In order to ensure that dangers like these are avoided a team around Kadau developed a simulation program that allowed it to design large generators and turbines. Its probabilistic data analytics tools tap into a wide array of data sources, including operational data or vendor data. Kadau and his team applied it to rotor disks for the new flagship gas turbine at Duke Energy, calculating the strength of its forged-steel components, and thereby the risk of their fracturing.
This tool has already played a critical part in ruling out the risk of disk fractures for a number of years in various turbines. It is used daily in turbine development to ensure that the disks can cope with new demands, assessing the rotor’s expected wear and tear and how this should affect its maintenance schedule. And even more, when inspected, the tool allows a user to determine whether, based on is condition, the rotor should be replaced.
This success wouldn’t have been possible without the help of an expert Siemens Technology team in graphics processor-based computing and software performance optimization for simulation and digital twins in Bangalore. They reorganized and reprogrammed key parts of the tool to enable its maximum performance when running on graphics processor-based high-performance computers. This way, Kadau’s team was able to calculate the fracture strength within minutes and even seconds rather than hours. An impressive feat, as the probabilistic tool runs through several million calculation sequences to cover all the material and load combinations that determine fracture strength.