TurboFlow - Release for JOSS submission

TurboFlow: Meanline Modelling of Axial Turbines

This release marks the version of Turboflow, submitted to the Journal of Open Source Software (JOSS).

TurboFlow is a Python package for mean-line modelling of axial turbines. It aims to offer flexible and reliable simulations for both performance prediction and design optimization, and should present a valuable resource for engineers and researchers working in the field of turbomachinery.

Core features

• Performance Prediction: Accurately predict the performance of axial turbines based on various input parameters.
• Design Optimization: Optimize preliminary axial turbine design to achieve optimal performance metrics.
• Equation-oriented problem formulation: Equation-oriented problem formulation for performance analysis and design optimization.
• Model consistency: The model is consistent for both performance prediction and design optimization.
• Efficient solution: The model adopts gradient-based root-finding and optimization solver
• Real gas fluid property analysis: Use CoolProp to determine thermohpysical properties.
• Flexible model: The model offers options for submodels for loss, deviation and choking calculations
• General geometry: Geometrical variables are defined to cover a wide range of designs, including multistage configurations.
  
• Easy-to-use: Intuitive and easy setup of input parameters for rapid development and analysis.
• Extensive Documentation: https://turbo-sim.github.io/turboflow/

Scientific Software - Peer-reviewed - Python
Published by lasseband 6 months ago