ArticleAnnals of biomedical engineering2021
On the Periodicity of Cardiovascular Fluid Dynamics Simulations.
Article in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Simulations predict improved valve performance without direct leaflet intervention after neonatal truncus arteriosus repair.The Journal of thoracic and cardiovascular surgery · 2026Article
- MRI-Based Pressure Gradient Mapping in Patient-Specific Models of Coarctation of the Aorta.medRxiv : the preprint server for health sciences · 2026Article
- Developing a non-invasive diagnostic framework for the fractional flow reserve quantification in left coronary arteries: validation with patient cases.Frontiers in physiology · 2026Article
- Establishing Hemodynamic Convergence Framework for Coronary Digital Twins Under Realistic Dynamic Heart Rates.Physics of fluids (Woodbury, N.Y. : 1994) · 2025Article
- Tube2FEM: a general-purpose highly automated pipeline for flow-related processes in (embedded) tubular objects.Royal Society open science · 2025Article
- Experiments and Simulations to Assess Exercise-Induced Pressure Drop Across Aortic Coarctations.Journal of biomechanical engineering · 2025Article
- Assessment of Aortic Dissection Remodeling With Patient-Specific Fluid-Structure Interaction Models.IEEE transactions on bio-medical engineering · 2025Article
- svZeroDSolver: A modular package for lumped-parameter cardiovascular simulations.Journal of open source software · 2025Article
- Hybrid physics-based and data-driven modeling of vascular bifurcation pressure differences.Computers in biology and medicine · 2025Article
- Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins.NPJ digital medicine · 2024Article
- Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements.Annals of biomedical engineering · 2024Article
- Learning reduced-order models for cardiovascular simulations with graph neural networks.Computers in biology and medicine · 2024Article
- Patient-specificFrontiers in cardiovascular medicine · 2024Review
- Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic Maps.International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) · 2023Article
- Hemodynamics of vascular shunts: trends, challenges, and prospects.Biophysical reviews · 2023Review
- A Vector Fitting Approach for the Automated Estimation of Lumped Boundary Conditions of 1D Circulation Models.Cardiovascular engineering and technology · 2023Article
- Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease.Biophysics reviews · 2023Review
- svMorph: Interactive Geometry-Editing Tools for Virtual Patient-Specific Vascular Anatomies.Journal of biomechanical engineering · 2023Article
- A Brief Note on Building Augmented Reality Models for Scientific Visualization.Finite elements in analysis and design : the international journal of applied finite elements and computer aided engineering · 2023Article
- Automated generation of 0D and 1D reduced-order models of patient-specific blood flow.International journal for numerical methods in biomedical engineering · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Three-dimensional cardiovascular fluid dynamics simulations typically require computation of several cardiac cycles before they reach a periodic solution, rendering them computationally expensive. Furthermore, there is currently no standardized method to determine whether a simulation has yet reached that periodic state. In this work, we propose the use of an asymptotic error measurement to quantify the difference between simulation results and their ideal periodic state using open-loop lumped-parameter modeling. We further show that initial conditions are crucial in reducing computational time and develop an automated framework to generate appropriate initial conditions from a one-dimensional model of blood flow. We demonstrate the performance of our initialization method using six patient-specific models from the Vascular Model Repository. In our examples, our initialization protocol achieves periodic convergence within one or two cardiac cycles, leading to a significant reduction in computational cost compared to standard methods. All computational tools used in this work are implemented in the open-source software platform SimVascular. Automatically generated initial conditions have the potential to significantly reduce computation time in cardiovascular fluid dynamics simulations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.