Foam property prediction and inception via a hybrid machine learning and model order reduction framework

Chady Ghnatios; Ilige Hage; Jose Enrico Q. Quinsaat; Daniel J. van de Pas; Richard Vendamme; Walter Eevers; Karolien Vanbroekhoven; Elias Feghali

doi:10.1186/s40323-026-00338-5

Foam property prediction and inception via a hybrid machine learning and model order reduction framework

Chady Ghnatios
, Ilige Hage
, Jose Enrico Q. Quinsaat
, Daniel J. van de Pas
, Richard Vendamme
, Walter Eevers
, Karolien Vanbroekhoven
, Elias Feghali

School of Engineering

University of Antwerp

Producción científica: Article › revisión exhaustiva

Idioma original	English
Número de artículo	18
Publicación	Advanced Modeling and Simulation in Engineering Sciences
Volumen	13
N.º	1
DOI	https://doi.org/10.1186/s40323-026-00338-5
Estado	Published - dic 2026

ASJC Scopus Subject Areas

Modeling and Simulation
Engineering (miscellaneous)
Computer Science Applications
Applied Mathematics

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title = "Foam property prediction and inception via a hybrid machine learning and model order reduction framework",

keywords = "Generative design, Learnable kernel principal component analysis, Non linear model order reduction, Polyurethane rigid foam generation, Rank reduction autoencoder, Variational rank reduction autoencoder",

author = "Chady Ghnatios and Ilige Hage and Quinsaat, \{Jose Enrico Q.\} and \{van de Pas\}, \{Daniel J.\} and Richard Vendamme and Walter Eevers and Karolien Vanbroekhoven and Elias Feghali",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2026.",

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language = "English",

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AU - Ghnatios, Chady

AU - Hage, Ilige

AU - Quinsaat, Jose Enrico Q.

AU - van de Pas, Daniel J.

AU - Vendamme, Richard

AU - Eevers, Walter

AU - Vanbroekhoven, Karolien

AU - Feghali, Elias

N1 - Publisher Copyright: © The Author(s) 2026.

PY - 2026/12

Y1 - 2026/12

KW - Generative design

KW - Learnable kernel principal component analysis

KW - Non linear model order reduction

KW - Polyurethane rigid foam generation

KW - Rank reduction autoencoder

KW - Variational rank reduction autoencoder

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UR - https://www.scopus.com/pages/publications/105046898296#tab=citedBy

U2 - 10.1186/s40323-026-00338-5

DO - 10.1186/s40323-026-00338-5

M3 - Article

AN - SCOPUS:105046898296

VL - 13

JO - Advanced Modeling and Simulation in Engineering Sciences

JF - Advanced Modeling and Simulation in Engineering Sciences

IS - 1

M1 - 18

ER -

Foam property prediction and inception via a hybrid machine learning and model order reduction framework

ASJC Scopus Subject Areas

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