Research on thermo-mechanical coupling behavior of plasma-sprayed mullite ceramic coatings on concrete surfaces
Abstract
This study systematically investigates the thermo-mechanical coupling behavior of plasma-sprayed mullite ceramic coatings on concrete surfaces through integrated finite element simulation and experimental verification. A three-dimensional thermo-mechanical coupling model was developed on the ANSYS Fluent platform to simulate temperature field distribution, residual stress evolution, and their impacts on interfacial bonding strength during the spraying process. Experimental data calibration confirmed the model accuracy with <5% deviation. Results demonstrate that spraying power and stand-off distance critically influence coating temperature gradients. Optimized parameters reduced interfacial residual stress to <50 MPa while decreasing porosity to 8.3%. SEM-EDS and X-CT analyses revealed the correlation between pore distribution and stress concentration. Thermal expansion coefficient mismatch was identified as the primary cause of interfacial delamination. Process optimization enhanced interfacial bonding strength by 38.7%, establishing a reliable predictive model for coating thermo-mechanical performance. The findings provide theoretical guidance for plasma spraying parameter optimization and establish a validated framework for concrete surface protection coating design. This research advances the fundamental understanding of substrate-coating interactions under thermal-mechanical loads and offers practical solutions for infrastructure durability enhancement.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.