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    Differentiable Neural Operator for Temperature Field Prediction for Aerogel Thermal Insulation Materials at Large Temperature Differentials 

    Source: ASME Journal of Heat and Mass Transfer:;2026:;volume( 148 ):;issue:002
    Author(s): Zhang, Zitong; Li, Ming; Liu, Tianyuan; Pang, Haoqiang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. To address the extreme aerodynamic heating challenges encountered by the leading edges of hypersonic vehicles, this study develops an aerogel-based thermal insulation material with engineering applicability. It ...
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    Effective Thermal Conductivity Model of Micron Hollow Sphere or Phase Change Material/Opacifier-SiO2 Aerogel Composites 

    Source: ASME Journal of Heat and Mass Transfer:;2023:;volume( 145 ):;issue: 006:;page 62501-1
    Author(s): Pang, Hao-Qiang; Fan, Ting-Hui; Zhang, Sheng-Nan; Gao, Yan-Feng
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Pure SiO2 aerogel has a strong light transmittance in the infrared wavebands from 3.0 to 8.0 μm, and an opacifier could efficiently reduce aerogel's radiative thermal conductivity (λr), especially at high temperatures ...
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    Physics-Informed Deep Operator Network for Sparse-Sensor Reconstruction of Aerogel Insulator's Overall Temperature Field Under Time-Varying Aerodynamic Heating Loads 

    Source: ASME Journal of Heat and Mass Transfer:;2026:;volume( 148 ):;issue:008
    Author(s): Zhang, Zitong; Li, Ming; Shi, Guoyang; Ding, Siqi; Liu, Tianyuan; Pang, Haoqiang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. Investigating the thermal insulation properties of SiO2 aerogels under large temperature differences is crucial for the development of thermal protection materials in hypersonic vehicles. Thus, a porous medium ...
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