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The numerical treatment of fluid-particle systems is a very challenging problem because of the complex coupling phenomena occurring between the two phases. Although accurate mathematical modelling is available to address this kind of…

Numerical Analysis · Mathematics 2024-03-22 Arash Hajisharifi , Rahul Halder , Michele Girfoglio , Andrea Beccari , Domenico Bonanni , Gianluigi Rozza

Predictive modeling of blood flow and pressure have numerous applications ranging from non-invasive assessment of functional significance of disease to planning invasive procedures. While several such predictive modeling techniques have…

Extensive studies suggested that fluid mechanical markers of intracranial aneurysms (IAs) derived from Computational Fluid Dynamics (CFD) can indicate disease progression risks, but to date this has not been translated clinically. This is…

Machine Learning · Computer Science 2026-01-30 Yiying Sheng , Wenhao Ding , Dylan Roi , Leonard Leong Litt Yeo , Hwa Liang Leo , Choon Hwai Yap

Computational fluid dynamics (CFD) is a valuable asset for patient-specific cardiovascular-disease diagnosis and prognosis, but its high computational demands hamper its adoption in practice. Machine-learning methods that estimate blood…

Machine Learning · Computer Science 2024-06-18 Julian Suk , Pim de Haan , Phillip Lippe , Christoph Brune , Jelmer M. Wolterink

Due to the limited accuracy of 4D Magnetic Resonance Imaging (MRI) in identifying hemodynamics in cardiovascular diseases, the challenges in obtaining patient-specific flow boundary conditions, and the computationally demanding and…

Machine Learning · Computer Science 2025-03-25 Oscar L. Cruz-González , Valérie Deplano , Badih Ghattas

Computational fluid dynamics (CFD) is a valuable tool for personalised, non-invasive evaluation of hemodynamics in arteries, but its complexity and time-consuming nature prohibit large-scale use in practice. Recently, the use of deep…

Machine Learning · Computer Science 2022-01-21 Julian Suk , Pim de Haan , Phillip Lippe , Christoph Brune , Jelmer M. Wolterink

The simulation of microcirculatory blood flow in realistic vascular architectures poses significant challenges due to the multiscale nature of the problem and the topological complexity of capillary networks. In this work, we propose a…

Numerical Analysis · Mathematics 2025-12-12 Paolo Botta , Piermario Vitullo , Thomas Ventimiglia , Andreas Linninger , Paolo Zunino

Reducing the computational time required by high-fidelity, full order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. While FOMs,…

Numerical Analysis · Mathematics 2022-02-09 Ludovica Cicci , Stefania Fresca , Andrea Manzoni , Alfio Quarteroni

Abdominal aortic aneurysms (AAAs) are pathologic dilatations of the abdominal aorta posing a high fatality risk upon rupture. Studying AAA progression and rupture risk often involves in-silico blood flow modelling with computational fluid…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Patryk Rygiel , Julian Suk , Christoph Brune , Kak Khee Yeung , Jelmer M. Wolterink

Coronary heart disease (CHD) remains a top reason of mortality worldwide. This study introduces a novel approach by integrating patient-specific Multi-slice CT scans into CAD models and employing a one-dimensional numerical framework to…

Medical Physics · Physics 2025-07-01 Oeshee Roy , Priyanshu Ghosh , Sayan Karmakar , Supratim Saha

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by…

Prediction of the blood flow characteristics is of utmost importance for understanding the behavior of the blood arterial network, especially in the presence of vascular diseases such as stenosis. Computational fluid dynamics (CFD) has…

Machine Learning · Computer Science 2021-11-11 Mohammad Farajtabar , Mohit Biglarian , Morteza Miansari

Reduced Order Modelling (ROM) has been widely used to create lower order, computationally inexpensive representations of higher-order dynamical systems. Using these representations, ROMs can efficiently model flow fields while using…

Fluid Dynamics · Physics 2021-10-13 Pranshu Pant , Ruchit Doshi , Pranav Bahl , Amir Barati Farimani

In this work we propose a low rank approximation of high fidelity finite element simulations by utilizing weights corresponding to areas of high stress levels for an abdominal aortic aneurysm, i.e. a deformed blood vessel. We focus on the…

Numerical Analysis · Mathematics 2023-05-09 Christoph Striegel , Göran Kauermann , Jonas Biehler

Computational modeling of the brain has become a key part of understanding how the brain clears metabolic waste, but patient-specific modeling on a significant scale is still out of reach with current methods. We introduce a novel approach…

Quantitative Methods · Quantitative Biology 2025-06-12 Andreas Solheim , Geir Ringstand , Per Kristian Eide , Kent-Andre Mardal

In this paper, a type of novel projection-based, time-segmented reduced order model (ROM) is proposed for dynamic fluid-structure interaction (FSI) problems based upon the arbitrary Lagrangian--Eulerian (ALE)-finite element method (FEM) in…

Computational Engineering, Finance, and Science · Computer Science 2024-02-16 Qijia Zhai , Shiquan Zhang , Pengtao Sun , Xiaoping Xie

Coronary heart disease (CHD) remains a leading cause of mortality worldwide. This study introduces a novel approach that integrates patient-specific Multi-slice CT scans into CAD models, using a one-dimensional numerical framework to assess…

Medical Physics · Physics 2025-05-21 Priyanshu Ghosh , Sayan Karmakar , Disha Mondal , Oeshee Roy , Supratim Saha

Typical approaches to patient-specific hemodynamic studies of cerebral aneurysms use image based computational fluid dynamics (CFD) and seek to statistically correlate parameters such as wall shear stress (WSS) and oscillatory shear index…

We present a numerical methodology for construction of reduced order models, ROMs, of fluid flows through the combination of flow modal decomposition and regression analysis. Spectral proper orthogonal decomposition, SPOD, is applied to…

Fluid Dynamics · Physics 2019-07-24 Hugo F. S. Lui , William R. Wolf

Reduced Order Models (ROMs) have been regarded as an efficient alternative to conventional high-fidelity Computational Fluid Dynamics (CFD) for accelerating the design and optimization processes in engineering applications. Many industrial…

Numerical Analysis · Mathematics 2026-01-15 Shenhui Ruan , Andreas G. Class , Gianluigi Rozza