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    Numerical Simulations of Wave–Structure–Soil Interaction of Offshore Monopiles 

    Source: International Journal of Geomechanics:;2017:;Volume ( 017 ):;issue: 001
    Author(s): Brian Sheil; William Finnegan
    Publisher: American Society of Civil Engineers
    Abstract: Ocean energy converters (OECs) are becoming a more popular source of electricity generated from the ocean. The main obstacle associated with the use of OECs is their high initial installation cost. In light of this, ...
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    Noncircular Cavity Expansion in Undrained Soil: Semi-Analytical Solution 

    Source: Journal of Engineering Mechanics:;2022:;Volume ( 148 ):;issue: 007:;page 04022032
    Author(s): Hang Zhou; Brian Sheil; Hanlong Liu
    Publisher: ASCE
    Abstract: The cavity expansion approach has been a popular tool to interpret a wide range of geotechnical problems over the last several decades. Most previous research focused on the expansion of cylindrical and/or spherical cavities, ...
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    Multifidelity Constitutive Modeling of Stress-Induced Anisotropic Behavior of Clay 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2024:;Volume ( 150 ):;issue: 003:;page 04024003-1
    Author(s): Pin Zhang; Zhen-Yu Yin; Brian Sheil
    Publisher: ASCE
    Abstract: Rigorous modeling of the stress-induced anisotropy of soils with different stress histories and loading conditions typically requires advanced constitutive models. However, calibration of state-of-the-art constitutive ...
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    Bayesian Optimization for CPT-Based Prediction of Impact Pile Drivability 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2023:;Volume ( 149 ):;issue: 011:;page 04023100-1
    Author(s): Róisín Buckley; Yuling Max Chen; Brian Sheil; Stephen Suryasentana; Diarmid Xu; James Doherty; Mark Randolph
    Publisher: ASCE
    Abstract: Pile drivability predictions require information on the pile geometry, impact hammer, and the soil resistance to driving (SRD). Current SRD prediction methods are based on databases of long slender piles from the oil and ...
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    Physics-Informed Multifidelity Residual Neural Networks for Hydromechanical Modeling of Granular Soils and Foundation Considering Internal Erosion 

    Source: Journal of Engineering Mechanics:;2022:;Volume ( 148 ):;issue: 004:;page 04022015
    Author(s): Pin Zhang; Zhen-Yu Yin; Yin-Fu Jin; Jie Yang; Brian Sheil
    Publisher: ASCE
    Abstract: Coupled hydromechanical finite-element modeling of granular soils, taking into account internal erosion, is computationally prohibitive. Alternative data-driven approaches require large data sets for training and often ...
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