Apr 26, 2024 · This work proposes a physics-informed neural network (PINN) named PINN-CHK designed for cement hydration kinetics, to predict early-age temperature rises in ...
Oct 13, 2023 · This study introduces the Physics-Informed Neural Network for Cement Hydration Kinetics (PINN-CHK) to investigate early-age temperature rises in ...
Apr 26, 2024 · This study introduces the Physics-Informed Neural Network for Cement Hydration Kinetics (PINN-CHK) to investigate early-age temperature rises in ...
Oct 17, 2023 · Abstract. Cement hydration kinetics, characterized by heat generation in early concrete stages, poses a modeling challenge. This.
This study introduces the Physics-Informed Neural Network for Cement Hydration Kinetics (PINN-CHK) to investigate early-age temperature rises in cement paste.
PINN-CHK leverages data-driven solutions to craft a high-fidelity prediction model, encompassing material properties and maturity functions in cement hydration.
Apr 26, 2024 · In this paper, we introduce techniques from Linear Algebra to model neural network layers as maps between signal spaces. First, we demonstrate ...
PINN-CHK: physics-informed neural network for high-fidelity prediction of early-age cement hydration kinetics. Download. Open Access.
Machine learning for high-fidelity prediction of cement hydration ...
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This study presents a deep learning (DL) model capable of producing a priori, high-fidelity predictions of composition- and time-dependent hydration ...
PINN-CHK: physics-informed neural network for high-fidelity prediction of early-age cement hydration kinetics. Download. Open Access. Neural Computing & ...