Machine learning aided multiscale mechanics of fiber suspensions

Name: Machine learning aided multiscale mechanics of fiber suspensions
Brand: Karlsruher Institut für Technologie
Availability: OutOfStock
Rating: 5 (1 reviews)

By Benedikt Sterr

0 - Default Title

Description

We present a Fast-Fourier-Transform (FFT) based computational approach to computing the viscous stress response of rigid fibers suspended in a non-Newtonian medium. We identify closed-form models for the fiber suspension viscosity from data obtained with the FFT-based computational approach by leveraging supervised machine learning techniques. Furthermore, we present a novel Deep Material Network architecture capable of treating suspensions of rigid particles with high computational efficiency.

Product details

Binding:

Paperback

Edition:

1

Number of Pages:

206

Release Date:

2025-11-24

Publication Date:

2025-11-24

Publisher:

Karlsruher Institut für Technologie

Languages:

Original: English

ISBN10:

3731514214

ISBN13:

9783731514213

Weight:

306 g

Height:

148 cm

Width:

210 cm

Thickness:

13 cm

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