@article {Marconcini2019,
	title = {Large eddy simulation and RANS analysis of the end-wall flow in a linear low-pressure- turbine Cascade-Part II: Loss generation},
	journal = {Journal of Turbomachinery},
	volume = {141},
	number = {5},
	year = {2019},
	abstract = {{\textcopyright} 2019 by ASME. In low-pressure turbines (LPT) at design point, around 60-70\% of losses are generated in the blade boundary layers far from end walls, while the remaining 30-40\% is controlled by the interaction of the blade profile with the end-wall boundary layer. Increasing attention is devoted to these flow regions in industrial design processes. This paper discusses the end-wall flow characteristics of the T106 profile with parallel end walls at realistic LPT conditions, as described in the experimental setup of Duden, A., and Fottner, L., 1997, \&quot;Influence of Taper, Reynolds Number and Mach Number on the Secondary Flow Field of a Highly Loaded Turbine Cascade,\&quot; Proc. Inst. Mech. Eng., Part A, 211(4), pp.309-320. Calculations are carried out by both Reynolds-averaged Navier-Stokes (RANS), due to its continuing role as the design verification workhorse, and highly resolved large eddy simulation (LES). Part II of this paper focuses on the loss generation associated with the secondary end-wall vortices. Entropy generation and the consequent stagnation pressure losses are analyzed following the aerodynamic investigation carried out in the companion paper (GT2018-76233). The ability of classical turbulence models generally used in RANS to discern the loss contributions of the different vortical structures is discussed in detail and the attainable degree of accuracy is scrutinized with the help of LES and the available test data. The purpose is to identify the flow features that require further modeling efforts in order to improve RANS/unsteady RANS (URANS) approaches and make them able to support the design of the next generation of LPTs.},
	issn = {15288900},
	doi = {10.1115/1.4042208},
	author = {Marconcini, M. and Pacciani, R. and Arnone, A. and Michelassi, V. and Pichler, R. and Y. Zhao and Sandberg, R.}
}
