Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Shadi Hanandeh"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-27 (2024)
Abstract In this work, intelligent numerical models for the prediction of debris flow susceptibility using slope stability failure factor of safety (FOS) machine learning predictions have been developed. These machine learning techniques were trained
Externí odkaz:
https://doaj.org/article/8f004291eb684a4a952e02aff208b100
Autor:
Kennedy C. Onyelowe, Arif Ali Baig Moghal, Ahmed Ebid, Ateekh Ur Rehman, Shadi Hanandeh, Vishnu Priyan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-29 (2024)
Abstract It has been imperative to study and stabilize cohesive soils for use in the construction of pavement subgrade and compacted landfill liners considering their unconfined compressive strength (UCS). As long as natural cohesive soil falls below
Externí odkaz:
https://doaj.org/article/bf609a1e78dd491688506f365f8da5f2
Autor:
Kennedy C. Onyelowe, Ahmed M. Ebid, Danilo Fernando Fernandez Vinueza, Néstor Augusto Estrada Brito, Nancy Velasco, Jorge Buñay, Sabih Hashim Muhodir, Hamza Imran, Shadi Hanandeh
Publikováno v:
Frontiers in Built Environment, Vol 10 (2024)
The development of concrete with excellent water and frost resistance providing high level of sound and thermal insulation has triggered the formulation of foamed concrete. However, multiple laboratory studies are required to produce reasonable data
Externí odkaz:
https://doaj.org/article/67c3d615e2b34767926a7b339196621e
Autor:
Cesar Garcia, Alexis Ivan Andrade Valle, Angel Alberto Silva Conde, Nestor Ulloa, Alireza Bahrami, Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh
Publikováno v:
Frontiers in Built Environment, Vol 10 (2024)
The mechanical characteristics of concrete are crucial factors in structural design standards especially in concrete technology. Employing reliable prediction models for concrete’s mechanical properties can reduce the number of necessary laboratory
Externí odkaz:
https://doaj.org/article/15133314e4ee45cd97f661f8c0668214
Autor:
Edwin Zumba, Nancy Velasco, Edison Marcelo Melendres Medina, Jorge Bunay, Nestor Augusto Estrada Brito, Kennedy C Onyelowe, Nakkeeran Ganasen, Shadi Hanandeh
Publikováno v:
PLoS ONE, Vol 19, Iss 7, p e0302202 (2024)
It is structurally pertinent to understudy the important roles the self-compacting concrete (SCC) yield stress and plastic viscosity play in maintaining the rheological state of the concrete to flow. It is also important to understand that different
Externí odkaz:
https://doaj.org/article/766d6e17e0274620861a8b03313afa60
Autor:
Xinghuang Guo, Cesar Garcia, Alexis Ivan Andrade Valle, Kennedy Onyelowe, Andrea Natali Zarate Villacres, Ahmed M Ebid, Shadi Hanandeh
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0301075 (2024)
In the field of soil mechanics, especially in transportation and environmental geotechnics, the use of machine learning (ML) techniques has emerged as a powerful tool for predicting and understanding the compressive strength behavior of soils especia
Externí odkaz:
https://doaj.org/article/4666791a18c84bc6bfa2c52476235d11
Publikováno v:
Frontiers in Built Environment, Vol 8 (2022)
The pavement management system is recognized as an assertive discipline that works on pavement indices to predict the pavement performance condition. This study used soft computing methods such as genetic algorithms and artificial intelligence to pro
Externí odkaz:
https://doaj.org/article/294df585958443368a796a649426524c
Autor:
Shadi Hanandeh
Publikováno v:
Case Studies in Construction Materials, Vol 16, Iss , Pp e00991- (2022)
This study explored the outcomes of utilizing genetic algorithms and artificial neural networks to assess the pavement quality index on the principal road by analyzing 500 flexible pavement sections in Amman, Jordan. Pavement sections are selected in
Externí odkaz:
https://doaj.org/article/a6371d961bd247d6a174d264ce2607fb
Autor:
Shadi Hanandeh
Publikováno v:
Frontiers in Built Environment, Vol 8 (2022)
This article presents an analysis of a dataset related to slope stability circular failure cases using the GeneXproTools program. Two models were developed: The first model was utilized to find a classification model that shows the stability status (
Externí odkaz:
https://doaj.org/article/ea38c92b12d74450a83a76606e231ffe
Autor:
Ala’ Taleb Obaidat, Ahmed M. Ashteyat, Yasmeen Taleb Obaidat, Aseel Yousef Al-Btoush, Shadi Hanandeh
Publikováno v:
Case Studies in Construction Materials, Vol 15, Iss , Pp e00742- (2021)
This study aims to investigate the behavior of heat damaged reinforced concrete RC circular column considering effect of heat and repair technique. Six RC circular column with diameter of 185 mm and 800 mm in height were cast, heated at 400°C and 60
Externí odkaz:
https://doaj.org/article/900652f13e4b4b9b9615fa613fb58f54