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Study on Frost Resistance of Recycled Rubber Straw Concrete Using Particle Swarm Optimization Enhanced Artificial
1College of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China.
Polymers
|November 27, 2024
Summary
This study introduces recycled rubber straw concrete, evaluating its frost resistance through freeze-thaw tests. Results show a predictive model accurately forecasts performance based on mix ratios.
Area of Science:
- Materials Science
- Civil Engineering
- Sustainable Construction
Background:
- Recycled materials like rubber particles and straw powder offer sustainable alternatives in construction.
- Assessing the freeze-thaw resistance of novel concrete composites is crucial for durability in cold climates.
Purpose of the Study:
- To investigate the frost resistance of recycled rubber straw concrete.
- To analyze the microstructural changes and mechanisms affecting concrete's performance under freeze-thaw conditions.
- To develop a predictive model for recycled rubber straw concrete properties.
Main Methods:
- Preparation of recycled rubber straw concrete using rubber particles and straw powder.
- Conducting freeze-thaw tests via the quick-freezing method.
- Evaluating frost resistance through relative dynamic modulus of elasticity, mass loss rate, and flexural strength.
- Utilizing Scanning Electron Microscopy (SEM) for microstructural analysis.
- Applying Particle Swarm Optimization (PSO) and Genetic Algorithms to optimize a BP neural network for predictive modeling.
Main Results:
- The frost resistance of recycled rubber straw concrete was quantified through various physical and mechanical tests after freeze-thaw cycles.
- SEM analysis revealed microstructural alterations in the concrete post-freeze-thaw.
- The optimized PSO-BP neural network model demonstrated high accuracy and stability in predicting flexural strength and freeze-thaw cycles.
- The study elucidated the effects and mechanisms of rubber and straw admixtures on concrete's frost resistance.
Conclusions:
- Recycled rubber straw concrete exhibits measurable frost resistance, influenced by rubber and straw admixtures.
- Microstructural analysis provides insights into the mechanisms of freeze-thaw damage and material behavior.
- The developed PSO-BP neural network model is a reliable tool for predicting the performance of recycled rubber straw concrete across different mix proportions.
Keywords:
BP neural network modelgenetic algorithm (GA)mechanical predictionparticle swarm optimization (PSO) algorithmrubber concretestraw powderMore Related Videos
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