Assessment of an Identification Strategy for the Prediction of the Dynamics of Two-phase Flows. (December 2015)

• Record Type: Journal Article
• Authors: Fichera, A.; Pagano, A.
• Is Part Of: Energy procedia. Volume 82(2015)
• Page Start: 316
• Page End: 321
• Publication Date: 2015-12
• Subjects: Two-phase flow -- NARMAX identification strategy -- predictive neural model ;; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2015.12.039
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The present study aims at assessing a flexible and light modeling methodology specifically oriented to the short-term prediction of the dynamics of the void fraction of experimental two-phase flows. The proposed strategy consists in the assessment and optimisation of a generalised NARMAX model for the input-output identification of the dynamics of the experimental time series of the void fraction, detected through a high resolution resistive probe during an extensive experimental campaign. Such a model has been implemented by means of Multilayer Perceptron artificial neural networks, trained using input-output data detected during experiments expressing different flow patterns. Reported results show that a satisfactory agreement is reached between simulated and experimental data, showing that the model is able to predict two-phase flow dynamics.