Digitised and Traceable Testing for Gas Turbine Components and Materials

Abstract

The Institute of Test and Simulation for Gas Turbines develops digital twins and simulation models to calculate the aerodynamic loads and to assess the damage mechanisms in engine parts and materials resulting from simultaneous mechanical, thermal and chemical-corrosive loads. Multiscale methods are used to quantify the long-term behaviour of objects, from the microstructure of materials to engine parts and components, and the characteristics of engine subsystems. Additionally, scale-resolving simulations are developed and applied to obtain high-fidelity CFD solutions. In order to validate the digital models experimentally, unique test stands and rigs are developed which provide engine-relevant operating conditions, dimensions, and loads. There are multiple test rigs in development for experimental testing of materials under engine-relevant conditions. The test rigs may be grouped in two major categories: materials testing and rotative engine subsystem testing. Materials testing is performed at mechanical, thermal, and chemical loads representative of real engine conditions. Rotative subsystem testing includes innovative seals, gears and secondary air systems. The subsystem tests are also performed under engine relevant conditions and used to validate pertinent design models. These test rigs are presented and their research objectives are specified. The presentation outlines how operating conditions for tests are combined in a number of ways to allow research under real engine conditions. Additionally, this setup allows testing under a combination of mechanical, thermal and chemical loads simultaneously, thereby going beyond the current state of the art. To achieve the best possible integration of simulation and experiments, both areas will be fully digitised. A tool is developed to establish comprehensive data provenance for all steps of research projects. The presentation details how process steps report data to be included in a graph database where connections are created based on ontologies specifically designed for this purpose. Ontology allow exchanging data between software and processes without loss of semantics. The graph database will represent processes performed and ensure that quality managed processes are adhered to. Furthermore, such a digitised system does not just allow insight into single research steps but allows a unique overview over all performed tasks.