Testing and simulation allow quantitative evaluation of alternative designs but also present opportunities to gain physical insight into how specific design features affect performance. Physical insight into thermodynamics loss mechanisms plays an essential role in guiding the turbomachinery design cycle. Continued development of more advanced and detailed experimental and simulation methods provides increasingly rich and voluminous data. However, analysis techniques must also be developed further so that the richness of the data enhances designers’ insight, rather than obscuring important phenomena.Benefitting from rapid advances in computational capabilities, computational fluid dynamics (CFD) offers increasingly valuable data for design of turbomachinery flows. This includes the ability to perform large numbers of basic simulations rapidly, for example using Reynolds-Averaged Navier-Stokes (RANS) techniques, and the ability to achieve high predictive accuracy for unsteady and turbulent flows using Large Eddy Simulation (LES) or, currently in a limited set of flow conditions, using Direct Numerical Simulation (DNS). In each case CFD provides a full three-dimensional detailed description of the thermodynamic state of the flow, enabling rigorous physics-based interrogation of loss mechanisms that is not currently possible using experimental measurements.The present work contrasts two approaches for using high-fidelity CFD data in loss analysis. The first approach is Mechanical Work Potential analysis originally developed by Miller (2013) and extended by Leggett et al. (2019) for application to LES and RANS data. The second approach is an entropy-based analysis developed by Zhao and Sandberg (2019), also derived in a form applicable to LES and RANS data. Both approaches are derived from exact balance equations for thermodynamics variables, but the two approaches provide different definitions of thermodynamic loss: the first considers loss of mechanical work potential, and the second considers entropy generation. These alternative definitions result in a different breakdown and classification of loss mechanisms.Given that both approaches have rigorous bases. The objective of this study is to provide a direct comparison between the two approaches and to assess the practical utility of the alternative approaches for a turbomachinery designer. The approaches are assessed through application to data from LES of a NACA 65 compressor with and without incident wakes and the different loss breakdown predictions are studied and compared.A key attribute of these two analyses is the ability to perform spatio-temporal decomposition of the flow domain. To highlight this the comparison will also be performed looking at various user defined ‘zones’ such as suction surface and pressure surface boundary layers. As well as the evolution of loss using phase locked averages of the wake passing.

Turbomachinery Loss Analysis: The Relationship Between Mechanical Work Potential and Entropy Analyses

Paper Proceedings: https://asmedigitalcollection.asme.org/GT/GT2021/volume/84898

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