The prediction of aerodynamic damping is a key step towards high fidelity forced response calculations. Without the knowledge of absolute damping values, the resulting stresses from forced response calculations are often afflicted with large uncertainties. In addition, with the knowledge of the aerodynamic damping the aeroelastic contribution to mistuning can be considered. The first section of this paper compares two methods of one-way-coupled aerodynamic damping computations on an axial turbine. Those methods are: the aerodynamic influence coefficient, and the travelling wave mode method. Excellent agreement between the two methods is found with significant differences in required computational time. The average deviation between all methods for the transonic turbine is 4%. Additionally, the use of transient blade row methods with phase lagged periodic boundaries are investigated and the influence of periodic boundaries on the aerodynamic influence coefficients are assessed. A total of 23 out of 33 passages are needed to remove all influence from the periodic boundaries for the present configuration. The second part of the paper presents the aerodynamic damping calculations for a centrifugal compressor. Simulations are predominantly performed using the aerodynamic influence coefficient approach. The influence of the periodic boundaries and the recirculation channel is investigated. All simulations are performed on a modern turbocharger turbine and centrifugal compressor using ANSYS CFX V17.0 with an inhouse pre- and post-processing procedure at ABB Turbocharging. The comparison to experimental results concludes the paper.

Traditional forced response calculations for adjacent blade rows without a common divisor demand full annular transient simulations. This typically results in large and often impractical computational costs during development. The present article discusses an approach to reduce this cost using a signal-patching routine on a transonic axial turbine. Additionally, the potential for further reduction of computational cost by means of time domain flow transformation methods is investigated. The methods assessed are profile transformation, time inclination and Fourier methods, all within ANSYS CFX. Comparisons are made for the vector components of blade force harmonics, generalised force and computational costs. The computational cost can be reduced to 40% and 5% of the full annular simulation with signal patching or time domain flow transformation methods respectively. The signal-patching and transformation methods applied result in an error of 10% and 15% of generalised force respectively. KEYWORDS PROFILE TRANSFORMATION, TIME INCLINATION, FOURIER METHOD, BLADE COUNT SCALING NOMENCLATURE U arbitrary flowfield variable P pitch P S stator pitch P R rotor pitch Ω rotational speed a axial coordinate r radial coordinate θ circumferential coordinate t time coordinate ∆t time coordinate variation

This paper describes low-order-model-based analysis of the design of an experiment to be used for parametric studies of adiabatic film and overall cooling effectiveness for fully cooled systems (internal and film) under wide ranges of mainstream-to-coolant temperature ratio variation, in the range 0.50 < T0m/T0c < 2.30. The purpose is to improve understanding of—and validation of—the scaling process from typical rig conditions to engine conditions. We are primarily interested in the variation in overall effectiveness when the controlling non-dimensional groups change in a natural co-dependent way with changes in temperature ratio: that is, the practical situation of interest to engine designers. We distinguish this from the situation in which individual non-dimensional groups are varied in isolation: a situation that we believe is essentially impossible to meaningfully approximate in practice, despite a body of literature purporting to do the same. Design and commissioning data from a new high temperature (600 K) test facility is presented, with detailed uncertainty analysis. We show that a typical nozzle guide vane which at engine conditions (TR = 2.00) would have overall cooling effectiveness of 0.450, would be expected to have overall effectiveness of 0.418 at typical rig conditions (TR = 1.20). That is, typical scaling from engine-to-rig result is −7.1%, and typical scaling from rig-to-engine is +7.7%, This result is important for first order estimation of overall cooling performance at engine conditions.