Z. Alsalihi

Multidisciplinary Optimization of a Radial Compressor for Microgas Turbine Applications

A multidisciplinary optimization system and its application to the design of a small radial compressor impeller are presented. The method uses a genetic algorithm and artificial neural network to find a compromise between the conflicting demands of high efficiency and low centrifugal stresses in the blades. Concurrent analyses of the aero performance and stress predictions replace the traditional time consuming sequential design approach. The aerodynamic performance, predicted by a 3D Navier-Stokes solver, is maximized while limiting the mechanical stresses to a maximum value. The stresses are calculated by means of a finite element analysis, and controlled by modifying the blade camber, lean, and thickness at the hub. The results show that it is possible to obtain a significant reduction of the centrifugal stresses in the blades without penalizing the performance.

Numerical Study of the Heat Transfer in Micro Gas Turbines

This paper presents a numerical investigation of the heat transfer inside a micro gas turbine and its impact on the performance. The large temperature difference between turbine and compressor in combination with the small dimensions results in a high heat transfer causing a drop in efficiency of both components. Present study aims to quantify this heat transfer and to reveal the different mechanisms that contribute to it. A conjugate heat transfer solver has been developed for this purpose. It combines a three-dimensional (3D) conduction calculation inside the rotor and the stator with a 3D flow calculation in the radial compressor, turbine and gap between stator and rotor. The results for micro gas turbines of different size and shape and different material characteristics are presented and the impact on performance is evaluated.

A comparison of conjugate heat transfer methods applied to an axial helium turbine

Abstract The current paper presents a numerical investigation of the conjugate heat transfer (CHT) in an axial helium turbine. The objective is the prediction of the cooling needed to keep the blade temperature below the allowable material limits. The cooling is applied at the hub by means of internal cooling channels. A CHT solver has been developed for this purpose. It combines a three-dimensional heat conduction calculation inside the blade with a three-dimensional Navier-Stokes flow calculation around the turbine blade. The required cooling at the blade root is calculated by imposing the temperature limit as boundary conditions at the bottom plane. Various alternative methods to implement the CHT are tested and compared. The results indicate that the so-called h-method is superior both in terms of accuracy and convergence speed.

Three Dimensional Design and Optimization of a Transonic Rotor in Axial Flow Compressors

This paper presents a 3-D optimization of a moderately loaded transonic compressor rotor by means of a multi-objective optimization system. The latter makes use of a Differential Evolutionary Algorithm in combination with an Artificial Neural Network and a 3D Navier-Stokes solver. Operating it on a cluster of 30 processors enabled the optimization of a large design space composed of the tip camber line and spanwise distribution of sweep and chord length. Objectives were an increase of efficiency at unchanged stall margin by controlling the shock waves and off-design performance curve. First, tests on a single blade row allowed a better understanding of the impact of the different design parameters. Forward sweep with unchanged camber improved the peak efficiency by only 0.3% with a small increase of the stall margin. Backward sweep with an optimized S shaped camber line improved the efficiency by 0.6% with unchanged stall margin. It is explained how the camber line control could introduce the forward sweep effect and compensate the negative effects of the backward sweep. The best results (0.7% increase in efficiency and unchanged stall margin) have been obtained by a stage optimization that also considered the spanwise redistribution of the rotor flow and loading to reduce the Mach number at the stator hub.Copyright

Multidisciplinary Optimization of a Radial Compressor for Micro Gas Turbine Applications

A multidisciplinary optimization system and its application to the design of a small radial compressor impeller are presented. The method uses a genetic algorithm and artificial neural network to find a compromise between the conflicting demands of high efficiency and low centrifugal stresses in the blades. Simultaneous analyses of the aero performance and stress predictions replace the traditional time consuming iterative design approach. The aerodynamic performance, predicted by a 3D Navier-Stokes solver, is maximized while limiting the mechanical stresses to a maximum value. The stesses are calculated by means of a finite element analysis and controlled by modifying the blade camber, lean and thickness at the hub. The results show that it is possible to obtain a significant reduction of the centrifugal stresses in the blades without penalizing the performance.© 2007 ASME

Numerical Study of the Heat Transfer in Micro Gasturbines

This paper presents a numerical investigation of the heat transfer inside a micro gasturbine and its impact on the performance. The high temperature difference between turbine and compressor in combination with the small dimensions results in a high heat transfer causing a drop in efficiency of both components. Present study aims to quantify this heat transfer and to reveal the different mechanisms that contribute to it. A conjugate heat transfer solver has been developed for this purpose. It combines a 3D conduction calculation inside the rotor and the stator with a 3D flow calculation in the radial compressor, turbine and gap between stator and rotor. The results for micro gasturbines of different size and shape and different material characteristics are presented and the impact on performance is evaluated.Copyright

Multipoint Multi-Objective Optimization of a Low Solidity Circular Cascade Diffuser in Centrifugal Blowers

In radial compressors or blowers, a low solidity circular cascade diffuser (LSD) is one of the effective devices to improve the pressure recovery at design flow rate while guaranteeing a wide operating range. The improvement is mainly attributed to the so called secondary flow effect, which reduces the flow separation on the LSD blade at small flow rates. However, it is very difficult to find out the effective shape of the blade in order to promote this secondary flow effect. In this paper, a multipoint and multi-objective optimization technique is applied to design the LSD blade of a centrifugal blower. The optimization method has been developed at the von Karman Institute for Fluid Dynamics (VKI), which makes use of an evolutionary algorithm, a metamodel as a rapid exploration tool, and a high fidelity 3D Navier-Stokes solver.The optimization is aiming at improving the static pressure coefficient at design point and at low flow rate condition while constraining the slope of the lift coefficient curve. Seven detailed design parameters describing the shape and position of the LSD vane were introduced, e.g. the radial spacing between impeller exit and the LSD leading edge, the radial chord length and the mean camber angle distribution of the LSD blade with five control points. Moreover, a small tip clearance of the LSD blade was applied in order to activate and to stabilize the secondary flow effect at small flow rate condition. The optimized LSD blade has an extended operating range of 114 % towards smaller flow rate as compared to the baseline design without deteriorating the diffuser pressure recovery at design point. The diffuser pressure rise and operating flow range of the optimized LSD blade are experimentally verified. It is found that the optimized LSD blade shows good improvement of the blade loading in the whole operating range, while at small flow rate the flow separation on the LSD blade has been successfully suppressed by the secondary flow effect. This is fully corresponding to the CFD predictions and demonstrates the effectiveness of the optimization methodology, by limiting the experimental testing to only two geometries.Copyright

Aerodynamic design optimization of a centrifugal compressor impeller based on an artificial neural network and genetic algorithm

Centrifugal compressors are applied to turbochargers, industrial compressors and turbo shaft gas turbine engines because of their high pressure ratio, relatively wide operating range and cost benefits. The internal flow in a centrifugal compressor impeller is however three dimensional and shows very complex flow phenomena, which makes the understanding of the loss generating mechanisms difficult and requires a considerable design effort to reach good performance. Especially turbocharger compressors impose a challenge to the designer when both a very wide operating range and high efficiency are required. The design effort can however be reduced by applying an advanced design optimization system as an alternative to a conventional manual design based on the experience of the designer.

Viscous, 2-D, Laminar Hypersonic Flows Over Compression Ramps

Steady, laminar hypersonic viscous flows over semi-infinite flat plates and two- dimensional compression ramps are calculated. Surface pressure, skin friction and heat transfer distributions as well as flow structure plots (isoline contours) are presented for Mach numbers of 5, 10 and 14.1 and for unit Reynolds numbers of 3 to 6 million per meter.