Carbon Carbon(C/C)composites in thermal-protection system are exposed to severe thermochemical ablation and mechanical erosion,and their thermal-protection performance is of vital importance to the structural safety a...Carbon Carbon(C/C)composites in thermal-protection system are exposed to severe thermochemical ablation and mechanical erosion,and their thermal-protection performance is of vital importance to the structural safety and flight status of hypersonic vehicles.We numerically analyzes the mesoscopic ablation-erosion of C/C Composites with Inclined Fibers(CCIF).First,a thermochemical ablation model describing the reaction-diffusion coupled problem of C/C composites on mesoscale is employed to analyze ablative process,and the corresponding surface ablation morphology is obtained.Then,the ablation morphology of CCIF is taken as the geometrical model for mechanical erosion analysis,and their damage and failure behavior under high-speed airflow shear is analyzed by using progressive damage method.Moreover,the effects of fiber inclined angle and airflow direction on the mechanical erosion of CCIF are investigated,and the ablationerosion behavior is analyzed and discussed.The results show that the failure modes of mechanical erosion in inner and edge regions are obviously different,showing granular and block erosion phenomena respectively.The mechanical erosion of CCIF in the direction of reverse flow is easier than that in the direction of forward flow.These results can provide a theoretical basis for the design and optimization of thermal protection system materials.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/342/suppl/C Volume 342,1 September 2025[OA](1)Experimental validation of neural network-based prediction of natural ventilation bulk airflow rate by Jo ao...https://www.sciencedirect.com/journal/energy-and-buildings/vol/342/suppl/C Volume 342,1 September 2025[OA](1)Experimental validation of neural network-based prediction of natural ventilation bulk airflow rate by Jo ao Carlos Sim oes,Guilherme Carrilho da Graca,Article115871Abstract:To fully exploit natural ventilation(NV)as an energysaving strategy in mixed-mode buildings,accurate real-time prediction of NV airflow rates is essential.Current approaches for NV airflow rates prediction often rely heavily on expertise knowledge and computationally demanding methods such as Computational Fluid Dynamics(CFD)as well as expensive and complex direct airflow measurements.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U2241240,12172045 and 12221002)the Opening Fund of State Key Laboratory of Explosion Science and Technology of Beijing Institute of Technology,China(No.ZDKT23-02)。
文摘Carbon Carbon(C/C)composites in thermal-protection system are exposed to severe thermochemical ablation and mechanical erosion,and their thermal-protection performance is of vital importance to the structural safety and flight status of hypersonic vehicles.We numerically analyzes the mesoscopic ablation-erosion of C/C Composites with Inclined Fibers(CCIF).First,a thermochemical ablation model describing the reaction-diffusion coupled problem of C/C composites on mesoscale is employed to analyze ablative process,and the corresponding surface ablation morphology is obtained.Then,the ablation morphology of CCIF is taken as the geometrical model for mechanical erosion analysis,and their damage and failure behavior under high-speed airflow shear is analyzed by using progressive damage method.Moreover,the effects of fiber inclined angle and airflow direction on the mechanical erosion of CCIF are investigated,and the ablationerosion behavior is analyzed and discussed.The results show that the failure modes of mechanical erosion in inner and edge regions are obviously different,showing granular and block erosion phenomena respectively.The mechanical erosion of CCIF in the direction of reverse flow is easier than that in the direction of forward flow.These results can provide a theoretical basis for the design and optimization of thermal protection system materials.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/342/suppl/C Volume 342,1 September 2025[OA](1)Experimental validation of neural network-based prediction of natural ventilation bulk airflow rate by Jo ao Carlos Sim oes,Guilherme Carrilho da Graca,Article115871Abstract:To fully exploit natural ventilation(NV)as an energysaving strategy in mixed-mode buildings,accurate real-time prediction of NV airflow rates is essential.Current approaches for NV airflow rates prediction often rely heavily on expertise knowledge and computationally demanding methods such as Computational Fluid Dynamics(CFD)as well as expensive and complex direct airflow measurements.
