Hemp Fiber-Reinforced Polymers Composite Jacketing Technique for Sustainable and Environment-Friendly Concrete

Area of Science:

• Civil Engineering
• Materials Science

Background:

• Synthetic fiber-reinforced polymers (FRPs) are costly for reinforcing concrete structures.
• Recycled aggregates, like fired-clay solid bricks, present a sustainable alternative but require effective strengthening methods.

Purpose of the Study:

• To investigate the efficacy of natural hemp fiber-reinforced ropes (FRR) as a sustainable and cost-effective reinforcement for concrete columns containing recycled brick aggregates.
• To evaluate the impact of FRR reinforcement on the compressive strength and ductility of concrete columns.
• To assess the predictive accuracy of analytical models and machine learning for the performance of FRR-strengthened concrete.

Main Methods:

• Fabrication and testing of 24 square concrete columns reinforced with varying layers of hemp FRR under monotonic axial compression.
• Analysis of experimental data to determine the effects of unconfined concrete strength and FRR layers on performance.
• Evaluation of existing analytical stress-strain models for predicting ultimate confined compressive stress and strain.
• Development and validation of a neural network model using literature data to predict compressive strength.

Main Results:

• Hemp FRR significantly enhanced the compressive strength and ductility of concrete columns, with improvements up to 181% and 564% respectively.
• Specimens with lower initial unconfined concrete strength exhibited the most substantial gains in strength and ductility.
• Analytical models showed limited accuracy in predicting both stress and strain, with strain prediction being particularly challenging.
• A neural network model trained on existing literature data demonstrated high accuracy in predicting the compressive strength of FRR-strengthened concrete.

Conclusions:

• Natural hemp FRR is a viable and cost-effective reinforcement for concrete columns with recycled aggregates, offering substantial improvements in mechanical properties.
• The performance enhancement is more pronounced in concrete with lower initial strength.
• Machine learning, specifically neural networks, shows promise for accurately predicting the behavior of hemp FRR-confined concrete, outperforming traditional analytical models.