Application of computational fluid dynamics and physics informed neural networks in predicting rupture risk of thoracoabdominal aneurysms with fluid-structure interaction analysis

Rehman M. A. U., EKİCİ Ö., Farooq M. A., Talha R. M., Amir S.

CHINESE JOURNAL OF PHYSICS, pp.433-454, 2025 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2025
  • Doi Number: 10.1016/j.cjph.2025.02.015
  • Journal Name: CHINESE JOURNAL OF PHYSICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, INSPEC, zbMATH
  • Page Numbers: pp.433-454
  • Hacettepe University Affiliated: Yes

Abstract

laminar and turbulent flow conditions are explored to reflect the diastolic and systolic phases, respectively.