Gas turbine (GT) engines are the primary engines of modern aviation. They are also widely used as power propulsion engines for power stations. The specificity of these engines implies they frequently work at off-design/part load modes that occur with:
- Different modes of aircrafts:
- Ground idle mode
- Take off
- Maximum continuous mode
- Cruising mode
- Different ambient conditions
- Grid demands (for power generation engines and gas pumping (compressor) stations)
Due to the off-design/part load operating conditions, the parameters of the engines might change significantly, which influences not only the engine efficiency, but also the reliable work of the turbine (high temperature at turbine inlet) and compressor (surge zone) at joint operational points. This is why accurate predictions of the gas generator parameters are crucial at every off-design mode.
To define the joint operational point, the compressor and turbine maps which are created for specified ambient conditions can be used. For example, pressure equal 101.3kPa, temperature – 288.15K. Maps method is widely used, relatively simple and allows you to find the needed engine parameters in the shortest time. However, when cooling is present, engine operation at low power modes (ground idle) impede the accurate determination of joint operational conditions based on maps. The significant drawback to the maps based approach is that it does not give the full picture of the physical processes in turbomachine flow paths which is critical for off-design calculations.Utilization of the digital twin concept allows significant increase of the off-design performance calculation accuracy. Use of the digital equivalent of object was introduced in 2003 . Despite this, less 1% of machines that are in use today are modeled with digital twin technology . Utilization of digital twin leads to a significant decrease in time and cost for developing and optimization of an object.
Good joint operational conditions accuracy of turbomachines is achieved using 2D simulation in combination with well-proven loss models which are based on experimental data. The loss models of Craig&Cox , Kacker-Okapuu for turbine and Aungier  for compressor, are often default models in the industry. The designed compressor and turbine flow paths are presented below.At the ground idle mode a compressor is at risk of surging. To avoid this, the guide vanes of the first stages of compressor are performed turning. The flow paths, above, have enough freedom degree to allow their geometry changing and recalculation to find renewed performance.To close the cycle of the gas turbine unit digital twin a thermodynamics model of combustor, intake and exhaust duct can be used. Practice has shown with such simulation models utilization does not lead to significant error in performance determination.
To find the compressor and turbine joint operational point the digital twin calculation model should be based on an iterative process, which start with some initial educated guesses of unknown quantities, but are required for next step parameters.
The presence of a cooling system in a gas turbine unit does not lead to significant changes of the digital twin scheme. A cooling system can be simulated via detailed (1D)  and simplified (0D) methods depending from required task. For gas turbine units that do not have the strict constraint on weight (power propulsion) the optimization of cooling air mass flow rate at off-design modes also can be performed. Wherein the possibility of hot gases entering into cooled blade can be traced.
In this way, the utilization of digital twin technology leads to significant decreases in object development and improvement time. Utilizing the digital twin for off-design modes allows engineers to determine if the compressor is beyond the safe operation margin to surge and perform automatic correction of guide vanes stagger angles to satisfy the requirements for safe work.
The digital twin based method is flexible, fast and highly accurate with the ability to connection different tools/models with different complexity degree for object simulation. Utilization of the digital twin opens new capabilities in the aircraft and power propulsion industries.
To learn more, contact us at info@Softinway.com.
- Walker, M.J.: Hype Cycle for Emerging Technologies, Gartner, 2017. Report ID G00314560.
- R. M. Craig; H. J. A. Cox, 1970 “Performance Estimation of Axial Flow turbines,” Proc. Instn. Mech. Engrs. 1970-71, ol.185 32/71.
- Ronald H. Aungier, 2003. “Axial –Flow compressors: a strategy for aerodynamic design and analysis”, The American Society of Mechanical Engineers, New York, 2003, 363p.
- Moroz, Yu. Govoruschenko, P. Pagur, A uniform approach to conceptual design of axial Turbine / compressor flow path, The Future of Gas Turbine Technology. 3rd International Conference, October 2006, Brussels, Belgium.
- SoftInWay Inc, 2017, AxSTREAM ION™ user documentation.
- SoftInWay Inc, 2016, AxSTREAM NET™ user documentation.