Multi-objective optimisation design for GFRP tendon reinforced cemented soil

Abstract

Rebar reinforced cemented soil is employed widely to solve the weak foundation problem led by sludge particularly. Nowadays, the glass fiber-reinforced polymer (GFRP) becomes a new tendon material instead of steel to avoid the performance degradation resulting from steel corrosion. The interface bond strength of GFRP tendon-reinforced cemented soils (GTRCS) displays its excellent mechanical capacity. Nevertheless, its application is obstructed by the deficient studies between the bond strength and influence factors. Therefore, this study investigates the effects of varying water contents (Cw: 50%-90%), cement proportions (Cc: 6%-30%), and curing periods (Tc: 28 days, 90 days) on both pullout strength (Tp) and unconfined compression strength (UCS) of GTRCS. The results showed that the pullout strength and compressive strength were positively related to Tc and Cc and negatively related to Cw. Besides, these experimental results were also utilised to develop support vector regression (SVR) models. The beetle antennae search (BAS) algorithm was used to adjust the SVR’s hyperparameters. The high correlation coefficients (0.988 for UCS and 0.972 for Tp) proved the reliability of the established BAS-SVR models. In addition, the multi-objective beetle antennae search algorithm (MOBAS-SVR) was developed for bi-objective optimisation designs (UCS-cost and Tp-cost). Finally, sensitivity analysis was conducted to range the significance of variables for Tp and UCS.