Article In: scopus, cienciavitae, orcid
Time-dependent strategy for improving aortic blood flow simulations with boundary control and data assimilation
Applied Mathematics and Computation
— 2025 — Elsevier BV
Key information
Authors:
Published in
May 2025
Abstract
Understanding time-dependent blood flow dynamics in arteries is crucial for diagnosing and treating cardiovascular diseases. However, accurately predicting time-varying flow patterns requires integrating observational data with computational models in a dynamic environment. This study investigates the application of data assimilation and boundary optimization techniques to improve the accuracy of time-dependent blood flow simulations. We propose an integrated approach that combines data assimilation methods with boundary optimization strategies tailored for time-dependent cases. Our method aims to minimize the disparity between model predictions and observed data over time, thereby enhancing the fidelity of time-dependent blood flow simulations. Using synthetic time-series observational data with added noise, we validate our approach by comparing its predictions with the known exact solution, computing the -norm to demonstrate improved accuracy in time-dependent blood flow simulations. Our results indicate that the optimization process consistently aligns the optimized data with the exact data. In particular, velocity magnitudes showed reduced discrepancies compared to the noisy data, aligning more closely with the exact solutions. The analysis of pressure data revealed a remarkable correspondence between the optimized and exact pressure values, highlighting the potential of this methodology for accurate pressure estimation without any previous knowledge on this quantity. Furthermore, wall shear stress (WSS) analysis demonstrated the effectiveness of our optimization scheme in reducing noise and improving prediction of a relevant indicator determined at the postprocessing level. These findings suggest that our approach can significantly enhance the accuracy of blood flow simulations, ultimately contributing to better diagnostic and therapeutic strategies.
Publication details
Authors in the community:
Jorge Filipe Duarte Tiago
ist90590
Publication version
VoR - Version of Record
Publisher
Elsevier BV
Link to the publisher's version
https://www.sciencedirect.com/science/article/pii/S0096300324007276?via%3Dihub
Title of the publication container
Applied Mathematics and Computation
First page or article number
129266
Volume
493
ISSN
0096-3003
Fields of Science and Technology (FOS)
mathematics - Mathematics
Keywords
- Adjoint problem
- Data assimilation
- Computational fluid dynamics
- Navier-Stokes equations
- Boundary control
Publication language (ISO code)
eng - English
Rights type:
Open access
Financing entity
Fundação para a Ciência e a Tecnologia
Identifier for the funding entity: PTDC/MAT-APL/7076/2020