Journal
COMPUTERS & CHEMICAL ENGINEERING
Volume 112, Issue -, Pages 92-100Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2018.02.004
Keywords
Proper orthogonal decomposition; Galerkin's projection; Moving boundary problems; Nonlinear model order reduction; Naive elastic net; Hydraulic fracturing
Funding
- Artie McFerrin department of chemical engineering
- Texas A&M Energy Institute
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Developing reduced-order models for nonlinear parabolic partial differential equation (PDE) systems with time-varying spatial domains remains a key challenge as the dominant spatial patterns of the system change with time. To address this issue, there have been several studies where the time-varying spatial domain is transformed to the time-invariant spatial domain by using an analytical expression that describes how the spatial domain changes with time. However, this information is not available in many real-world applications, and therefore, the approach is not generally applicable. To overcome this challenge, we introduce sparse proper orthogonal decomposition (SPOD)-Galerkin methodology that exploits the key features of ridge and lasso regularization techniques for the model order reduction of such systems. This methodology is successfully applied to a hydraulic fracturing process, and a series of simulation results indicates that it is more accurate in approximating the original nonlinear system than the standard POD-Galerkin methodology. Published by Elsevier Ltd.
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