Design and optimization of a radial turbine for a Rankine cycle were accomplished ensuring higher thermal efficiency of the system despite the low turbine inlet temperature. A turbine design code (TDC) based on the meanline design methodology was developed to construct the base design of the turbine rotor. Best design practices for the base design were discussed and adopted to initiate a robust optimization procedure. The baseline design was optimized using the response surface methodology and by coupling it with the genetic algorithm. The design variables considered for the study are rotational speed, total to static speed ratio, hub radius ratio, shroud radius ration, and number of blades. Various designs of the turbine were constructed based on the Central Composite Design (CCD) while performance variables were computed using the in-house turbine design code (TDC) in the MATLAB environment. The TDC can access the properties of the working fluid through a subroutine that links NIST’s REFPROP to the design code through a subroutine. The finalization of the geometry was made through an iterative process between 3D-Reynolds-Averaged Navier-Stokes (RANS) simulations and the one-dimensional optimization procedure. 3D RANS simulations were also conducted to analyze the optimized geometry of the turbine rotor for off-design conditions. For computational fluid dynamics (CFD) simulation, a commercial code ANSYS-CFX was employed. 3D geometry was constructed using ASYS Bladegen while structured mesh was generated using ANSYS Turbogrid. Fluid properties were supplied to the CFD solver through a real gas property (RGP) file that was constructed in MATLAB by linking it to REFPROP. Computed results show that an initial good design can reduce the time and computational efforts necessary to reach an optimal design successfully. Furthermore, it can be inferred from the CFD calculation that Response Surface Methodology (RSM) employing CFD as a model evaluation tool can be highly effective for the design and optimization of turbomachinery.

The rising environmental problems due to fossil fuels’ consumption have pushed researchers and technologists to develop sustainable power systems. Due to properties such as abundance and nontoxicity of the working fluid, the supercritical carbon (${\mathrm{sCO}}_2$) dioxide Brayton cycle is considered one of the most promising technologies among the various sustainable power systems. In the current study, a mathematical model has been developed and coded in Matlab for the recompression of the supercritical carbon dioxide Brayton cycle sCO₂-BC. The real gas properties of supercritical carbon dioxide (${\mathrm{sCO}}_2$) were incorporated into the program by pairing the NIST’s Refporp with Matlab© through a subroutine. The impacts of the various designs of the cycle’s individual components have been investigated on the performance of ${\mathrm{sCO}}_2-\mathrm{BC}$. The impact of various sedative cycle parameters, i.e., compressor’s inlet temperature $\left(T_1\right),$ and pressure ($P_1$), cycle pressure ratio ($Pr$), and split mass fraction ($x$), on the cycle’s performance $({\eta }_{cyc}$) were studied and highlighted. Moreover, an optimization study using the genetic algorithm was carried out to find the abovementioned cycle’s optimized values that maximize the cycle’s per-formance under provided design constraints and boundaries.