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The T-100re optimization is obtained using the present GA assisted preliminary design procedure. The GA configuration has a population size of 15, an elite number of 1, a mutation rate of 0.15 and a maximum generation number of 200. The convergence curve of the total-to-static efficiency is shown in Figure 6 and the T-100re turbine has a total-to-static efficiency of 87.4%. It can be found that the convergent speed is quite fast and the design process costs only a few minutes. Some key Appl. Sci. 2018, 8, 2038 9 of 16 parameters like rotor inlet radius and blade number, etc. can be easily optimized through the empirical correlations in the preliminary design optimization, but hard to be optimized in the later tnhurmeee-rdicimaleonpstiiomniazlat(i3oDn), wnhuimcheriincdailcaotpetsimthiaztaitioisns,trwonhgiclhy ninecdeiscsaaterys ttohapteriftorismsatnroonpgtliyminzeacteiosnsaartythtoe preerlfiomrminarnyodpetsiimgnizsataiogne.at the preliminary design stage. 88 87 86 85 84 83 82 81 20 40 60 80 100 120 140 160 180 200 Generation [-] Figure 6. Convergence curve of the optimal design. Figure 6. Convergence curve of the optimal design. For the T-100re turbine, the axial, radial and back face clearance is set to be 0.3, respectively, which For the T-100re turbine, the axial, radial and back face clearance is set to be 0.3, respectively, is a minimum reasonable clearance. The six loss terms of the T-100re design are all lower than those which is a minimum reasonable clearance. The six loss terms of the T-100re design are all lower than of the verification design, which results in a higher total-to-static efficiency of 87.4%. The T-100re those of the verification design, which results in a higher total-to-static efficiency of 87.4%. The T- design has a smaller rotor inlet radius than that of the verification design, thus having a lower passage 100re design has a smaller rotor inlet radius than that of the verification design, thus having a lower loss and nozzle loss. Though the rotor tip clearance of the T-100re design is a little bit larger than passage loss and nozzle loss. Though the rotor tip clearance of the T-100re design is a little bit larger that of the verification design, the tip clearance loss is lower due to the smaller size too. Figure 7 than that of the verification design, the tip clearance loss is lower due to the smaller size too. Figure shows a comparison of the meridional contours of these two turbines. It can be seen that the T-100re 7 shows a comparison of the meridional contours of these two turbines. It can be seen that the T-100re turbine has a lower inlet radius and shorter axial length of the rotor than the T-100 turbine. Therefore, turbine has a lower inlet radius and shorter axial length of the rotor than the T-100 turbine. Therefore, the T-100re rotor weighs much lighter than the T-100, and the turbine‘s total weight will also reduce the T-100re rotor weighs much lighter than the T-100, and the turbine‘s total weight will also reduce due to the lower radial geometry size of rotor, nozzle and the corresponding volute. It is of significance due to the lower radial geometry size of rotor, nozzle and the corresponding volute. It is of fAoprplA. SPciU. 20o1f8a, 8e,rxoFspOaRcPeEaEnRdREtuVrIEbWine rotor of turbochargers. 10 of 17 significance for APU of aerospace and turbine rotor of turbochargers. Figure 7. Comparison of meridional contour. Figure 7. Comparison of meridional contour. Therefore, the present automated preliminary design approach is quite effective to determine Therefore, the present automated preliminary design approach is quite effective to determine the main parameters for the preliminary design. In this approach, the GA helps the designer find the main parameters for the preliminary design. In this approach, the GA helps the designer find the the best combination of (ψ, φ, n) corresponding to the highest total-to-static efficiency under specified best combination of (ψ , φ , n ) corresponding to the highest total-to-static efficiency under specified constraints and well-established loss models in a short time, thus making a good start for the later 3D constraints and well-established loss models in a short time, thus making a good start for the later 3D numerical optimization work, which will be presented in Part II of this paper [34]. numerical optimization work, which will be presented in Part II of this paper [34]. 3.2. Numerical Computation In 2012, Sauret [35] published a paper that intended to make the T-100 turbine an open benchmark for validation work and provided all the geometric data. In this study, an in-house blade design code for radial inflow turbines is developed in order to reconstruct the T-100 turbine based on the original data [27,35] and initialize the T-100re turbine design. Figures 8 and 9 show the T-100 Total-to-static efficiency [%]PDF Image | Design and Optimization Approach for Radial Inflow Turbines
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