INNIO Learning Experiences vs AeroEngineS

INNIO’s Learning Experiences help you to understand the fundamental principles of how our gas engines power the world in a fun and engaging way. How does a Jenbacher* engine work? Our first interactive learning experience helps you to understand the basic principles of our gas engines. How to use it: 1) Download and start the app 2) Select "How does a Jenbacher work" 3) If you have an engine box: start the Augmented Reality (AR) version, alternatively start the 3D version 4) Find and watch all videos, collect all parts and start your engine Visit http://training.jenbacher.com/app for further information * Indicates a trademark

Aircraft Engine Performance at Design Point - Subsonic/Supersonic 1-Spool Turbojet - Subsonic 2-Spool Turbofan - Subsonic 2-Spool Boosted Turbofan - Subsonic 3-Spool Turbofan - Analysis of the Thermodynamic Cycle - Nozzle Area and Performance (Thrust, Power etc.) calculation - Mass Flows (Core, Bypass, Fuel) - Automatic calculation of ambient conditions based on the flight altitude using the International Standard Atmosphere model - Automatic calculation of Cp, gama, R for each component based on temperature and Fuel to Air Ratio - Automatic calculation of isentropic efficiency for each compressor and turbine based on polytropic efficiency and pressure ratio Hybrid Precooled Rocket Engine at Design Point - Analysis of the combined Thermodynamic Cycles with Air, Hydrogen & Helium as working fluids Ramjet Engine at Design Point - Simulation of the thermodynamic cycle of a hydrogen-fuelled Ramjet engine at optimized conditions. Ramjet Engine at Design Point - Simulation of the thermodynamic cycle of a hydrogen-fuelled Ramjet engine at optimized conditions. Supersonic 2-spool Turbojet Engine at Design Point - Simulation of the thermodynamic cycle of a Supersonic 2-spool turbojet engine with reheat. Aircraft Emissions - Emissions calculation for aircraft engines in LTO cycle and Cruise - Type of turbofan engines used: 1. Subsonic 2-Spool, 2. Subsonic 3-Spool Compressor Map Operating Point Prediction using - Scaling Techniques on an existing HPC map - Artificial Neural Networks to interpolate the existing map's data ______________________________________________________ Developer: Aggelos Gaitanis Original creator: Evangelia Pontika HyRE, Ramjet tab programmer: Spiros Tsentis Supersonic 2-spool Reheated tab programmer: Anastasios Saflekos Emissions tab developer/programmer: Maria Bakali Advisor: Ioanna Aslanidou, Konstantinos Kyprianidis Supervisor: Anestis Kalfas