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    NURBS Strands Modeling of Prestressed Concrete Bridges 

    Source: Journal of Highway and Transportation Research and Development (English Edition):;2007:;Volume ( 002 ):;issue: 002
    Author(s): Huang Qiao; Yang Da-wei; Li Zhong-long
    Publisher: American Society of Civil Engineers
    Abstract: To establish the unified description of strands in prestressed concrete girder bridge, NURBS strands model is presented with introducing Non-Uniform Rational Basic Spline (NURBS). Prestressed strands in design and construction ...
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    Reconsideration of Problems in Transverse Distribution and Reinforcement of Beam-slab Bridge 

    Source: Journal of Highway and Transportation Research and Development (English Edition):;2009:;Volume ( 004 ):;issue: 001
    Author(s): Tang Haihong; Huang Qiao; Lin Yangzi; Zhang Shuren
    Publisher: American Society of Civil Engineers
    Abstract: Based on theoretic analysis and calculation by establishing solid finite element model, the variance between mechanical hypothesis/simplification and the real structure and the changes of transverse distribution of bridge ...
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    Failure Criterion of Ordinary Concrete Subjected to Triaxial Compression of Full Section and Local Loadings 

    Source: Journal of Materials in Civil Engineering:;2018:;Volume ( 030 ):;issue: 010
    Author(s): Yu Zhenpeng;Huang Qiao;Shan Yushi;Ren Zheng
    Publisher: American Society of Civil Engineers
    Abstract: In this paper, experiments carried out on ordinary concrete under multiaxial compression of both full section and local section are presented and the failure modes compared under different loading conditions. According to ...
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    Comparison of Random Forest and Neural Network in Modeling the Performance and Emissions of a Natural Gas Spark Ignition Engine 

    Source: Journal of Energy Resources Technology:;2022:;volume( 144 ):;issue: 003:;page 32310-1
    Author(s): Liu, Jinlong; Huang, Qiao; Ulishney, Christopher; Dumitrescu, Cosmin E.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Machine learning (ML) models can accelerate the development of efficient internal combustion engines. This study assessed the feasibility of data-driven methods toward predicting the performance of a diesel engine modified ...
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