has been cited by the following article(s):
[1]
|
Effect of PVA Fiber on the Mechanical Properties of Seawater Coral Sand Engineered Cementitious Composites
|
|
Materials,
2024 |
|
|
[2]
|
Influence of Fiber Orientation on the Water and Ions Transportation of Engineered Cementitious Composite (ECC)
|
|
Materials,
2023 |
|
|
[3]
|
Influence of fiber orientation on the mechanical responses of engineering cementitious composite (ECC) under various loading conditions
|
|
Journal of Building …,
2023 |
|
|
[4]
|
Experimental investigation of strengthening of masonry-infilled RC frames using prefabricated engineered cementitious composite panels
|
|
Alahi - Engineering Structures,
2022 |
|
|
[5]
|
Ecological Effects of Local Materials in Landscape Design based on Machine Learning
|
|
International Transactions on Electrical Energy …,
2022 |
|
|
[6]
|
Makine Öğrenmesi ile Kompozit Malzemelerin Yük Altındaki Yer Değiştirme ve Gerilme Değerlerinin Tahmini
|
|
Avrupa Bilim ve Teknoloji Dergisi,
2022 |
|
|
[7]
|
Characterizing fiber reinforced concrete incorporating zeolite and metakaolin as natural pozzolans
|
|
Nik, NA Libre, S Nasrollahpour - Structures,
2021 |
|
|
[8]
|
Evaluation of the efficacy of using engineered cementitious composites in RC beam-column joints
|
|
2020 |
|
|
[9]
|
Improving Seismic Performance of Steel Beam-Concrete Column Joint Using Engineered Cementations Composites (ECC)
|
|
A, A Dehghani - Bulletin of Earthquake Science …,
2020 |
|
|
[10]
|
Prediction of Engineered Cementitious Composite Material Properties Using Artificial Neural Network
|
|
2019 |
|
|
[1]
|
The experimental and numerical simulation of interface shear behavior between ECC and coal gangue concrete
Advances in Structural Engineering,
2024
DOI:10.1177/13694332241276055
|
|
|
[2]
|
Ecological Effects of Local Materials in Landscape Design based on Machine Learning
International Transactions on Electrical Energy Systems,
2022
DOI:10.1155/2022/7340002
|
|
|
[3]
|
Prediction of Displacement and Stress Values of Composite Materials Under Load with Machine Learning Models
European Journal of Science and Technology,
2022
DOI:10.31590/ejosat.1188744
|
|
|