Nucleation and growth probabilistic models for powders transformation
type: Dataset
description: This work focuses on powder transformations using the Mampel model, i.e. proceeding by surfacic nucleation and isotropic growth. In the first part, using a probabilistic approach, a new expression of the fractional conversion is established. This expression is more general than the existing ones because it is free of any geometrical dependence and is available in non isothermal/non isobaric conditions. The fractional conversion is then numerically evaluated by a Monte Carlo method. Different variance reduction methods are implemented, allowing to improve time calculation. In the following part it is shown how the probabilistic structure of the measured fractional conversion influences the choice of the fitting method and leads to the quantification of the parameters uncertainties. Finaly, a new nucleation model is introduced. It describes the phenomenon from a microscopic point of view where a nucleus is a group of defects which appear and move randomly in the cristalline structure.
landing page: https://theses.hal.science/tel-00803655
identifier: NNT: 2005EMSE0011
keyword: chaine-de-markov
keyword: germination-et-croissance
keyword: infoeu-reposemanticsdoctoralthesis
keyword: mathmath-prmathematics-mathprobability-mathpr
keyword: monte-carlo
keyword: monte-carlo-method
keyword: nucleation-and-growth
keyword: parameters-sensibility
keyword: poisson-point-process
keyword: processus-spatio-temporel-de-poisson
keyword: quantification-des-incertitudes
keyword: reduction-de-variance
keyword: sensibilite-aux-parametres
keyword: theses
keyword: uncertainties-quantification
keyword: variance-reduction
issued: 2026-05-12T05:13:38.245540
modified: 2026-05-12T05:13:38.245545
language: fr
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Nucleation and growth probabilistic models for powders transformation
type: Distribution
format: HTML
access URL: https://theses.hal.science/tel-00803655
issued: 2026-05-12T05:13:38.269989
modified: 2026-05-12T05:13:38.218964