A Data-Driven Space-Time-Parameter Reduced-Order Model with Manifold Learning for Coupled Problems: Application to Deformable Capsules Flowing in Microchannels

A Data-Driven Space-Time-Parameter Reduced-Order Model with Manifold Learning for Coupled Problems: Application to Deformable Capsules Flowing in Microchannels

An innovative data-driven model-order reduction technique is proposed to model dilute micrometric or nanometric suspensions of microcapsules, i.e., microdrops protected in a thin hyperelastic membrane, which are used in Healthcare as innovative drug vehicles. We consider a microcapsule flowing in a...

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Bibliographic Details
Main Authors: Toufik Boubehziz, Carlos Quesada-Granja, Claire Dupont, Pierre Villon, Florian De Vuyst, Anne-Virginie Salsac
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Entropy
Subjects:
data-driven model
model order reduction
proper orthogonal decomposition
manifold learning
diffuse approximation
microcapsule suspension
Online Access:https://www.mdpi.com/1099-4300/23/9/1193

Internet

https://www.mdpi.com/1099-4300/23/9/1193

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