By means of this corrigendum, the authors would like to include relevant information regarding the validation of the meanline turbine model employed in the original article. The improvement regarding the validation of the model was made possible thanks to the contribution of Prof. Jürg Schiffmann. The additional results documented here provide more confidence on the reliability of the model when it applied to mini-ORC turbines. Therefore, we kindly ask the Editor to add his name to the authors list. The following paragraph extends the one that discusses the meanline validation located in Section 2. The turbine preliminary design is performed by means of a meanline code, which is based on the loss models listed in Ref. [1]. These models have been developed for conventional turbomachinery operating with fluids in the ideal gas state, featuring subsonic flows and large Reynolds numbers. The meanline code has been validated with the results of literature test cases presenting these characteristics [2]. It has been also compared against an experimentally validated turbine model for mORC machines operating in the subsonic regime [3]. Table 1 shows the information of the machine geometry for which results of the two codes were compared, while Fig. 1 presents the meridional channel of the turbine. Table 2 shows the corresponding operating conditions. The results of the total-to-static efficiency computation are presented in Fig. 2. It can be observed that the efficiency trend obtained with zTurbo is similar to that computed with the validated EPFL code. The comparison between the two models suggests a deviation lower than 2.5% for all the tested operating conditions. This deviation occurs because each model uses a different set of loss correlations. These correlations are described in Refs. [1,3].

High temperature Organic Rankine Cycles power systems of low power capacity, i.e. 3-50 kW_e, are receiving recognition for distributed and mobile energy generation applications. For this type of power plants, it is customary to adopt a radial-turbine as prime mover, essentially for their ability to cope with very large volumetric flow ratio with limited fluid-dynamic penalty. To date, the design of such turbines is based on design guidelines and loss models developed mainly for turbo-chargers, subsequently adapted by means of non-validated computational fluid-dynamic calculations. In the attempt to provide data sets for CFD validation and calibration of loss models, a mini-ORC radial inflow turbine delivering 10kW of mechanical power will be realized and tested in the Propulsion and Power Laboratory of TU-Delft. The fluid dynamic design and characterization of the machine is detailed in this paper. According to available models, the results indicate that the optimal layout of mini-ORC turbines can substantially differ from that of radial-inflow turbines utilized in more traditional applications, strengthening the need of experimental campaigns to support the conception of new design practices.

The preliminary fluid dynamic design of turbomachinery operating with non-standard working fluids and unusual operating conditions and specifications can be very challenging because of the lack of know-how and guidelines. Examples are the design of turbomachinery for small-capacity organic Rankine cycle and supercritical CO₂ cycle power plants, whereby the efficiency of turbomachinery components has also a strong influence on the net conversion efficiency of the system. These machines operate with the fluid in thermodynamic states which, for part of the process, largely deviate from those obeying to the ideal gas law. This in turn implies the presence of so-called non-ideal compressible fluid dynamics effects. Active subspaces, a model reduction technique, is at the basis of the methodology presented here, which is aimed at the optimal meanline design of unconventional turbomachinery. The resulting surrogate model depends on a very small set of non-physical variables, called active variables. The procedure integrates into a single constrained optimization framework the selection of the working fluid, the thermodynamic cycle calculation and the preliminary sizing of the turbomachinery component. As a demonstration of the advantages of the proposed approach, the design of a 10kW mini organic Rankine cycle turbine with a turbine inlet temperature of 240°C is illustrated. In this case, approximately the same maximum efficiency is estimated for three dissimilar turbines operating with different working fluids and rather different thermodynamic cycles. The use of active subspaces allows the seamless evaluation of the sensitivity of results to input parameters, both those related to the machine and the working fluid. The novel design procedure is compared in terms of computational efficiency to a conventional approach based on the coupling of a genetic algorithm directly with a meanline code. Results show that the calculation based on the use of surrogate models is more than two orders of magnitude faster. The surrogate can be used to solve any design problem within the specified boundaries of the design envelope. Results are affected by uncertainty on the estimation of losses and of non-ideal compressible fluid dynamics effects, which, in turn, do not affect the applicability of the method, which will become quantitatively accurate once this information will be available. Work to this end is underway in various laboratories.

The fluid dynamic preliminary design of unconventional turbomachinery is customary done with meanline design procedures coupled with gradient-free optimizers. This method features various drawbacks, since it might become computationally expensive, and it does not provide design insights or guidelines to the designer. This work proposes a strategy to abate this disadvantages, namely, the construction of a reduced-order model by means of active sub-spaces, and the use of the surrogate combined with a gradient-based optimizer. The case study is the design optimization of a Organic Rankine Cycle radial inflow turbine. The results show that active subspaces exist for this application, and that it is possible to construct a surrogate with an approximate error of ±1% for the total-to-static efficiency. Additionally, the optimization using the surrogate leads to accurate results and a computational cost at least four times faster. Furthermore, the results reveal that the models for unconventional turbomachinery feature multiple regions containing constrained optima. Active subspace methods thus prove to be a promising alternative for optimization of unconventional turbomachinery.