Fitting the grain orientation distribution of a polycrystalline material conditioned on a Laguerre tessellation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10465417" target="_blank" >RIV/00216208:11320/23:10465417 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Ubsde_4Skn" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Ubsde_4Skn</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.spasta.2023.100747" target="_blank" >10.1016/j.spasta.2023.100747</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fitting the grain orientation distribution of a polycrystalline material conditioned on a Laguerre tessellation

Popis výsledku v původním jazyce

The description of distributions related to grain microstruc-ture helps physicists to understand the processes in materials and their properties. This paper presents a general statistical methodology for the analysis of crystallographic orientations of grains in a 3D Laguerre tessellation dataset which represents the microstructure of a polycrystalline material. We introduce complex stochastic models which may substitute expensive lab-oratory experiments: conditional on the Laguerre tessellation, we suggest interaction models for the distribution of cubic crystal lattice orientations, where the interaction is between pairs of ori-entations for neighbouring grains in the tessellation. We discuss parameter estimation and model comparison methods based on maximum pseudolikelihood as well as graphical procedures for model checking using simulations. Our methodology is applied for analysing a dataset representing a nickel-titanium shape memory alloy.(c) 2023 Elsevier B.V. All rights reserved.

Název v anglickém jazyce

Fitting the grain orientation distribution of a polycrystalline material conditioned on a Laguerre tessellation

Popis výsledku anglicky

The description of distributions related to grain microstruc-ture helps physicists to understand the processes in materials and their properties. This paper presents a general statistical methodology for the analysis of crystallographic orientations of grains in a 3D Laguerre tessellation dataset which represents the microstructure of a polycrystalline material. We introduce complex stochastic models which may substitute expensive lab-oratory experiments: conditional on the Laguerre tessellation, we suggest interaction models for the distribution of cubic crystal lattice orientations, where the interaction is between pairs of ori-entations for neighbouring grains in the tessellation. We discuss parameter estimation and model comparison methods based on maximum pseudolikelihood as well as graphical procedures for model checking using simulations. Our methodology is applied for analysing a dataset representing a nickel-titanium shape memory alloy.(c) 2023 Elsevier B.V. All rights reserved.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Spatial Statistics

ISSN

2211-6753

e-ISSN

2211-6753

Svazek periodika

55

Číslo periodika v rámci svazku

June 2023

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

16

Strana od-do

100747

Kód UT WoS článku

000986064800001

EID výsledku v databázi Scopus

2-s2.0-85152692872