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Wyświetlanie 1-3 z 3
Tytuł:
Mechanical Performances of Artificial Aggregated Lightweight Concrete
Autorzy:
Davraz, M.
Ceylan, H.
Kılınçarslan, Ş.
Powiązania:
https://bibliotekanauki.pl/articles/1194125.pdf
Data publikacji:
2015-04
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
62.20.dj
Opis:
In this study, some physical and mechanical performances of artificial aggregated lightweight concretes were compared. Special empirical models were developed to estimate the elasticity modulus of lightweight aggregate concrete (LWAC). Five different natural aggregates and one artificial lightweight aggregate material were used throughout the research. Mixture proportions were kept as constant values in all concrete mixtures. All mixtures were cast into cubic, prismatic and cylindrical concrete standard moulds and they were cured at the same curing conditions. A series of physical and mechanical properties, such as density, compressive strength and elasticity modulus for LWAC were experimentally determined. According to the research findings a few empirical models were statistically developed for estimating the elasticity modulus and Poisson's ratio of LWAC and a new diagram practically to be used for estimating the Poisson's ratio of LWAC was also proposed.
Źródło:
Acta Physica Polonica A; 2015, 127, 4; 1246-1250
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Predicting the Poisson Ratio of Lightweight Concretes using Artificial Neural Network
Autorzy:
Davraz, M.
Kilinçarslan, Ş.
Ceylan, H.
Powiązania:
https://bibliotekanauki.pl/articles/1401967.pdf
Data publikacji:
2015-08
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
62.20.dj
Opis:
Artificial neural network is generally information processing system and a computer program that imitates human brain neural network system. By entering the information from outside, artificial neural network can be trained on examples related to a problem, so that modeling of the problem is provided. In this study, compressive strength, Poisson ratio of the lightweight concrete specimens, which have different natural lightweight aggregates, were modeled with artificial neural network. The data which were provided by artificial neural network model were compared with the data obtained from experimental study and a good agreement was determined between the results.
Źródło:
Acta Physica Polonica A; 2015, 128, 2B; B-184-B-186
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
First principles study of mechanical stability and thermodynamic properties of K₂S under pressure and temperature effect
Autorzy:
Boufadi, F.
Bidai, K.
Ameri, M.
Bentouaf, A.
Bensaid, D.
Azzaz, Y.
Ameri, I.
Powiązania:
https://bibliotekanauki.pl/articles/1070528.pdf
Data publikacji:
2016-03
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
62.20.de
81.40.Jj
71.15.Ap
62.20.dj
Opis:
First principles calculations on structural, elastic and thermodynamic properties of K₂S have been made using the full-potential augmented plane-waves plus local orbitals within density functional theory using generalized gradient approximation for exchange correlation potentials. The ground state lattice parameter, bulk moduli have been obtained. The second-order elastic constants, Young and shear modulus, Poisson ratio, have also been calculated. Calculated structural, elastic and other parameters are in good agreement with available data. The elastic constants and thermodynamic quantities under high pressure and temperature are also calculated and discussed.
Źródło:
Acta Physica Polonica A; 2016, 129, 3; 315-322
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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