Naslov
Development of an automated process for turbine blade optimisation

Autori
Šojat, Borna

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, diplomski rad, diplomski

Fakultet
Fakultet strojarstva i brodogradnje

Mjesto
Zagreb

Datum
27.01

Godina
2017

Stranica
117

Mentor
Hrvoje Jasak

Ključne riječi
Optimisation, Turbomachinery, Evolutionary algorithm, Compressible transonic fluid flow

Sažetak
Computational fluid dynamics (CFD) is a critical part in optimisation of turbomachinery components. Constant commercial pressure to produce parts of highest possible quality both in shortest possible time and with maximal reduction in price, are the reasons why CFD has become a necessity. Utilization of CFD enables faster design cycles, better performance, and reduction in cost and weight of the final product. CFD is of greatest importance in optimisation procedures because much more blade designs as well as blade parameters can be examined than it would be the case in an experimental study. Also CFD enables visualisation of complex fluid flow patterns over critical component geometries. Developed automated optimisation process consists of the following steps: 1. Blade geometry parametrisation using a periodic B-spline curve, 2. Morphing of the computational mesh 3. Numerical calculation of a compressible fluid flow through turbine blade passage, and 4. Obtaining the new set of control polygon vertices. In the parametrisation step, blade geometry, which is defined with the set of control polygon vertices, is approximated with a periodic B-spline curve of 5th degree. 40 parametrisation points are extrapolated between each pair of control polygon vertices. In the mesh morphing step, numerical mesh is deformed in respect with the parametrisation points coordinates. Numerical calculation of compressible fluid flow is conducted in the third step of this optimisation process in which objective function values are obtained. Objective functions are physical values derived from flow variables, which describe the characteristics of each blade geometry. Using this values, new set of control polygon vertices is calculated with Multi-objective evolutionary algorithm. In this way, the optimisation loop is closed and restarted. Due to the possibility of working with very irregular and distorted starting geometries, the developed automated optimisation process has proven to be robust and effective.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo

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