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Modular gas-cooled reactor core optimal design and additive manufacturing performance based on SiC matrix dispersed with TRi-structural ISOtropic fuel

Author

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  • Lu, Qi
  • Han, Wenbin
  • Deng, Jian
  • Li, Hongbo
  • Wei, Zonglan

Abstract

High-temperature gas-cooled reactors present significant technical competitiveness in various fields, such as low-carbon electricity, thermal energy, and hydrogen supply. Silicon Carbide (SiC) matrix dispersed with TRi-structural ISOtropic (TRISO) particle fuel is characterized by high-temperature tolerance, radiation resistance, and good neutron economy, which has emerged as a pivotal technological pathway for reactor core design. With the rapid advancement of SiC Additive Manufacturing (AM) technology, there is a substantial increase in core design flexibility, and an innovative gas-cooled reactor design was proposed by Monte Carlo (MC) method in this paper. The Non-uniform Rational B-spline (NURBS), Latin Hypercube Sampling (LHS), second-order polynomial response surface, as well as Genetic Algorithm (GA) were coupled to realize the optimization design for the coolant channel. Besides, a modular fuel design was proposed, and the AM SiC shell was fabricated using Binder Jetting (BJ) technology. Furthermore, the densification of the AM SiC shell and the matrix with SiC powder and SiC microspheres (TRISO simulator) was investigated by Chemical Vapor Infiltration (CVI). Finally, the microscopic morphology analysis and thermal-mechanical performance characterization of the samples were conducted, which demonstrated the technical feasibility and advanced capabilities of the SiC matrix dispersed with TRISO fuel based on AM technology.

Suggested Citation

  • Lu, Qi & Han, Wenbin & Deng, Jian & Li, Hongbo & Wei, Zonglan, 2024. "Modular gas-cooled reactor core optimal design and additive manufacturing performance based on SiC matrix dispersed with TRi-structural ISOtropic fuel," Energy, Elsevier, vol. 308(C).
    • Handle: RePEc:eee:energy:v:308:y:2024:i:c:s0360544224026112
    DOI: 10.1016/j.energy.2024.132837
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    as
    1. Kumar, Nitesh & Basu, Dipankar N., 2023. "Thermalhydraulic assessment and design optimization of incorporating flow obstructors in a supercritical minichannel heat sink," Applied Energy, Elsevier, vol. 349(C).
    2. Merk, Bruno & Stanculescu, Alexander & Chellapandi, Perumal & Hill, Robert, 2015. "Progress in reliability of fast reactor operation and new trends to increased inherent safety," Applied Energy, Elsevier, vol. 147(C), pages 104-116.
    3. He, Wei & Zhang, Jifang & Guo, Rui & Pei, Chenchen & Li, Hailong & Liu, Shengchun & Wei, Jie & Wang, Yulin, 2022. "Performance analysis and structural optimization of a finned liquid-cooling radiator for chip heat dissipation," Applied Energy, Elsevier, vol. 327(C).
    4. Sun, Jinxiang & Zhang, Ruibo & Wang, Mingjun & Zhang, Jing & Qiu, Suizheng & Tian, Wenxi & Su, G.H., 2022. "Multi-objective optimization of helical coil steam generator in high temperature gas reactors with genetic algorithm and response surface method," Energy, Elsevier, vol. 259(C).
    5. Verma, Ashima & Saikia, Tanmoy & Saikia, Pranaynil & Rakshit, Dibakar & Ugalde-Loo, Carlos E., 2023. "Thermal performance analysis and experimental verification of lithium-ion batteries for electric vehicle applications through optimized inclined mini-channels," Applied Energy, Elsevier, vol. 335(C).
    6. Xia, Yang & Chen, Li & Luo, Jiwang & Tao, Wenquan, 2023. "Numerical investigation of microchannel heat sinks with different inlets and outlets based on topology optimization," Applied Energy, Elsevier, vol. 330(PA).
    7. Ni, Hang & Qu, Xinhe & Zhao, Gang & Zhang, Ping & Peng, Wei, 2024. "Research on two novel hydrogen-electricity-heat polygeneration systems using very-high-temperature gas-cooled reactor and hybrid-sulfur cycle," Energy, Elsevier, vol. 290(C).
    8. Stewart, W.R. & Velez-Lopez, E. & Wiser, R. & Shirvan, K., 2021. "Economic solution for low carbon process heat: A horizontal, compact high temperature gas reactor," Applied Energy, Elsevier, vol. 304(C).
    9. Asuega, Anthony & Limb, Braden J. & Quinn, Jason C., 2023. "Techno-economic analysis of advanced small modular nuclear reactors," Applied Energy, Elsevier, vol. 334(C).
    10. Cai, Genchun & Liang, Yunmin & Liu, Zhichun & Liu, Wei, 2020. "Design and optimization of bio-inspired wave-like channel for a PEM fuel cell applying genetic algorithm," Energy, Elsevier, vol. 192(C).
    11. Steigerwald, Björn & Weibezahn, Jens & Slowik, Martin & von Hirschhausen, Christian, 2023. "Uncertainties in estimating production costs of future nuclear technologies: A model-based analysis of small modular reactors," Energy, Elsevier, vol. 281(C).
    12. Velásquez, Laura & Posada, Alejandro & Chica, Edwin, 2023. "Surrogate modeling method for multi-objective optimization of the inlet channel and the basin of a gravitational water vortex hydraulic turbine," Applied Energy, Elsevier, vol. 330(PB).
    13. Li, Wei & Shirvan, Koroush & Harrison, Shay & Pegna, Joseph, 2020. "Innovative accident tolerant fuel concept enabled through direct manufacturing technology," Applied Energy, Elsevier, vol. 264(C).
    Full references (including those not matched with items on IDEAS)

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