Evidence map›Paper›PMID 37670027›Full record

ArticleScientific reports2023

Assessing the impact of turbulent kinetic energy boundary conditions on turbulent flow simulations using computational fluid dynamics.

Eui Cheol Jung, Gyu-Han Lee, Eun Bo Shim, Hojin Ha

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Eui Cheol JungKangwon Institute of Inclusive Technology, Kangwon National University, 1, Kangwondaehak-Gil, Chuncheon, 24341, Republic of Korea.
Gyu-Han LeeInstitute of Medical Devices, Kangwon National University, 1, Kangwondaehak-Gil, Chuncheon, 24341, Republic of Korea.
Eun Bo ShimDepartment of Mechanical and Biomedical Engineering, Kangwon National University, 1, Kangwondaehak-Gil, Chuncheon, 24341, Republic of Korea.
Hojin HaDepartment of Mechanical and Biomedical Engineering, Kangwon National University, 1, Kangwondaehak-Gil, Chuncheon, 24341, Republic of Korea. hojinha@kangwon.ac.kr.

Funding

National Research Foundation of Korea No. 2020R1A4A1019475
6 · The paper itself

Abstract

Computational fluid dynamics has been widely used to study hemodynamics, but accurately determining boundary conditions for turbulent blood flow remains challenging. This study aims to investigate the effect of patient-specific turbulence boundary conditions on the accuracy of turbulent flow simulation. Using a stenosis model with 50% severity in diameter, the post-stenosis turbulence flow region was simulated with different planes to obtain inlet boundary conditions and simulate downstream flows. The errors of simulated flow fields obtained with turbulence kinetic energy (TKE) boundary data and arbitrary turbulence intensity were compared. Additionally, the study tested various TKE data resolutions and noise levels to simulate experimental environments. The mean absolute error of velocity and TKE was investigated with various turbulence intensities and TKE mapping. While voxel size and signal-to-noise ratio of the TKE data affected the results, simulation with SNR > 5 and voxel size < 10% resulted in better accuracy than simulations with turbulence intensities. The simulation with appropriate TKE boundary data resulted in a more accurate velocity and turbulence field than those with arbitrary turbulence intensity boundary conditions. The study demonstrated the potential improvement of turbulent blood flow simulation with patient-specific turbulence boundary conditions, which can be obtained from recent measurement techniques.

Identifiers

PMID37670027
PMCPMC10480182

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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.