Adaptive parameterizations for optimization and numerical methods in engineering

group leader

prof. Damir Vučina, PhD

Biography · Publications · Teaching duties

associates

assoc. prof. Milan Ćurković, PhD

Biography · Publications · Teaching duties

assoc. prof. Igor Pehnec, PhD

Biography · Publications · Teaching duties

assist. prof. Ivo Marinić-Kragić, PhD

Biography · Publications · Teaching duties

Domagoj Samardžić, MScEng

Biography · Publications · Teaching duties

Research topics

  1. Numerical optimization algorithms
  2. Geometric modelling
  3. Evolutionary algorithms
  4. Computational fluid dynamics
  5. Applications: fluid mechanics, solid mechanics, FEA and CFD analysis
  6. Fluid flow experimental measurements

Description of laboratory and equipment

  • Lab for optimization and design, Lab for rapid prototyping C614, equipment: 3D scanners with high resolution and accuracy GOM ATOS I and GOM ATOS COMPACT 8, 3D printers Prusa and Zortrax, milling machine Proxxon FF 500 CNC Micro Mill, computers and workstations
  • Basic test bed for VAWT
  • Lab for CFD, c515, equipment for fluid mechanics experiments
  • Lab for numerical modelling and optimization C617
  • Lab for fluid mechanics and hydraulic machinery A134 Equipment: hydraulic centrifugal pump systems, centrifugal and axial fan systems, Filtration Systems, Pressure Transmitter, Pitot tube, 3D hot wire anemometers IFA 300 TSI 1240…
  • Lab for CFD – 4 computers

Contacts with academic and other institutions

  • University of Trieste, Italy
  • University of Maribor, Faculty of Mechanical Engineering (FS), Slovenia
  • University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture (FSB), Croatia
  • University of Split, Faculty of Science (PMFST), Croatia
project title

Adaptive parameterizations for optimization and numerical methods in engineering (DADAPT)

Description of research in a 5-year term

  • 2D and 3D adaptive and dynamic parameterizations based on features detected in 3D clouds
  • Dynamic partitioning according to features
  • Parameterizations with reduced number of parameters for shape optimization  Adaptations of GA coding for dynamic multi-partition models
  • Development of numerically efficient and dynamically adaptive parametric shape coding for optimization
  • Numerical turbulence models for different types of flow – analysis and parameters adjustments