A data-driven multiscale theory for modeling damage and fracture of composite materials

Modesar Shakoor; Jiaying Gao; Zeliang Liu; Wing K Liu

doi:10.1007/978-3-030-15119-5_8

A data-driven multiscale theory for modeling damage and fracture of composite materials

Modesar Shakoor, Jiaying Gao, Zeliang Liu, Wing K Liu^*

^*Corresponding author for this work

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The advent of advanced processing and manufacturing techniques has led to new material classes with complex microstructures across scales from nanometers to meters. In this paper, a data-driven computational framework for the analysis of these complex material systems is presented. A mechanistic concurrent multiscale method called Self-consistent Clustering Analysis (SCA) is developed for general inelastic heterogeneous material systems. The efficiency of SCA is achieved via data compression algorithms which group local microstructures into clusters during the training stage, thereby reducing required computational expense. Its accuracy is guaranteed by introducing a self-consistent method for solving the Lippmann–Schwinger integral equation in the prediction stage. The proposed framework is illustrated for a composite cutting process where fracture can be analyzed simultaneously at the microstructure and part scales.

Original language	English (US)
Title of host publication	Meshfree Methods for Partial Differential Equations IX, 2017
Editors	Michael Griebel, Marc Alexander Schweitzer, Michael Griebel, Marc Alexander Schweitzer
Publisher	Springer Verlag
Pages	135-148
Number of pages	14
ISBN (Print)	9783030151188
DOIs	https://doi.org/10.1007/978-3-030-15119-5_8
State	Published - Jan 1 2019
Event	9th International Workshop on Meshfree Methods for Partial Differential Equations, IWMMPDE 2017 - Bonn, Germany Duration: Sep 18 2017 → Sep 20 2017

Publication series

Name	Lecture Notes in Computational Science and Engineering
Volume	129
ISSN (Print)	1439-7358

Conference

Conference	9th International Workshop on Meshfree Methods for Partial Differential Equations, IWMMPDE 2017
Country	Germany
City	Bonn
Period	9/18/17 → 9/20/17

ASJC Scopus subject areas

Modeling and Simulation
Engineering(all)
Discrete Mathematics and Combinatorics
Control and Optimization
Computational Mathematics

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Shakoor, M., Gao, J., Liu, Z., & Liu, W. K. (2019). A data-driven multiscale theory for modeling damage and fracture of composite materials. In M. Griebel, M. A. Schweitzer, M. Griebel, & M. A. Schweitzer (Eds.), Meshfree Methods for Partial Differential Equations IX, 2017 (pp. 135-148). (Lecture Notes in Computational Science and Engineering; Vol. 129). Springer Verlag. https://doi.org/10.1007/978-3-030-15119-5_8

Shakoor, Modesar ; Gao, Jiaying ; Liu, Zeliang ; Liu, Wing K. / A data-driven multiscale theory for modeling damage and fracture of composite materials. Meshfree Methods for Partial Differential Equations IX, 2017. editor / Michael Griebel ; Marc Alexander Schweitzer ; Michael Griebel ; Marc Alexander Schweitzer. Springer Verlag, 2019. pp. 135-148 (Lecture Notes in Computational Science and Engineering).

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abstract = "The advent of advanced processing and manufacturing techniques has led to new material classes with complex microstructures across scales from nanometers to meters. In this paper, a data-driven computational framework for the analysis of these complex material systems is presented. A mechanistic concurrent multiscale method called Self-consistent Clustering Analysis (SCA) is developed for general inelastic heterogeneous material systems. The efficiency of SCA is achieved via data compression algorithms which group local microstructures into clusters during the training stage, thereby reducing required computational expense. Its accuracy is guaranteed by introducing a self-consistent method for solving the Lippmann–Schwinger integral equation in the prediction stage. The proposed framework is illustrated for a composite cutting process where fracture can be analyzed simultaneously at the microstructure and part scales.",

author = "Modesar Shakoor and Jiaying Gao and Zeliang Liu and Liu, {Wing K}",

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Shakoor, M, Gao, J, Liu, Z & Liu, WK 2019, A data-driven multiscale theory for modeling damage and fracture of composite materials. in M Griebel, MA Schweitzer, M Griebel & MA Schweitzer (eds), Meshfree Methods for Partial Differential Equations IX, 2017. Lecture Notes in Computational Science and Engineering, vol. 129, Springer Verlag, pp. 135-148, 9th International Workshop on Meshfree Methods for Partial Differential Equations, IWMMPDE 2017, Bonn, Germany, 9/18/17. https://doi.org/10.1007/978-3-030-15119-5_8

A data-driven multiscale theory for modeling damage and fracture of composite materials. / Shakoor, Modesar; Gao, Jiaying; Liu, Zeliang; Liu, Wing K.

Meshfree Methods for Partial Differential Equations IX, 2017. ed. / Michael Griebel; Marc Alexander Schweitzer; Michael Griebel; Marc Alexander Schweitzer. Springer Verlag, 2019. p. 135-148 (Lecture Notes in Computational Science and Engineering; Vol. 129).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Shakoor M, Gao J, Liu Z, Liu WK. A data-driven multiscale theory for modeling damage and fracture of composite materials. In Griebel M, Schweitzer MA, Griebel M, Schweitzer MA, editors, Meshfree Methods for Partial Differential Equations IX, 2017. Springer Verlag. 2019. p. 135-148. (Lecture Notes in Computational Science and Engineering). https://doi.org/10.1007/978-3-030-15119-5_8