Strain localization of reinforced alkali-activated concrete under corrosion using digital image correlation
Date of Publication
Bachelor of Science in Civil Engineering with Spec in Construction Technology & Management
Gokongwei College of Engineering
Jason Maximino C. Ongpeng
Defense Panel Chair
Ronaldo S. Gallardo
Defense Panel Member
Bryan Josef T. Medrano
Richard M. De Jesus
Ordinary port land cement (OPC) is one of the most commonly used material in the construction industry. However, its production produces harmful pollutants that largely contribute to global greenhouse emissions, as well as consumes a significant amount of natural resources such as limestone. Studies have found alkali-activated concrete (AAC) to be viable alternative for cement, and one of the greatest advantages of AAC against OPC is it corrosion resistance.
In this study, the strain localization of reinforced alkali-activated concrete (AAC) with low-calcium coal fly ash (CFA) and ordinary port land cement (OPC) concrete beams under flexural bending tests with cyclic load has been investigated through digital image correlation (DIC) technique. The strain values obtained from both concrete types were compared and it was concluded that AAC strains are consistently higher than that of OPC
Prior to testing the beams, compression tests were conducted on cylindrical samples of the two concrete types wherein it was found that both AAC and OPC are both ductile.
Furthermore, the sensitivity of DIC and conventional strain gauges in measuring the strain for both AAC and OPC was investigated, and it was found that both techniques are sensitive for OPC while otherwise for AAC due to strain localization. The strain localization of AAC may be linked to its ductile characterization.
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
xvi, 149 leaves : illustrations (some color) ; 30 cm.
Building materials; Portland cement
Bolivar, E., Escleto, A. T., Rubinos, I. B., & Tan, S. M. (2018). Strain localization of reinforced alkali-activated concrete under corrosion using digital image correlation. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/6452