Small-scale radial turbine pre-design model for ORCs

Here are gathered the different polynomial functions that estimate the performance of a small scale radial inflow turbine function of specific speeds (ns), specific diameters (ds) and pressure ratio (PR). Four sets of functions performed with varying shroud to tip radius ratio (epsilon=r6s/r4=[0.5 0.6 0.7 0.8]) are presented.
These polynoms were built with R134a, but as minor differences were found with the use of another organic fluid (R245fa, R600a, R152a), these maps are valid for different working fluids. An additional model built with a shroud to tip radius ratio epsilon equal to 0.5 and a blade height ratio b4/r4 equal to 0.05, instead of 0.11 for the other models. It can be useful first to check if the Ns and Ds solutions lie into the convexhull domain of the original dataset, which is given for each epsilon ratio (ConvexHullNsDsEps**.mat), in order to avoid any extrapolation errors. These extrapolation errors are usually mitigated but could arise if unusual turbine design locations are targeted.

For more information about the methodology of the model generation, its boundaries, and other features, please refer to the following paper : "SMALL SCALE RADIAL INFLOW TURBINE PERFORMANCE AND PRE-DESIGN MAPS FOR ORGANIC RANKINE CYCLES, V.Mounier, L.E. Olmedo, J. Schiffmann, Energy, 2017" and the thesis "POTENTIAL AND CHALLENGES OF ORC DRIVEN HEAT PUMPS BASED ON GAS BEARING SUPPORTED TURBOMACHINERY, V.Mounier, Ecole Polytechnique Fédérale de Lausanne, 2018"

本数据集汇集了不同多项式函数，用以评估小规模径向进气涡轮在特定转速（ns）、特定直径（ds）和压力比（PR）下的性能。展示了四组函数，这些函数在变化的壳体与尖端半径比（ε=r6s/r4=[0.5 0.6 0.7 0.8]）下进行。这些多项式函数以R134a为介质构建，但由于在使用其他有机流体（R245fa、R600a、R152a）时发现了一些细微的差异，因此这些映射适用于不同的工作流体。此外，还构建了一个附加模型，其壳体与尖端半径比ε等于0.5，叶片高度比b4/r4等于0.05，而其他模型为0.11。首先检查Ns和Ds解是否位于原始数据集的凸包域内，对于每个ε比率均给出（ConvexHullNsDsEps**.mat），这对于避免任何外推误差是有益的。这些外推误差通常可以得到缓解，但如果针对不寻常的涡轮设计位置，则可能会出现。有关模型生成方法、边界条件及其他特性的更多信息，请参阅以下论文：《有机朗肯循环中小规模径向进气涡轮性能与预设计映射，V.Mounier, L.E. Olmedo, J. Schiffmann，能源，2017》以及论文《基于气垫支持的涡轮机械的有机朗肯循环热泵的潜力和挑战，V.Mounier，洛桑联邦理工学院，2018》