Extracting three-dimensional Cellular Automaton for cement microstructure development using Gene Expression Programming
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092818" target="_blank" >RIV/61989100:27240/14:86092818 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1109/NaBIC.2014.6921851" target="_blank" >http://dx.doi.org/10.1109/NaBIC.2014.6921851</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NaBIC.2014.6921851" target="_blank" >10.1109/NaBIC.2014.6921851</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Extracting three-dimensional Cellular Automaton for cement microstructure development using Gene Expression Programming
Popis výsledku v původním jazyce
A three-dimensional CA model for the simulation of Portland cement microstructure development has been developed in this paper. The Gene Expression Programming (GEP) algorithm is employed as the learning algorithm to evolve the transition rule reverselyfrom the microstructure development characteristic data due to hydration reactions. The characteristic data is extracted from 8-bit gray images that based on the processing of real cement acquired by Micro Computed Tomography (micro-CT) technology. Starting with initial micro-CT image, cement microstructure evolution images of 28 days is constructed through CA rule discovered by GEP. The experimental results show that this model with the CA rule designed by GEP has higher agreement between the model predictions and experimental measurements for degree of hydration than other models. Furthermore, this model still has good generalization ability when changing the water-cement ratio and chemical composition. 2014 IEEE.
Název v anglickém jazyce
Extracting three-dimensional Cellular Automaton for cement microstructure development using Gene Expression Programming
Popis výsledku anglicky
A three-dimensional CA model for the simulation of Portland cement microstructure development has been developed in this paper. The Gene Expression Programming (GEP) algorithm is employed as the learning algorithm to evolve the transition rule reverselyfrom the microstructure development characteristic data due to hydration reactions. The characteristic data is extracted from 8-bit gray images that based on the processing of real cement acquired by Micro Computed Tomography (micro-CT) technology. Starting with initial micro-CT image, cement microstructure evolution images of 28 days is constructed through CA rule discovered by GEP. The experimental results show that this model with the CA rule designed by GEP has higher agreement between the model predictions and experimental measurements for degree of hydration than other models. Furthermore, this model still has good generalization ability when changing the water-cement ratio and chemical composition. 2014 IEEE.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2014
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
NaBIC 2014 ; CASoN 2014 : July 30-31, Porto, Portugal
ISBN
978-1-4799-5937-2
ISSN
—
e-ISSN
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Počet stran výsledku
6
Strana od-do
41-46
Název nakladatele
IEEE
Místo vydání
New York
Místo konání akce
Porto
Datum konání akce
30. 7. 2014
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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