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<p>This study investigates the development and analysis of concrete cubes enhanced with carbon nanotube-stainless steel (CNTSS) fibers using probabilistic modeling to address uncertainties in material properties and loading conditions. A 150&#xa0;mm × 150&#xa0;mm × 150&#xa0;mm cube was designed and tested for compressive strength under various loading rates following ASTM C39 standards, with experimental data utilized to develop a prediction model incorporating the Monte Carlo simulation and finite element method (FEM). The model predicts key structural parameters, including compressive strength, displacement, stress, and strain, while accounting for inherent variability. Results indicate that CNTSS fibers significantly improved compressive strength by 28-35%, improved strain capacity at peak stress by 12-15%, and reduced porosity by up to 18% compared with control specimens. Furthermore, scanning electron microscope (SEM) analysis revealed that CNTSS fibers bridged micro-cracks, arrested crack propagation, and reduced porosity through dense CNTSS packing, thereby improving overall durability and resistance to environmental factors. The validated Monte Carlo and FEM framework reliably captured the experimental behavior, confirming its potential for predicting the structural performance of CNTSS-enhanced concrete by showing a mean error of less than 5% compared to experimental results. These findings highlight the significance of CNTSS fiber reinforcement and probabilistic modeling in advancing durable, reliable, and sustainable materials for critical infrastructure applications.</p>

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Probabilistic Prediction of Compressive Strength and Structural Performance of Concrete Specimens Enhanced with Carbon Nanotube–Stainless Steel Fibers Using Monte Carlo Simulation and FEM

  • 期刊论文

  • 发表日期：

    2025年12月22日

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  • Surya Dev Singh,
  • Pradyut Anand,
  • Denise-Penelope N. Kontoni,
  • Sudheer Kumar Yantrapalli

摘要

This study investigates the development and analysis of concrete cubes enhanced with carbon nanotube-stainless steel (CNTSS) fibers using probabilistic modeling to address uncertainties in material properties and loading conditions. A 150 mm × 150 mm × 150 mm cube was designed and tested for compressive strength under various loading rates following ASTM C39 standards, with experimental data utilized to develop a prediction model incorporating the Monte Carlo simulation and finite element method (FEM). The model predicts key structural parameters, including compressive strength, displacement, stress, and strain, while accounting for inherent variability. Results indicate that CNTSS fibers significantly improved compressive strength by 28-35%, improved strain capacity at peak stress by 12-15%, and reduced porosity by up to 18% compared with control specimens. Furthermore, scanning electron microscope (SEM) analysis revealed that CNTSS fibers bridged micro-cracks, arrested crack propagation, and reduced porosity through dense CNTSS packing, thereby improving overall durability and resistance to environmental factors. The validated Monte Carlo and FEM framework reliably captured the experimental behavior, confirming its potential for predicting the structural performance of CNTSS-enhanced concrete by showing a mean error of less than 5% compared to experimental results. These findings highlight the significance of CNTSS fiber reinforcement and probabilistic modeling in advancing durable, reliable, and sustainable materials for critical infrastructure applications.