Semi-Analytic Jacobian-Forming Method for a Newton–Krylov Turbomachinery Flow Solver

Reynolds-averaged Navier–Stokes computational fluid dynamics solvers based on Newton–Krylov algorithms are becoming increasingly popular because of their favorable robustness and efficiency in achieving residual convergence, especially for edge-of-envelope cases. A key ingredient in Newton–Krylov algorithms is the efficient calculation of Jacobian matrices. The widely used graph-coloring method for Jacobian-forming, although straightforward to implement, is computationally expensive, thus impairing the overall efficiency of Newton–Krylov solvers. The semi-analytic approach can significantly reduce computational cost but requires sophisticated manual derivation when being extended to turbomachinery internal flow analysis. This paper introduces an efficient semi-analytic Jacobian-forming method for turbomachinery aerodynamic analysis. Special attention is given to Jacobian correction to account for periodic boundary conditions. The proposed method was compared against the graph-coloring approach on two test cases: a linear compressor cascade and a three-dimensional transonic rotor, with its performance thoroughly evaluated across different flow regimes. Results show that the semi-analytic approach can accelerate the Jacobian-matrix calculations by up to [Formula: see text]. Consequently, nonlinear flow analyses were accelerated by up to [Formula: see text]. The proposed semi-analytic Jacobian-forming method could also be applied to various advanced flow analyses that prefer a Jacobian-explicit approach, such as adjoint and eigenvalue analyses.

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Publication Details

Journal
AIAA Journal
Published
2025-11-12
DOI
https://doi.org/10.2514/1.j065806
Primary Topic
Turbomachinery Performance and Optimization
Type
article
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article

Semi-Analytic Jacobian-Forming Method for a Newton–Krylov Turbomachinery Flow Solver

Dingxi Wang, Jiazi Zhao, Sen Zhang, Sicheng Li et al.
AIAA Journal
Turbomachinery Performance and Optimization
article

Semi-Analytic Jacobian-Forming Method for a Newton–Krylov Turbomachinery Flow Solver

Dingxi Wang, Jiazi Zhao, Sen Zhang, Sicheng Li, Boqian Wang, Shenren Xu
article en

Abstract

Reynolds-averaged Navier–Stokes computational fluid dynamics solvers based on Newton–Krylov algorithms are becoming increasingly popular because of their favorable robustness and efficiency in achieving residual convergence, especially for edge-of-envelope cases. A key ingredient in Newton–Krylov algorithms is the efficient calculation of Jacobian matrices. The widely used graph-coloring method for Jacobian-forming, although straightforward to implement, is computationally expensive, thus impairing the overall efficiency of Newton–Krylov solvers. The semi-analytic approach can significantly reduce computational cost but requires sophisticated manual derivation when being extended to turbomachinery internal flow analysis. This paper introduces an efficient semi-analytic Jacobian-forming method for turbomachinery aerodynamic analysis. Special attention is given to Jacobian correction to account for periodic boundary conditions. The proposed method was compared against the graph-coloring approach on two test cases: a linear compressor cascade and a three-dimensional transonic rotor, with its performance thoroughly evaluated across different flow regimes. Results show that the semi-analytic approach can accelerate the Jacobian-matrix calculations by up to [Formula: see text]. Consequently, nonlinear flow analyses were accelerated by up to [Formula: see text]. The proposed semi-analytic Jacobian-forming method could also be applied to various advanced flow analyses that prefer a Jacobian-explicit approach, such as adjoint and eigenvalue analyses.

AIAA JournalVol. 64(2)
Northwestern Polytechnical University (CN)
Openalex Percentile: Top 55%
Turbomachinery Performance and Optimization
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Semi-Analytic Jacobian-Forming Method for a Newton–Krylov Turbomachinery Flow Solver — Dingxi Wang, Jiazi Zhao, et al. · AIAA Journal (2025) | TGRS Research Map | TGRS