used mean values of all input parameters) and also betterthan the design proposed by an experienced heat transferAVIO engineer, who used standard best practice methods.Furthermore the large number of experiences gained by theseveral simulations run by the optimizer generated a virtualdatabase of tip cooling configurations, allowing the designerto find laws, functions and correlation between inputparameters and performance output, with a further anddeeper insight on this specific design blade cooling problem.

This study is part of an AVIO project concerning the develop-ment of High Pressure Turbine blades with advanced coolingsystems. Due to the high gas temperatures entering theturbine of the most recent aero-engines in general up to 2000K at the turbine inlet at 40 bars, a very efficient coolingsystem is required in order to maintain the metal tempera-tures below the allowable limits. This means to use a certainamount of "cold" air directly extracted from the compressor,with a significant negative impact on the engine perfor-mance.

One of the most critical area, from a thermal point of view, isthe tip region of the unshrouded rotor blades. Tip regions aregenerally cooled using rotor internal air ejected in the flowpath through a series of small holes located in the tipsurfaces. The ejected air must cover all the surfaces in orderto create a cold filmbetween the hot gasand the metal. As thetip region is character-ized by a very complex3D flow field, it is verydifficult to optimize thecooling system usingthe standard designmethodologies, alsoconsidering the otherblade tip requirementssuch as minimizing the

Methodology

A novel methodology has been used to design the layout ofthe tip cooling nozzles of a high pressure rotor blade turbine.The methodology used is through a complete CAE approach,by means of a parametric CFD model which is run many timesfor the exploration of several designs by an optimizer.Hence the design is carried out automatically by parallelcomputations, with the optimization algorithms taking thedecisions rather than the design engineer. The engineerinstead takes decision regarding the physical settings of theCFD model to employ, the number and the extension of thegeometrical parameters of the blade tip holes and the optimi-zation algorithms to be employed.

The final design of the tip cooling geometry found by theoptimizer proved to be better than the base design (which

Optimization of Gas Turbine BladesTip Cooling Holes Layout Design via Multiobjective Genetic Algoritms

And Artificial Neural Network Expert System

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hot leakage air from pressure to suction side, which has anegative impact on turbine aerodynamic efficiency.For these reasons the area of the tip is investigated with aparametric CFD approach: a parametric model is run severaltimes guided by an optimization algorithm, such that anoptimal solution in terms of performance can be found.

This kind of approach requiresto link an optimizationsoftware (modeFRONTIER) toa 3-D CFD code (ICEM-CFX5)with the goal to find theoptimal values of somegeometrical parameters of thetip area of the high pressurerotor blade, such that certainperformance objectives arereached. As a consequence ofthe geometrical complexity ofthe problem and of the highcomputational time, the useof the interpolators or expert system techniques becomescompulsory if a 3-D fluid-dynamic optimisation has to beapproached.Several methods are generally available within optimizationsoftware: RSM, ANN, etc. In this case a ANN method waschosen because of the nonlinearity of the system.

This way, after a preliminary series of CFD analyses and afterthe estimation of ANN, the 3-D CFD model can be substitutedby a series of mathematical functions and the computationaltime is considerably reduced. The expert system, represented

Blade Cascade

modeFRONTIERmodeFRONTIER provides a powerful and easy to use solution toinclude CAE software into an integrated design chain where CAD,FEM, CFD, cost prediction and Six-Sigma design are usedsimultaneously and in a distributed environment to push theenvelope in product development.

modeFRONTIER includes a wide range of numerical methods for DOE,Robust Design, Optimization and data-modelling. A powerful post-processing and easy to use process flow integration greatly enhanceboth the engineers as well as the decision maker capabilityautomating frequent tasks while filtering only useful information.

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by a ANN, must be introduced after a fair number of analysisare run, such that the expert system is reliable.

The error of the expert system is a known value and is theparameter which yields the accuracy of the interpolatorrelative to the database of real experiments so far acquired. Itis up to the designer to chose the threshold error value of hisexpert system. Basically more CFD analysis we run, the moretrained and the more accurate the expert system becomes,but with an increase of the CPU effort, and viceversa.

A parametric batch procedure allows the creation of differentgeometrical models, the mesh generation and the CFDanalyses of the blades in an automatic way.A series of preliminary CFD simulations is planned and ascreening is performed in order to build an input-outputdatabase.ANN coefficients for the two layers are calculated by theoptimizer. A MOGA algorithm investigates runs with furtherCFD "Virtual" analysis, exploring the space of possiblesolutions on the ANN. Basically a virtual optimization of thecooling system is carried out without further CPU expensiveCFD analysis.The best virtual solutions are selected and the ANN virtualsolutions are validated by a "real" CFD analysis.More accurate Neural Nets can now be estimated with a larger

database. The virtualoptimization can beexecuted again and newand more performingdesigns can be found.T h i s p r o c e du r e i srepeated till the desiredconvergence to the set ofoptimal solutions isachieved.

Finally a layout of tipcooling nozzles is foundby the optimizer andvalidated by a CFD

analysis. The final design chosen proved to yield the sameheat transfer performance with a reduction of approximated16% of the cooling air required. Hence we can conclude that aremarkable increase of performance of 16% is obtainedthanks to an innovative complete CAE design process withCFD parametic models evolved by optimization algorithms.

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Key partner in Design Process InnovationmodeFRONTIER® is a trademark of ESTECO srl, Italy