Zobrazeno 1 - 10
of 105
pro vyhledávání: '"A Nechnech"'
Publikováno v:
Magazine of Civil Engineering, Vol None, Iss 08 (2021)
Today the road has become a necessity and an important factor in the economic and social development of nations. Algeria knows the realization of many grandiose road projects that required large quantities of noble materials such as aggregates and cr
Externí odkaz:
https://doaj.org/article/f6e0d3c97f5d4144b1cef927fa1069a7
Publikováno v:
In Construction and Building Materials 30 May 2019 208:464-471
Publikováno v:
Journal of Building Materials and Structures, Vol 8, Iss 1 (2021)
The purpose of this work consists of valorizing a local sand dune which is found in abundance in the region of Djelfa (Algeria); for use in pavement foundations. For this investigation a method of formulation has been proposed, which based on the sta
Externí odkaz:
https://doaj.org/article/9f972d9835ec41b8948a62d84b9f14cd
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Journal of Building Materials and Structures. 9:33-43
The purpose of this work is the study and the valorization of sand dune which is found in abundance in the region of Djelfa (Algeria); for use in pavement foundations. For this investigation a method of formulation has been proposed, which based on t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaf19f738ddbff701e71ee444d8e00ba
https://doi.org/10.34118/jbms.v9i1.1897
https://doi.org/10.34118/jbms.v9i1.1897
Publikováno v:
In APCBEE Procedia 2014 9:328-333
Prediction of axial capacity of piles driven in non-cohesive soils based on neural networks approach
Publikováno v:
Journal of Civil Engineering and Management, Vol 23, Iss 3 (2017)
This paper presents an application of two advanced approaches, Artificial Neural Networks (ANN) and Principal Component Analysis (PCA) in predicting the axial pile capacity. The combination of these two approaches allowed the development of an ANN
Externí odkaz:
https://doaj.org/article/6dc9e78dcc6c42628f9a40a787493a6e
Autor:
Ammar Nechnech, Patrick Pizette, Nor-Edine Abriak, Souhila Fergani, Lynda Djerbal, Khedidja Allag Ait Mokhtar
Publikováno v:
Geotechnical and Geological Engineering. 39:991-1008
This article presents the results of a numerical simulation carried out from a series of standard triaxial tests conducted on limestone sand from a quarry situated in Algiers (center of Algeria). The main objective of the investigation is to obtain f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::baded2dfec0d6ebbb2d878cf055f95df
https://doi.org/10.1007/s10706-020-01540-x
https://doi.org/10.1007/s10706-020-01540-x
Publikováno v:
MATEC Web of Conferences, Vol 149, p 02025 (2018)
Determination of pile bearing capacity from the in-situ tests has developed considerably due to the significant development of their technology. The project presented in this paper is a combination of two approaches, artificial neural networks and ma
Externí odkaz:
https://doaj.org/article/cb2fc3d49f00472f960bd23be7d32b2a
Publikováno v:
Engineering with Computers. 37:675-684
Due to a considerable level of uncertainty describing the pile–soil behavior, many pile capacity prediction methods have focused on correlation with in situ tests. In recent years, artificial neural networks (ANNs) have been applied successfully in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::890b4d7630580bf98ec6a1cb0e35842f
https://doi.org/10.1007/s00366-019-00847-5
https://doi.org/10.1007/s00366-019-00847-5