Gianmarco Aversano | Researchain

Archive Network Publication Hotspot Collaboration

Hotspot

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2017 (ICCMSE-2017) | 2017

On the application of POD to the study of flames

Gianmarco Aversano; Katarzyna Bizon; Gaetano Continillo; Lucia Russo

This paper deals with the application of Proper Orthogonal Decomposition (POD) to the analysis of flame phenomena. POD is used in combustion both as a powerful means of extracting the main features of flame phenomena from massive experimental data consisting of high-definition, high sampling rate image sequences, and as a means of construction of reduced order models. Both applications are illustrated, with more emphasis on the model reduction procedure with reference to a one-dimensional laminar propagating gas flame; open issues are addressed, and results computed by means of reduced models are compared with full model simulations.

Fuel | 2017

Application of Reduced-Order models based on the combination of PCA & Kriging on 1D flames

Gianmarco Aversano; Alessandro Parente; Olivier Gicquel; Axel Coussement

Proceedings of the Combustion Institute | 2018

PCA and Kriging for the efficient exploration of consistency regions in Uncertainty Quantification

Gianmarco Aversano; John Parra-Alvarez; Benjamin Isaac; Sean T. Smith; Axel Coussement; Olivier Gicquel; Alessandro Parente

Energy & Fuels | 2018

Optimization of Chemical Kinetics for Methane and Biomass Pyrolysis Products in Moderate or Intense Low-Oxygen Dilution Combustion

Magnus Fürst; P. Sabia; Marco Lubrano Lavadera; Gianmarco Aversano; Mara de Joannon; Alessio Frassoldati; Alessandro Parente

Computers & Chemical Engineering | 2018

Application of Reduced-Order Models based on PCA & Kriging for the development of digital twins of reacting flow applications

Gianmarco Aversano; Aurélie Bellemans; Z. Li; Axel Coussement; O. Gicquel; Alessandro Parente

Computers & Chemical Engineering | 2018

Feature extraction and reduced-order modelling of nitrogen plasma models using principal component analysis

Aurélie Bellemans; Gianmarco Aversano; Axel Coussement; Alessandro Parente

Archive | 2017

Reduced-order models for uncertainty quantification studies in large-scale applications

Gianmarco Aversano; Alessandro Parente; Sean T. Smith; Benjamin Isaac; Olivier Gicquel

Archive | 2016

PCA & Kriging for model reduction

Gianmarco Aversano; Alessandro Parente

Archive | 2016

Numerical simulation of novel combustion technologies

Gianmarco Aversano; Magnus Fürst; Zhiyi Li; Mohammad Rafi Malik; Alessandro Parente

Archive | 2016

PCA & Kriging For Surrogate Models

Gianmarco Aversano; Alessandro Parente

Explore More