• Geomechanics and Engineering
• /
• v.28 no.6
• /
• pp.599-611
• /
• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• Composites Research
• /
• v.30 no.1
• /
• pp.59-64
• /
• 2017

Eco-convivial composites with improved properties are essential to present polymer scenario and can be made easily by replacing partially/completely renewable materials either matrix or reinforcement along with few % of additives. In these investigations, Abaca fabric have been used as reinforcement for manufacturing of Vinyl ester composites through VARTM technique and study the effect of alkali surface treatment of abaca fabric and flame retardant additives i.e., ammonium polyphosphate (APP) with halloysite nano-clay (HNT) on mechanical and flame retardant properties. The results concluded that, surface treatment deceased the hydrophilic nature of fabric and enhanced the interfacial bonding with hydrophobic matrix and eventually increased mechanical properties slightly of developed composites. Similarly, the flame retardancy of the composites improved significantly and increases the burning time by varying the wt% of filler concentration.