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Probability methods for engine design
Baseline configuration

The baseline aircraft for this study is a four-engine large commercial transport capable of carrying 420 passengers (at 210 lb/passenger) in a three-class configuration. The aircraft is in the 800,000-900,000 lb gross takeoff weight class. The baseline configuration is set up for a fixed operating empty weight, minus propulsion system weight, with a variable design range (fuel-volume-limited aircraft). Baseline power extraction and customer compressor bleed are based on typical customer requirements.

The baseline engine cycle is based on a current-technology core, which has a fixed, but scaleable configuration. The low-pressure spool configuration is completely variable, but it has an assumed fixed technology level and a two-stage booster. The model for the baseline engine is calibrated to match the performance capability using current technology. Compressor pressure ratio is fixed and the overall pressure ratio neglected for the analysis. The impact of changes in the overall pressure ratio due to changes in fan pressure ratio are small with the narrowly selected fan pressure ratio range. In addition, maximum turbine inlet temperature is specified, allowing core size also to be neglected.

The baseline engine cycle key control parameters (KCPs) and key noise parameters (KNPs) used in the study are presented in Table 2. The primary KCPs Ñ fan pressure ratio and extraction ratio Ñ are strong drivers on specific thrust, specific fuel consumption, and engine weight. The seven key noise parameters (KNPs) examined are chosen for the greatest impact on range and fuel burn.

Table 2
Engine Cycle Parameter Range
Control parameter Upper Nominal Lower
Fan pressure ratio 0.065 Base -0.065
Extraction ratio 0.15 Base -0.15
Max. turbine inlet temperature 200° Base -200°

All noise parameter distributions are specified as normal distributions, although, in reality, the shape of these distributions may be different. This is a first-pass approximation based on the best available knowledge of the distribution mean and standard deviation.

With upper and lower limits for the KNPs based on ± 2s variation around the mean value for each parameter, 95.4% of the expected uncertainty is captured. That is, there is a 95.4% chance that the hardware that goes to test will perform inside the defined upper and lower boundaries. Baseline KCP and KNP values are proprietary.

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