The maintenance and reliability of aircraft engines is strongly influenced by the environmental and operating conditions they are subjected to in service. A probabilistic tool has been developed to predict shop visit arisings and respective maintenance workscope that depends on these factors. The tool contains a performance model of the engine and a number of physics-based damage mechanisms (at piece part level). The performance model includes variation of performance relevant parameters due to production scatter and delivers the conditions to determine the deterioration of the individual parts. Shop visit maintenance is modeled as a result of limitations to engine operation, e.g. reaching TGT limit, or mechanical deterioration. The influence of maintenance actions on engine performance is determined on component basis. The maintenance strategy can consist of proactive and reactive maintenance elements. The decision of repair or replacement of any single part is implemented through a sum of different logic rules in the model. The loading capacity scatter depends on the engine type and is operator independent. It is represented via data-driven distribution functions, in which the probabilities of failure, repair and replacement for each part are specified depending on the number of reference flight cycles. The loading variation is considered through a physics-based cycle weighting. The developed tool runs a Monte Carlo simulation in which a fleet of engines is modeled through their respective lifetime of maintenance and performance deterioration. Using an example it is shown that the model can describe the effects of varying environmental and operating conditions on part damage, and therefore engine maintenance cost and reliability.

During the design process of compressor blades predominantly deterministic models are used for High Cycle Fatigue (HCF) strength investigations. The scatter of HCF that results e.g. through abrasion of the production machines [1] or inhomogeneities of the blade material, is accounted by safety factors and conservative assumptions. A more realistic approach to consider these uncertainties is the application of probabilistic methods. Therefore, further information about HCF and eigenfrequency scatter of the really produced blades can be used for a robust design during the design process. Within a measurement campaign 400 blades of a Rolls-Royce High Pressure Compressor were randomly selected and scanned using an automated process that applies the optical measurement technique of strip projection. The measurement data of the airfoil were subdivided into constant spanwise profile slices. Geometric airfoil parameters were determined on each of the profile slices [2]. Due to the large number of scanned blades each geometric airfoil parameter can be described as a distribution function with corresponding parameters. These distribution functions are the input parameters for the probabilistic investigation — the Monte-Carlo-Simulation (MCS). Within the MCS an automatically transfer process varies at first the profile slices of a CAD-airfoil and in a second step morphs an existent 3D finite element mesh applying the meshmorphing tool of the FE preprocessor Hypermesh. The HCF and eigenfrequency scatter of all blades were calculated with the interpretation of the MCS results and parameters were detected with the largest influence on HCF-strength and eigenfrequencies. A detailed interpretation of the HCF-strength at one example shows the power of the probabilistic investigation. The interpretation helps the engineer to understand the entire system and to design a robust blade.

The rims of high pressure turbines in aeroengines are sealed with air via the internal air system. This sealing is required to avoid occurrence of hot gas ingestion into the rotor-stator cavities. Due to a rapid decrease of turbine disc life at higher temperatures, such ingestion would present a hazard to the integrity of the discs and subsequently to the safety of the aircraft. One of the driving factors for ingestion is the circumferential pressure variation downstream of vanes and blades due to the aerodynamic wakes. Small ingestion cavities close to the annulus are commonly used to damp down this pressure variation. Substantial ingestion into these cavities is permitted. The actual sealing of the rotor-stator cavity itself is accomplished with a secondary seal. A numerical simulation of the flow in an engine type rotor-stator cavity was carried out using a commercial CFD code. The cases studied comprise relevant features as rotor-stator and ingestion cavities, leakage across rotor blade shanks and circumferential pressure variation downstream of an NGV. The simulation was carried out at relevant engine temperatures and pressures. The paper will firstly present the effects of a variation of the rim sealing mass flow on the flow field, ingestion and temperature increase in the cavity. These results were solely gained by computational means. For validation of a new air system design, engine tests on the BR715 jet engine have been performed. The data measured in these tests not only serve for certification purposes, but also may be used as input for CFD calculations. Thus, the experimental data was the baseline for comparison with the results from the present study.

The geometric parameters of manufactured compressor blades do not exactly comply with the design intention. These deviations result from the abrasion of the forging and milling machines as well as variations of the material properties or the blank part geometries. Using probabilistic methods, the geometric deviations can be considered within the design process. This paper presents the results of a probabilistic High-Cycle-Fatigue investigation under consideration of the geometric parameter scatter of the entire compressor blade. Based on a previous paper of the authors, the geometric parametrization as well as the process chain to apply the geometric scatter to an existing FE-mesh was supplemented by the radii and the geometric dimensions of the compressor blade root. Thus, the impact of all geometric parameter scatter on the High-Cycle-Fatigue strength, the eigenfrequencies and the mode shapes can be evaluated.

Recent developments in computer capabilities and software enabled the application of deterministic optimization and Robust Design methods in real world aero engine development programs. This paper describes the methods used and shows several applications of this technology. The first example is the application of a Monte-Carlo simulation to support design decisions in the HP turbine casing air system. Here the main goal was to achieve a robust design addressing the variation of build tolerances on flow areas. The variation of parameters as mass flows, pressures and temperatures based on 5000 permutations of the base model give a high confidence level for achieving reliable system behavior for a large population of engines. In addition, dependencies of result parameters on input variations indicate the main levers for system improvement. A second example is the optimization of compressor discs. Here the main emphasis was on the influence of manufacturing tolerances and on the best method to evaluate these tolerances for longer running analysis tasks. Therefore, results of a full Monte-Carlo simulation are compared with results based on two surrogate models, a response surface and a Taylor series expansion. As a final example the optimization of a HP turbine disc for which a Design of Experiment has been performed to generate a response surface model is discussed. Using the response surface data the life variability due to assumptions in the thermal modeling have been quantified and used to adjust the constraints for the subsequent deterministic optimization for weight of the HP turbine. Using deterministic optimization and especially Robust Design methods a considerable decrease in development time and cost as well as an increased product quality and reliability have been achieved. However, deterministic optimization methods alone normally drive designs on to the constraint boundaries, leading to “cliff-edge” designs. Therefore, the application of Robust Design methods is required to increase the product reliability. These methods still require a considerable computing effort, so the widespread application is just starting.