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    A Coarse-Grained Regularization Method of Convolutional Kernel for Molten Pool Defect Identification 

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 002
    Author(s): Liu, Tianyuan; Bao, Jinsong; Wang, Junliang; Zhang, Yiming
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Machine vision has a wide range of applications in the field of welding. The rise of convolutional neural network (CNN) provides a new way to extract visual features of welding. Due to the limitation of the small size of ...
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    Fast Reconstruction Method of the Stress Field for the Steam Turbine Rotor Based on Deep Fully Convolutional Network 

    Source: Journal of Engineering for Gas Turbines and Power:;2021:;volume( 144 ):;issue: 002:;page 21023-1
    Author(s): Guo, Ding; Liu, Tianyuan; Zhang, Di; Xie, Yonghui
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Since it is difficult to directly measure the transient stress of a steam turbine rotor in operation, a rotor stress field reconstruction model based on the deep fully convolutional network for the startup process is ...
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    Water Droplet Erosion Life Prediction Method for Steam Turbine Blade Materials Based on Image Recognition and Machine Learning 

    Source: Journal of Engineering for Gas Turbines and Power:;2021:;volume( 143 ):;issue: 003:;page 031009-1
    Author(s): Zhang, Zheyuan; Liu, Tianyuan; Zhang, Di; Xie, Yonghui
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, a method for predicting remaining useful life (RUL) of turbine blade under water droplet erosion (WDE) based on image recognition and machine learning is presented. Using the experimental rig for testing the ...
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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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    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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