A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
New Prediction Models for Compressive Strength of GGBS-Based Geopolymer Clays Using Swarm Assisted Optimization
This paper discusses experimental data on unconfined compressive strength (UCS) of an expansive soil chemically altered with GGBS-based geopolymer with varying amounts of GGBS content. Ground granulated blast furnace slag (GGBS) was added to the expansive soil up to 25% in increments of 5%. Scanning Electron Microscopy (SEM) analysis was undertaken to know the microstructural development in the GGBS-based geopolymer clay blends. The unconfined compressive strength (UCS) of the GGBS-based geopolymer clay blends increased with increasing additive content. This paper also presents the viability of particle swarm optimization (PSO) technique in predicting 28 days UCS of alkali-activated blended expansive clays. With availability of limited experimental data accurate estimation is possible with PSO. In multilinear model UCS equation, the coefficients are adjusted by PSO has been developed for the prediction of UCS for geotechnical designs is the key factor presented in this paper.
New Prediction Models for Compressive Strength of GGBS-Based Geopolymer Clays Using Swarm Assisted Optimization
This paper discusses experimental data on unconfined compressive strength (UCS) of an expansive soil chemically altered with GGBS-based geopolymer with varying amounts of GGBS content. Ground granulated blast furnace slag (GGBS) was added to the expansive soil up to 25% in increments of 5%. Scanning Electron Microscopy (SEM) analysis was undertaken to know the microstructural development in the GGBS-based geopolymer clay blends. The unconfined compressive strength (UCS) of the GGBS-based geopolymer clay blends increased with increasing additive content. This paper also presents the viability of particle swarm optimization (PSO) technique in predicting 28 days UCS of alkali-activated blended expansive clays. With availability of limited experimental data accurate estimation is possible with PSO. In multilinear model UCS equation, the coefficients are adjusted by PSO has been developed for the prediction of UCS for geotechnical designs is the key factor presented in this paper.
New Prediction Models for Compressive Strength of GGBS-Based Geopolymer Clays Using Swarm Assisted Optimization
Lecture Notes in Civil Engineering
Prashant, Amit (editor) / Sachan, Ajanta (editor) / Desai, Chandrakant S. (editor) / Nagaraju, T. Vamsi (author) / Prasad, Ch. Durga (author)
2020-01-15
13 pages
Article/Chapter (Book)
Electronic Resource
English
Prediction of compressive strength of GGBS based concrete using RVM
| British Library Online Contents | 2018