Modeling of Highly Instrumented Honeywell Turbofan Engine Tested with Ice Crystal Ingestion in the NASA Propulsion System Laboratory

The Propulsion Systems Laboratory (PSL), an altitude test facility at NASA Glenn Research Center, has been used to test a highly instrumented turbine engine at simulated altitude operating conditions. This is a continuation of the PSL testing that successfully duplicated the icing events that were experienced in a previous engine (serial LF01) during flight through ice crystal clouds, which was the first turbofan engine tested in PSL. This second model of the ALF502R-5A serial number LF11 is a highly instrumented version of the previous engine. The PSL facility provides a continuous cloud of ice crystals with controlled characteristics of size and concentration, which are ingested by the engine during operation at simulated altitudes. Several of the previous operating points tested in the LF01 engine were duplicated to confirm repeatability in LF11. The instrumentation included video cameras to visually illustrate the accretion of ice in the low pressure compressor (LPC) exit guide vane region in order to confirm the ice accretion, which was suspected during the testing of the LF01. Traditional instrumentation included static pressure taps in the low pressure compressor inner and outer flow path walls, as well as total pressure and temperature rakes in the low pressure compressor region. The test data was utilized to determine the losses and blockages due to accretion in the exit guide vane region of the LPC. Multiple data points were analyzed with the Honeywell Customer Deck. A full engine roll back point was modeled with the Numerical Propulsion System Simulation (NPSS) code. The mean line compressor flow analysis code with ice crystal modeling was utilized to estimate the parameters that indicate the risk of accretion, as well as to estimate the degree of blockage and losses caused by accretion during a full engine roll back point. The analysis provided additional validation of the icing risk parameters within the LPC, as well as the creation of models for estimating the rates of blockage growth and losses.