Machine learning-based multi-objective optimization and physical-geometrical competitive mechanisms for 3D woven thermal protection composites-Reference-Cited by-同舟云学术

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Machine learning-based multi-objective optimization and physical-geometrical competitive mechanisms for 3D woven thermal protection composites

Published:2024-11 Issue: Volume:232 Page:125920
ISSN:0017-9310
Container-title:International Journal of Heat and Mass Transfer
language:en
Short-container-title:International Journal of Heat and Mass Transfer

Author:

Liang Haoran^ORCID,Li Weijie,Li Yu,Li Ying

Publisher

Elsevier BV

Reference58 articles.

1. Roughness induced heat transfer and shear stress augmentation measurements of the HEEET thermal protection system;Hambidge,2024

2. Mechanical, thermal insulation, and ablation behaviors of needle-punched fabric reinforced nanoporous phenolic composites: the role of anisotropic microstructure;Cai;Compos. Sci. Technol.,2024

3. The design of special woven-preformed structures for the high-performance film cooling with undamaged fibers based on 2.5D ceramic matrix composites;Zhao;Compos. Struct.,2022

4. Multi-scale collaborative design method for macroscopic thermal optimization and mesoscopic woven structure of hypersonic vehicle's TOCMC leading edge;ZHAO;Chin. J. Aeronaut.,2024

5. Study on the ablation performance of SiC-coated high thermal conductivity three-dimensional C/C composites;Zhang;J. Eur. Ceram. Soc.,2024

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