PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 16, 2026Scientific Reports0 citationsOpen Access

Effect of blade parameters on radial turbine rotor aerodynamics

View Full Paper
MFMostafa Abdo FawazMilitary Technical CollegeAHAhmed Farid Ayad HassanMilitary Technical CollegeMSMohammed ShaheenMilitary Technical College

Key Points

  • This work aims to explore the aerodynamic effects of blade parameters on radial turbine performance.
  • Developed a CFD-based numerical model for a reference rotor
  • Systematically varied blade angle distribution, thickness profile, and blade count
  • Assessed the impact on turbine efficiency and mass flow
  • Optimized geometric adjustments enhance flow uniformity
  • Minimized secondary losses associated with poor design
  • Improved overall energy conversion efficiency observed

Abstract

Abstract Radial turbines play a vital role in turbochargers and compact power systems, where efficiency and size optimization are crucial. However, the combined aerodynamic effects of key rotor geometric features–namely blade angle distribution, thickness profile, and blade count–have not been comprehensively examined. This work presents a unified CFD-based methodology to assess how coordinated changes in these parameters influence turbine performance. A validated numerical model of a reference rotor was employed to systematically vary each design factor and evaluate its impact on efficiency and reduced mass flow. The investigation demonstrates that carefully optimized geometric adjustments can enhance flow uniformity, minimize secondary losses, and improve overall energy conversion. The study establishes clear performance trends supported by detailed flow-field analysis and provides design-oriented correlations that can guide future optimization of radial turbine rotors for high-efficiency operation.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Fawaz et al. (2026) studied this question.

synapsesocial.com/papers/6969d4dc940543b977709c3ahttps://doi.org/10.1038/s41598-025-33442-4
Ask AI
Helpful
Bookmark
Share
View Full Paper