2023.04–2024.08: 3D Mesoscale Modeling of Concrete Consolidation and Packing Behavior

Summary

This research develops a comprehensive computational framework for the 3D Mesoscale Characterization of Concrete Compaction and Consolidation during slipform paving. By leveraging spherical harmonics to mathematically represent aggregate morphology, discrete element method (DEM) simulations to model spatial packing, and image-based analysis for validation, the project establishes a robust method for evaluating internal structure and consolidation quality of concrete.

Objectives

• Develop a mathematical framework using spherical harmonics for aggregate shape representation.
• Implement stochastic aggregate synthesis with controllable variability using phase-scaling techniques.
• Simulate ideal packing of aggregates using discrete element modeling.
• Benchmark real-world concrete samples against statistically representative idealized packing distributions.
• Support quantitative assessment of vibration-induced consolidation performance.

Key Results

• Developed a phase-controlled spectral synthesis method to generate morphologically realistic synthetic aggregates.
• Built a DEM-based simulation framework that enables optimal spatial distribution of aggregates under packing constraints.
• Performed a Monte Carlo analysis on DEM outputs to establish benchmark indicators for aggregate spacing, mortar-to-aggregate ratio, and effective centroid shift.
• Validated simulation results against laboratory cross-sections obtained from vibrated concrete specimens.

Related Publications

• Yan, X., Fascetti, A.* (2025). An Integrated Framework for Mesoscale Modeling of Concrete Elements Based on Spherical Harmonic Expansion. Construction and Building Materials. (Under Review)
• Yan, X., Fascetti, A.* (2025). A Photometric Stereo and Vision Transformer-Based Framework for Automated Air Void Analysis in Hardened Concrete. Cement and Concrete Research. (Under Review)

Funding

This research is funded through the Improved Infrastructure Systems and Evaluation (IRISE) Consortium under the Year 4 and Year 6 Research Programs at the University of Pittsburgh, with additional support from the Pennsylvania Department of Transportation (PennDOT).

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