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This research aims to develop GPU-based algorithms for analyzing flowfields in turbomachinery efficiently.

Implicit Simulation of Turbomachinery Flows on Structured Meshes Using Graphics Processing Units

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This research aims to develop GPU-based algorithms for analyzing flowfields in turbomachinery efficiently.
Developed a GPU-accelerated CFD solver for steady and unsteady flow analyses.
Incorporated a data-parallel lower–upper relaxation method for improved convergence.
Implemented mixing plane and sliding plane methods for rotor-stator coupling.
Conducted parallel scalability tests on an eight-GPU cluster.
Validated the results against experimental data in a fan stage and axial compressor.
Achieved speedup factors of 18 and 24 for single- and double-precision computations, respectively.
Demonstrated high parallel efficiency of 96% for strong scaling and 98% for weak scaling.
Validation results showed good agreement with experimental data for flow profiles and performance metrics.
Analysis of stall behavior at 65% design speed aligned with experimental findings.

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Reveals efficient flow analysis in turbomachinery using GPU-accelerated CFD, highlighting significant performance improvements.

Wang et al. (2026) studied this question.

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