESIGN; 1ST WALL; ITER; SUPPORT; VESSEL; PERFORMANCE;
D O I
10.1088/1741-4326/ad4ef2
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
An efficient optimization design for the large and complex components of fusion reactors is crucial to address the engineering design requirements and further promote technical standardization. Based on research status, current engineering designs for fusion reactors have some deficiencies, such as time and energy wastage, inefficiency, and difficulties in covering the typical 'multi-variable multi-objective' design requirements. These are pressing and common problems that urgently need to be overcome. To deal with the aforementioned technical challenges, it is vitally important to design an efficient, precise, and normalized approach that is tailored for the development of future fusion reactors. Therefore, this paper proposes a process-oriented optimization design method, which involves Coupled external parameterized modeling, Experimental points design, Response surface optimization, and Structural integrity validation (CERS), to improve the currently inefficient design methods. And the vacuum cryostat, the largest and complex component of a tokamak, is taken as an example to present the basic procedures of CERS. Firstly, the functions, basic structures, load types, analysis methods, and verification criteria of the cryostat are presented in detail. Then, real-time data interaction between external global parametric variables and ANSYS via coupling is established by CERS, which achieves parametric modeling of the cryostat and efficient experimental point design and optimization analysis with multi-variables and multi-objectives in an automatic way. Subsequently, this study demonstrates the significance and sensitivity of various structural parameters of the cryostat from such objectives as maximum deformation, maximum equivalent stress, and total mass. And the optimal set of its structural parameters is obtained by establishing a mathematical optimization model. Finally, the structural integrity is verified. The results indicate that the optimized cryostat maintains a minimum safety margin of 23% and will not suffer fatigue damage under various load events during its service. Moreover, the nonlinear buckling load multiplier & empty; is 5.4, obtained by analyzing the load-displacement curve of the cryostat according to the zero-curvature criterion. This shows that the designed cryostat is stable enough. The proposed method is simple, efficient, and reliable, and can be applied to both the cryostat and other complex components of fusion reactors in engineering design fields. It has great value of practical technical reference and can further promote the standardization of engineering design technology for future fusion reactors.
引用
收藏
页数:16
相关论文
共 40 条
  • [1] Efficient large-scale process-oriented parallel simulations
    Perumalla, KS
    Fujimoto, RM
    [J]. 1998 WINTER SIMULATION CONFERENCE PROCEEDINGS, VOLS 1 AND 2, 1998, : 459 - 466
  • [2] EFFICIENT TREATMENT OF CONSTRAINTS IN LARGE-SCALE STRUCTURAL OPTIMIZATION
    ARORA, JS
    HAUG, EJ
    RAJAN, SD
    [J]. ENGINEERING OPTIMIZATION, 1981, 5 (02) : 105 - 120
  • [3] How engineering data management and system support the main process-oriented functions of a large-scale project
    Hameri, AP
    Nikkola, J
    [J]. PRODUCTION PLANNING & CONTROL, 1999, 10 (05) : 404 - 413
  • [4] How engineering data management and system support the main process-oriented functions of a large-scale project
    Hameri, Ari-Pekka
    Nikkola, Juho
    [J]. Production Planning and Control, 10 (05): : 404 - 413
  • [5] Efficient Sparse Large-Scale Multiobjective Optimization Based on Cross-Scale Knowledge Fusion
    Ding, Zhuanlian
    Chen, Lei
    Sun, Dengdi
    Zhang, Xingyi
    Liu, Wei
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2024,
  • [6] Process-oriented realisation of projects within large-scale plant engineering - Recommended fields of action and approaches for solution
    Domagk, Martin
    Riedel, Ralph
    Müller, Egon
    [J]. ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 2013, 108 (06): : 426 - 429
  • [7] An efficient gradient method with approximate optimal stepsize for large-scale unconstrained optimization
    Liu, Zexian
    Liu, Hongwei
    [J]. NUMERICAL ALGORITHMS, 2018, 78 (01) : 21 - 39
  • [8] Gene Targeting Differential Evolution: A Simple and Efficient Method for Large-Scale Optimization
    Wang, Zi-Jia
    Jian, Jun-Rong
    Zhan, Zhi-Hui
    Li, Yun
    Kwong, Sam
    Zhang, Jun
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2023, 27 (04) : 964 - 979
  • [9] An efficient conjugate direction method with orthogonalization for large-scale quadratic optimization problems
    Boudinov, Edouard R.
    Manevich, Arkadiy I.
    [J]. OPTIMIZATION METHODS & SOFTWARE, 2007, 22 (02): : 309 - 328
  • [10] An Efficient Fisher Matrix Approximation Method for Large-Scale Neural Network Optimization
    Yang, Minghan
    Xu, Dong
    Cui, Qiwen
    Wen, Zaiwen
    Xu, Pengxiang
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 45 (05) : 5391 - 5403