Coupling STAR-CCM+ with Optimization Software IOSO by the example of axial 8-stages jet engine compressor.

Transcription

1 Coupling STAR-CCM+ with Optimization Software IOSO by the example of axial 8-stages jet engine compressor. Folomeev V., (Sarov Engineering Center) Iakunin A., (JSC Klimov) 1

2 Objectives To create the procedure for coupling CFD code STAR- CCM+ with optimization software IOSO To improve the law of turning guide vanes for the first tree stages of axial compressor. 2

3 Main steps Create axial 8-stages compressor CFD model Develop the optimization task IOSO supports only windows platform when clusters usually operate on Linux, thus we need do develop the procedure for net connection 3

4 Typical design iterations 4

5 CFD model Steady model with mixing plane interfaces. Low-Reynolds k-omega turbulence model Turbulence Suppression model Polyhedral mesh about 15 mln cells with near wall prism layers Optimization process involved 500 cores of IBM cluster 5

6 CFD modeling visualization 6

7 CFD modeling visualization 7

8 CFD modeling visualization First rotating row Pressure side Suction side 8

9 CFD modeling convergence history 9

10 Results of CFD calculation 10

11 Main features of the IOSO optimization technology IOSO Technology is based on the response surface technology. That is why the strategy differs significantly from the well-known approaches to optimization. The strategy has higher efficiency and provides wider range of capabilities than standard algorithms. The main advantage one can get from using the IOSO Technology is ability to solve very complex optimization tasks. IOSO Technology algorithms: Are independent of the optimization task types Have good global properties and in the majority of the cases are able to find the global optimum Have high convergence rate and allow to quickly and efficiently find the region where optimum is located Are highly robust with the respect to the computational process Allow for robust solving of stochastic optimization tasks, even if such problems have high level of noise Provide the capabilities to solve real-life optimization tasks that involve complex modern high fidelity mathematical models or engineering applications (for example, 3D CAD, CFD or FEA software). Allow for solving robust design optimization tasks, including multidimensional single and multiobjective optimization tasks. Are very simple to use even for solving complex practical tasks of nonlinear optimization. Have full-automatic optimization algorithms which do not need to be tuned up by a user. 11

12 Optimization task For each rotational rate we solve independent optimization task Independent parameters Leading vane angle constrained parameters Mass flow Objective function efficiency 1-stage stator angle Pressure rise 2-stage stator angle 12

13 Setting the optimization task IOSO uses file base coupling with STAR-CCM+ 13

14 Scripting STAR-CCM+ macro STAR-CCM+ macro provides full java functionality including net sockets and supports ssh libraries. This was used in creation client-server application. 14

15 Scheme of coupling IOSO generates text file with input parameters IOSO runs Server.java Server.java reads input file Server.java runs ssh on remote cluster and starts STAR-CCM+ with macro Server.java opens server sockets and sends input variables STAR-CCM+ with macro receives input variables, performs CFD calculations and sends back to Server.java output variables Server.java receives output values and writes output file for IOSO IOSO reads output file and analyses parameters for a next iteration 15

16 Results of optimization The normal rotation rate regime was examined firstly It was found that optimal configuration is nearly to zero for all variable angles with variation less than 0.5 degree. This is consistent with analytical compressor design methods. The convergence of the optimization process was reached within 30 iterations. It approximately corresponds to 1 week of calculation on 500 cores of modern cluster solution. 16

17 Conclusions The main task of this work was to develop procedure for coupling CFD code STAR-CCM+ with optimization software IOSO. This task was reached. Axial 8-stages compressor served as an example for the main task. The robust CFD model of the compressor was created and tested. This model is appropriate for the automatic calculations with varying geometry parameters. The results of the optimization process are in agreement with other analytical methods of prediction compressor performance. It is presumed that the accuracy may be improved with complication of CFD model, for instance including harmonic balance model. 17

18 Thank you for your attention 18