Projects

Twin-screw machine
Twin-screw machine
Twin-screw machine
Twin-screw machine

CSC-funded research projects

Theory and practical algorithms for NURBS Surface/Surface Intersection (SSI) in industrial software

Duration

09/2024 - 09/2028

Candidate

Linlin Li

Multi-sided parameterization method with hierarchical refinement for Isogeometric Analysis and its application in twin-screw rotary compressors

Duration

10/2022 - 10/2024

Candidate

Mengyun Wang

PDE-based parameterization method in Isogeometric Analysis and its application in twin-screw rotary compressors

Rotary-type positive displacement machines (PDMs) are widely used in industry to produce high-pressure air and gases. A recent trend is screw compressors with variable pitch and/or variable rotor profiles, which enable such performance improvements. The core idea is to vary the pitch angle and/or the rotor profile from the inlet to the outlet either in discrete segments or continuously. The goal of this two-years project is to develop volumetric parametrization methods for twin-screw rotary compressors using Isogeometric Analysis.

Duration

09/2021 - 09/2023

Candidate

Ji Ye

Numerical Simulation of Surface-Piercing Propellers by SPH/FEM methods

Duration

09/2014 - 09/2018

Candidate

Xu Fei

Selected contributions

  • Ye Ji, Matthias Möller, Yingying Yu, and Chungang Zhu. Boundary parameter matching for isogeometric analysis using Schwarz-Christoffel mapping. Engineering with Computers, July 2024. [ DOI | http ]
  • Ye Ji, Kewang Chen, Matthias Möller, and Cornelis Vuik. On an improved PDE-based elliptic parameterization method for isogeometric analysis using preconditioned Anderson acceleration. Computer Aided Geometric Design, 102:102191, 2023. [ DOI ]
  • Ye Ji and Matthias Möller. Mesh Generation for Twin-Screw Compressors by Spline-Based Parameterization Using Preconditioned Anderson Acceleration, pages 77--87. Springer Nature Switzerland, 2024. [ DOI | http ]
  • Ye Ji and Matthias Möller. Mesh Generation for Twin-Screw Compressors by Spline-Based Parameterization Using Preconditioned Anderson Acceleration, pages 77--87. Springer Nature Switzerland, 2024. [ DOI | http ]