This thesis presents an accurate study about the fluid-dynamics of dense gases and their potential application as working fluids in Organic Rankine Cycles (ORCs). The ORCs are similar to a steam Rankine Cycle where an organic fluid is used instead of steam, which ensures better efficiency for low-temperature sources. Specific interest is developed into a particular class of dense gases, the Bethe-Zel'dovich-Thompson (BZT) fluids, which exhibit negative values of the Fundamental Derivative of Gasdynamics G in the vapor phase , for a range of temperatures and pressures of the order of magnitude of those of the liquid/vapor critical point, just above the upper coexistence curve. Transonic and supersonic flows in a region of negative G are characterized by nonclassical gasdynamic behaviors, such as the disintegration of compression shocks. Owing to this effect, the use of BZT gases as working fluids in ORCs is particularly attractive, since it may reduce losses due to wave drag and shock/boundary layer interactions. This advantage can be further improved by a proper design of the turbine blade. The present work is devoted to improve the understanding of the peculiar fluid-dynamic behavior of dense gases with respect perfect ones and to the research of suitable aerodynamic shapes. To this purpose, a dense-gas Navier-Stokes (NS) numerical solver is coupled with a multi-objective genetic algorithm. The Navier-Stokes solver employs equations of state of high accuracy within the thermodynamic region of interest and suitable thermophysical models for the fluid viscosity and thermal conductivity. Different computations are performed for transonic flows over isolated airfoils and through turbine cascades to evaluate the influence of the upstream kinematic and thermodynamic conditions on the flow patterns and the system efficiency, and possible advantages deriving from the use of a non-conventional working fluid are pointed out. Then, high performance airfoils and turbine blade shapes for transonic flows of BZT fluids are constructed using the CFD solver coupled with a multi-objective genetic algorithm. Shape optimization allows to strongly increase flow critical Mach Number, delaying the appearance of shock waves, while ensuring high lift (for an airfoil) and efficiency. A careful analysis of the convergence behavior of Genetic Algorithms has also been undertaken by means of statistical tools. Genetic Algorithm exhibit a marked sensitivity to the shape of the response surface and to its numerical representation. Some strategies are proposed to systematically evaluate GAs convergence capabilities for a given problem and to enhance their convergence properties for dense gas optimization problems.