Apparent viscosity modeling and flow simulation of precursor solutions for PIP process of ceramic matrix composites

Purpose To improve the infiltration quality and efficiency in the precursor impregnation pyrolysis (PIP) process for fabricating ceramic matrix composites, this study focuses on modeling the viscosity behavior of the precursor solution under different solute mass fractions and shear rates. Design/methodology/approach A multiscale apparent viscosity model is established based on Landau phase transition theory and the variational principle of the Lagrangian energy functional. The governing equation for the order parameter is analytically solved to obtain a local viscosity expression, which is extended to the global domain using a first-order Bernstein polynomial. The model is validated using experimental data from a SiC powder–modified precursor solution and then applied to simulate infiltration under different pressures to evaluate process efficiency. Findings The model successfully captures the shear-thinning behavior and solute sensitivity of the precursor solution. Results show that both excessively low and high viscosities result in poor impregnation due to bubble entrapment or limited mobility. Optimized solute content and pressure can achieve a balance between viscous and capillary forces, enabling uniform and efficient impregnation. Originality/value This work provides a practical viscosity model for PIP processes, helping to better design precursor formulations and pressure conditions. The results support more stable and efficient manufacturing of ceramic matrix composites.

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Publication Details

Journal
Multidiscipline Modeling in Materials and Structures
Published
2025-08-08
DOI
https://doi.org/10.1108/mmms-05-2025-0196
Primary Topic
Composite Material Mechanics
Type
article
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article

Apparent viscosity modeling and flow simulation of precursor solutions for PIP process of ceramic matrix composites

Pengfei He, Yanni He, Ying Dai
Multidiscipline Modeling in Materials and Structures
Composite Material Mechanics
article

Apparent viscosity modeling and flow simulation of precursor solutions for PIP process of ceramic matrix composites

Pengfei He, Yanni He, Ying Dai
article en

Abstract

Purpose To improve the infiltration quality and efficiency in the precursor impregnation pyrolysis (PIP) process for fabricating ceramic matrix composites, this study focuses on modeling the viscosity behavior of the precursor solution under different solute mass fractions and shear rates. Design/methodology/approach A multiscale apparent viscosity model is established based on Landau phase transition theory and the variational principle of the Lagrangian energy functional. The governing equation for the order parameter is analytically solved to obtain a local viscosity expression, which is extended to the global domain using a first-order Bernstein polynomial. The model is validated using experimental data from a SiC powder–modified precursor solution and then applied to simulate infiltration under different pressures to evaluate process efficiency. Findings The model successfully captures the shear-thinning behavior and solute sensitivity of the precursor solution. Results show that both excessively low and high viscosities result in poor impregnation due to bubble entrapment or limited mobility. Optimized solute content and pressure can achieve a balance between viscous and capillary forces, enabling uniform and efficient impregnation. Originality/value This work provides a practical viscosity model for PIP processes, helping to better design precursor formulations and pressure conditions. The results support more stable and efficient manufacturing of ceramic matrix composites.

Multidiscipline Modeling in Materials and StructuresVol. 21(6)
Tongji University (CN)
Affordable and clean energy
Openalex Percentile: Top 77%
Composite Material Mechanics
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Apparent viscosity modeling and flow simulation of precursor solutions for PIP process of ceramic matrix composites — Pengfei He, Yanni He, et al. · Multidiscipline Modeling in Materials and Structures (2025) | TGRS Research Map | TGRS