Development of rate-dependent thermoplastic constitutive models for numerical analysis of ceramics at high-temperature

Three constitutive models for the mechanical description of the behavior of ceramic materials are developed, implemented into a numerical code, calibrated on experimental data, and validated. - The first model is elastic-plastic and addresses the cold compaction of ceramic powders, combining nonlinear elasticity, elasto-plastic coupling and increase of cohesion. - The second model is thermal-viscous-elastic-plastic and is specifically tailored to describe the thermo-mechanical behavior of refractory devices under working conditions at high-temperature. - The third model is thermal-elastic-plastic and implements a shape evolution of the BP yield function, calibrated to simulate the forming of green bodies and their pre-sintering phase. Three algorithms are developed for the integration of constitutive equations when pathological yield functions are involved. The algorithms are coded in user material subroutines to be used in commercial FE softwares and their accuracy is evaluated in model problems allowing for semi-analytical solutions. Material constitutive parameters are obtained from a combination of experimental tests and multi-objective optimization and employed in FE simulations of industrial processes, such as cold-forming of combed finish ceramic tiles and metal flow confinement by means of refractory devices. This PhD thesis is the outcome of the secondment period at the Vesuvius Group, within the framework of the IAPP European project HOTBRICKS (contract number PIAPP GA-2013-609758).

Grantor dc:publisher

Università degli studi di Trento

Year dc:date

2017

Author dc:creator

• Penasa, Massimo

Contributors dc:contributor

• Piccolroaz, Andrea

Statement dc:rights

• info:eu-repo/semantics/openAccess
• license:Tutti i diritti riservati (All rights reserved)
• license uri:iris.PRI01

Language dc:language

eng

Identifier

http://dx.doi.org/10.15168/11572_368018
10.15168/11572_368018

OAI identifier oai:identifier

oai:iris.unitn.it:11572/368018