Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 4, 2018Open Access

Fitting shear-thinning rheological models to experimental blood data reveals parameter non-identifiability, meaning parameters cannot be uniquely determined or physically interpreted.

View Full Paper
Ask AI
Bookmark
Share

Population

Computational models of shear-thinning complex fluids applied to hemodynamics

Design

Other

Key result

Fitting shear-thinning rheological models to experimental blood data reveals parameter non-identifiability, meaning parameters cannot be uniquely determined or physically interpreted.

Authors

MGMeurig T. GallagherRWRichard A. J. WainSDSonia Dari

Discussion

Loading...

Member takes

Overview

Non-identifiability in shear-thinning models warrants caution for hemodynamic flow predictions; leaves open the need for identifiable alternatives in research.

Structured PICO

P
Population
Computational models of shear-thinning complex fluids (Bird, Carreau, Cross, and Yasuda models) applied to hemodynamics
I
Intervention
Parameter inference by fitting rheology experiments and synthetic data simulations
O
Outcome
Parameter identifiability and flow profile prediction

Parameter identifiability is an intrinsic problem in common shear-thinning rheological models used in hemodynamics, meaning inferred parameters cannot reliably predict physical fluid properties or flow behaviors.

Limitations

  • Analysis based on specific steady-shear experimental datasets
  • Does not cover time-dependent flows or extensional rheometry

Cite This Study

Gallagher et al. (2018) studied Blood rheology. Shear-thinning rheological models was evaluated on Parameter identifiability. Fitting shear-thinning rheological models to experimental blood data reveals parameter non-identifiability, meaning parameters cannot be uniquely determined or physically interpreted.

synapsesocial.com/papers/6a9f60d40167e551126900cdhttps://doi.org/10.48550/arxiv.1810.02292
View Full Paper
Ask AI
Bookmark
Share