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University of Illinois at Urbana-Champaign

Neural Network-Based Constitutive Modeling of Granular Material

Abstract

dc:description

An autoprogressive training simulator is developed, and non-linear finite element analysis is implemented to handle geometrically non-linear problems. This simulator is then used for the autoprogressive training of the NN material models using the results of drained triaxial compression tests with end friction.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Civil Engineering
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sidarta, Djoni Eka
Contributors dc:contributor
  • Ghaboussi, Jamshid

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI9971194
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/83509

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Sidarta, Djoni Eka. Neural Network-Based Constitutive Modeling of Granular Material. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/83509