October 9, 2025SymmetryOpen Access

Surrogate Modelling and Simulation Approaches for Renal Artery Haemodynamics: Balancing Symmetry in Computational Cost and Accuracy

View Full Paper

Ask AI

Bookmark

Authors

DCDávid CsonkaUniversity of Pecs TSTamás StorczUniversity of Pecs AKAndrás KaszásUniversity of Pecs

Discussion

Member takes

Implication

This comparative analysis evaluates surrogate modelling and CFD techniques for renal artery haemodynamics, suggesting improved computational efficiency.

Key Points

Surrogate models trained on over 6500 samples achieved high predictive accuracy (R2 > 0.98) for velocity and pressure.
GPU-accelerated voxel simulations provided a viable alternative, while 2D FEA offered sufficient accuracy at lower runtimes.
Branching angles and blood pressure were systematically varied to assess their effects on velocity, pressure, and turbulence.
Symmetry in model fidelity and computational efficiency highlights a resource-effective methodology for vascular applications.

Cite This Study

Csonka et al. (2025) studied this question.

synapsesocial.com/papers/68e7f0af2d7e30942762c844 https://doi.org/10.3390/sym17101681

View Full Paper

Ask AI

Bookmark

Implication

This comparative analysis evaluates surrogate modelling and CFD techniques for renal artery haemodynamics, suggesting improved computational efficiency.

Surrogate Modelling and Simulation Approaches for Renal Artery Haemodynamics: Balancing Symmetry in Computational Cost and Accuracy

Discussion

Member takes

Implication

Key Points

Cite This Study

Surrogate Modelling and Simulation Approaches for Renal Artery Haemodynamics: Balancing Symmetry in Computational Cost and Accuracy

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider