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    Optimization and Uncertainty Analysis of a Diesel Engine Operating Point Using Computational Fluid Dynamics 

    Source: Journal of Engineering for Gas Turbines and Power:;2018:;volume( 140 ):;issue: 010:;page 102806
    Author(s): Probst, Daniel M.; Senecal, Peter K.; Chien, Peter Z.; Xu, Max X.; Leyde, Brian P.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This study describes the use of an analytical model, constructed using sequential design of experiments (DOEs), to optimize and quantify the uncertainty of a diesel engine operating point. A genetic algorithm (GA) was also ...
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    Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators 

    Source: Journal of Engineering for Gas Turbines and Power:;2019:;volume( 141 ):;issue: 009:;page 91011
    Author(s): Probst, Daniel M.; Raju, Mandhapati; Senecal, Peter K.; Kodavasal, Janardhan; Pal, Pinaki; Som, Sibendu; Moiz, Ahmed A.; Pei, Yuanjiang
    Publisher: American Society of Mechanical Engineers (ASME)
    Abstract: This work evaluates different optimization algorithms for computational fluid dynamics (CFD) simulations of engine combustion. Due to the computational expense of CFD simulations, emulators built with machine learning ...
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    Piston Bowl Geometry Effects on Gasoline Compression Ignition in a Heavy-Duty Diesel Engine 

    Source: Journal of Energy Resources Technology:;2021:;volume( 143 ):;issue: 006:;page 062309-1
    Author(s): Tang, Meng; Pei, Yuanjiang; Guo, Hengjie; Zhang, Yu; Torelli, Roberto; Probst, Daniel; Fütterer, Carsten; Traver, Michael
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A design optimization campaign was conducted to search for improved combustion profiles that enhance gasoline compression ignition in a heavy-duty diesel engine with a geometric compression ratio of 17.3. A large-scale ...
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