Automatic model reduction of differential algebraic systems by proper orthogonal decomposition. (2nd February 2017)

• Record Type: Journal Article
• Authors: Khlopov, Dmytro; Mangold, Michael
• Is Part Of: Computers & chemical engineering. Volume 97(2017)
• Page Start: 104
• Page End: 113
• Publication Date: 2017-02-02
• Subjects: Nonlinear model reduction -- Proper orthogonal decomposition -- Empirical interpolation -- Computer aided modeling -- Differential algebraic systems; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2016.11.004
• Languages: English
• ISSNs: 0098-1354

Abstract

Abstract : Highlights: A software tool for automatic model reduction has been developed. The tool relies on combination of symbolic and numerical preprocessing. Successful reduction of distributed nonlinear test examples. Abstract: Proper orthogonal decomposition (POD) is an attractive way to obtain nonlinear low-dimensional models. This article reports on the automatization of the mentioned reduction method. An automatic procedure for the reduction of differential algebraic systems is presented, which is implemented in the modeling and simulation environment ProMoT/Diana. The software tool has been applied to a nonlinear heat conduction model and a continuous fluidized bed crystallizer model. The automatically generated reduced models are significantly smaller than the reference models, while the loss of accuracy is negligible.