Cargando…
Prediction on Compressive and Split Tensile Strengths of GGBFS/FA Based GPC
Based on rate constant concept, empirical models were presented for the predictions of age-dependent development of compressive and split tensile strengths of geopolymer concrete composite (GPCC) with fly ash (FA) blended with ground granulated blast furnace slag (GGBFS). The models were empirically...
Autores principales: | Lee, Songhee, Shin, Sangmin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6947414/ https://www.ncbi.nlm.nih.gov/pubmed/31847257 http://dx.doi.org/10.3390/ma12244198 |
Ejemplares similares
-
Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS
por: Tran, Van Quan, et al.
Publicado: (2021) -
Learned Prediction of Compressive Strength of GGBFS Concrete Using Hybrid Artificial Neural Network Models
por: Han, In-Ji, et al.
Publicado: (2019) -
Importance of Cation Species during Sulfate Resistance Tests for Alkali-Activated FA/GGBFS Blended Mortars
por: Cho, Youngkeun, et al.
Publicado: (2019) -
Application of Machine Learning Techniques for Predicting Compressive, Splitting Tensile, and Flexural Strengths of Concrete with Metakaolin
por: Shah, Hammad Ahmed, et al.
Publicado: (2022) -
Experimental data on compressive strength and ultrasonic pulse velocity properties of sustainable mortar made with high content of GGBFS and CKD combinations
por: Majdi, Hasan Sh, et al.
Publicado: (2020)