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Multi-objective genetic algorithm calibration of colored self-compacting concrete using DEM: an integrated parallel
Vahid Shafaie1, Majid Movahedi Rad2
1Department of Structural and Geotechnical Engineering, Széchenyi István University, 9026, Győr, Hungary.
Scientific Reports
|February 20, 2024
Summary
This study presents an automated method for simulating Colored Self-Compacting Concrete (CSCC) using multi-objective optimization and Discrete Element Modeling (DEM). The approach accurately predicts concrete behavior by integrating pigment effects into micro-parameters.
Area of Science:
- Materials Science
- Civil Engineering
- Computational Mechanics
Background:
- Numerical simulations are crucial for understanding concrete behavior.
- Existing methods often lack precision in modeling complex concrete properties like color effects.
- Self-compacting concrete (SCC) offers advantages in construction but requires accurate simulation for optimization.
Purpose of the Study:
- To develop and validate an innovative, automated calibration methodology for Colored Self-Compacting Concrete (CSCC) simulations.
- To integrate multi-objective optimization with Discrete Element Modeling (DEM) for enhanced concrete simulation accuracy.
- To investigate the influence of pigment effects on the micro-mechanical parameters of CSCC.
Main Methods:
- Utilized MATLAB's Genetic Algorithm (GA) for multi-objective optimization of micro-parameters.
- Integrated GA with PFC3D (Discrete Element Modeling software) for CSCC behavior simulation.
- Developed an automated calibration script in MATLAB and PFC fish script, terminating based on predefined criteria.
- Employed Uniaxial Compressive Strength (UCS) tests as the primary calibration basis.
Main Results:
- Achieved a high degree of alignment between simulated and observed macro properties of CSCC.
- Demonstrated the effectiveness of the automated calibration methodology with fitness values consistently exceeding 0.94.
- Successfully incorporated pigment effects into DEM micro-parameters, influencing cohesion coefficients.
Conclusions:
- The developed automated calibration methodology significantly enhances the accuracy of CSCC numerical simulations.
- Multi-objective optimization is vital for precise calibration of concrete's micro-parameters in DEM.
- This research advances the simulation of advanced concrete materials, including the impact of colorants.
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