Time-Varying Pattern and Prediction Model for Geopolymer Mortar Performance under Seawater Immersion

Area of Science:

• Materials Science
• Civil Engineering
• Geopolymer Chemistry

Background:

• Geopolymer mortar (GPM) is a sustainable alternative to traditional concrete.
• Assessing GPM durability in marine environments is crucial for its application in offshore structures.
• Seawater exposure presents significant challenges to the long-term performance of GPM.

Purpose of the Study:

• To investigate the impact of alkali equivalent (AE) and waterglass modulus (WGM) on GPM's resistance to artificial seawater immersion.
• To analyze the microstructural changes and performance evolution of GPM over 270 days of immersion.
• To develop a predictive model for GPM's uniaxial compressive strength (UCS) under seawater exposure.

Main Methods:

• Immersion experiments using artificial seawater on 300 GPM specimens.
• Periodic performance testing measuring mass loss and uniaxial compressive strength (UCS).
• Microstructural analysis using X-ray diffraction (XRD) and scanning electron microscopy (SEM).
• Development of a support vector regression (SVR) model for UCS prediction.

Main Results:

• GPM's UCS exhibited an initial increase followed by a decline during seawater immersion.
• Optimal GPM seawater resistance was observed within an alkali equivalent (AE) range of 9-12%.
• Increased waterglass modulus (WGM) led to a thinner diffusion layer, reducing seawater resistance.
• The SVR model accurately predicted GPM UCS within 1-2 months of immersion.

Conclusions:

• Alkali equivalent (AE) and waterglass modulus (WGM) significantly influence GPM's seawater immersion resistance.
• A specific AE range (9-12%) is recommended for enhanced GPM durability in marine environments.
• The developed SVR model offers a reliable method for predicting GPM strength in offshore construction.