Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations
type: Item
instance of: scholarly article
title: Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations
zbMATH Open document ID: 1390.76945
author: Justin S. Tran
author: D. Schiavazzi
author: Abhay B. Ramachandra
author: Andrew M. Kahn
author: A. L. Marsden
published in: Computers and Fluids
publication date: 2018-06-27T00:00:00Z
Mathematics Subject Classification ID: 76Z05
Mathematics Subject Classification ID: 76M25
zbMATH DE Number: 6895057
zbMATH Keywords: coronary flow
zbMATH Keywords: hemodynamics
zbMATH Keywords: multiscale cardiovascular simulation
zbMATH Keywords: data assimilation
zbMATH Keywords: parameter estimation
zbMATH Keywords: lumped boundary circulation models
zbMATH Keywords: uncertainty quantification
MaRDI profile type: Publication
full work available at URL: j.compfluid.2016.05.015
OpenAlex ID: W2397934715
Wikidata QID: Q38978043
cites work: Q4447431
cites work: A generalized-\(\alpha\) method for integrating the filtered Navier-Stokes equations with a stabilized finite element method
cites work: Finite element modeling of blood in arteries
cites work: Adaptive proposal distribution for random walk Metropolis algorithm
cites work: Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
cites work: Identification in Parametric Models
cites work: Inference from iterative simulation using multiple sequences
cites work: Space-time and ALE-VMS techniques for patient-specific cardiovascular fluid-structure interaction modeling
cites work: A fully-coupled fluid-structure interaction simulation of cerebral aneurysms
cites work: Impact of geometric uncertainty on hemodynamic simulations using machine learning
DOI: 10.1016/J.COMPFLUID.2016.05.015
description: scientific article; zbMATH DE number 6895057