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, cilt.95, ss.433-454, 2025 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 95
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.cjph.2025.02.015
  • Dergi Adı: CHINESE JOURNAL OF PHYSICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, INSPEC, zbMATH
  • Sayfa Sayıları: ss.433-454
  • Hacettepe Üniversitesi Adresli: Evet

Özet

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