Sparse identification of multiphase turbulence closures for coupled fluid–particle flows – CORRIGENDUM
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Fluid Mechanics"
DOI: 10.1017/jfm.2021.316
Abstract: In this work, model closures of the multiphase Reynolds-Average Navier-Stokes (RANS) equations are developed for homogeneous, fully-developed gas--particle flows. To date, the majority of RANS closures are based on extensions of single-phase turbulence models, which… read more here.
Keywords: identification multiphase; turbulence; sparse identification; particle ... See more keywords
A Levenberg-Marquardt algorithm for sparse identification of dynamical systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3157963
Abstract: Low complexity of a system model is essential for its use in real-time applications. However, sparse identification methods commonly have stringent requirements that exclude them from being applied in an industrial setting. In this article,… read more here.
Keywords: sparse identification; identification; marquardt algorithm; identification dynamical ... See more keywords
Error-Triggered Adaptive Sparse Identification for Predictive Control and Its Application to Multiple Operating Conditions Processes.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3262541
Abstract: With the digital transformation of process manufacturing, identifying the system model from process data and then applying to predictive control has become the most dominant approach in process control. However, the controlled plant often operates… read more here.
Keywords: sparse identification; control; error triggered; predictive control ... See more keywords
Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Immunology"
DOI: 10.3389/fimmu.2023.1115536
Abstract: In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge first on… read more here.
Keywords: cell; sparse identification; car; data driven ... See more keywords