Leichte Turbolader-Verdichterräder aus Aluminium- und Magnesium-Feinguß

Light turbocharger compressor wheels from aluminium and magnesium investment casting Within the scope of a team work between Kühnle, Kopp & Kausch AG, Volkswagen AG, Sterling International Technologies Ltd. and the Fraunhofer Institute for Strength of Structures under Operational Conditions LBF compressor wheels of aluminium and magnesium investment casting were developed and tested. Strength and fatigue tests, overspeed and field tests as well as metallographic checks were made in addition to the finite element calculations to optimize the stress under centrifugal force in an appropriate way for the materials involved. The results and the knowledge gathered are to clarify whether magnesium alloys are an appropriate replacement for the proven standard aluminium alloy for turbochargers.     

The method of fractional steps applied to laminar flat flame calculations

The premixed, freely propagating, steady, laminar, flat flames are solved by a relaxation method. For solution of the unsteady species conservation equations, the method of fractional steps is used. In this method the differential equations for the conservation of the species are split up into two parts, a reaction part and a diffusive convective part which are solved separately and then superposed. The method is used to solve a methane-oxygen flame and compared to the solution of a standard method. In addition the time step behaviour of both the methods are examined and compared to each other. Paper presented at the Workshop “Modelling of Chemical Reaction Systems”, Heidelberg 1986.     

KTN optical waveguides grown by liquid-phase epitaxy

Single-crystal optical waveguiding KTa1-xNbxO3layers have been successfully grown on to a (100)-KTaO3 substrate from a K2O-V2O5 flux by liquid-phase epitaxy.     

Einfluss der Versuchsunterstützung auf die Abschätzungsgenauigkeit mittels künstlich neuronaler Netze

Suitable methods and transferability criteria and knowledge of the cyclic material behaviour is essential for a durable design of a component. For this reason, the cyclic material parameters are determined as a function of the product's properties (level of deformation, microstructure, surface finish, residual stresses) and different loading parameters. However, since the determination of the cyclic parameters is associated with considerable experimental effort and costs, a cost‐effective and easy method is sought to determine these parameters. A very promising approach for this is the application of artificial neural networks (ANN) since they have the ability to generate the influences on the fatigue strength from the manufacturing and environmental parameters using sensibly selected input parameters. They offer the possibility to access acquired knowledge and to thus construct a multidimensional map based on a few tests. By combining a few experimental tests with the ANN, the result of the estimation can be improved and the experimental effort can be reduced.