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contributor authorLiu, Yang
contributor authorSun, WaiChing
contributor authorFish, Jacob
date accessioned2017-05-09T01:25:30Z
date available2017-05-09T01:25:30Z
date issued2016
identifier issn0021-8936
identifier otherjam_083_01_011003.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/160184
description abstractThis work presents a new staggered multilevel material identification procedure for phenomenological critical state plasticity models. The emphasis is placed on cases in which available experimental data and constraints are insufficient for calibration. The key idea is to create a secondary virtual experimental database from highfidelity models, such as discrete element simulations, then merge both the actual experimental data and secondary database as an extended digital database (EDD) to determine material parameters for the phenomenological macroscopic critical state plasticity model. The calibration procedure therefore consists of two steps. First, the material parameters of the discrete (distinct) element method (DEM) simulations are identified via the standard optimization procedure. Then, the calibrated DEM simulations are used to expand the experimental database with new simulated loading histories. This expansion of database provides additional constraints necessary for calibration of the phenomenological critical state plasticity models. The robustness of the proposed material identification framework is demonstrated in the context of the Dafalias–Manzari plasticity model.
publisherThe American Society of Mechanical Engineers (ASME)
titleDetermining Material Parameters for Critical State Plasticity Models Based on Multilevel Extended Digital Database
typeJournal Paper
journal volume83
journal issue1
journal titleJournal of Applied Mechanics
identifier doi10.1115/1.4031619
journal fristpage11003
journal lastpage11003
identifier eissn1528-9036
treeJournal of Applied Mechanics:;2016:;volume( 083 ):;issue: 001
contenttypeFulltext


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