Sharif Digital Repository

A morphing-body optimization method is introduced to accelerate adjoint-based shape optimization techniques. The optimization process solves the flow and adjoint equations around a continuously deforming body whose shape is controlled by the cost function. Effect of various parameters on the efficiency of the scheme is studied. It is found that, for the best performance of the algorithm, the morphing rate of the airfoil should be restricted, since larger rates foster oscillations and lower values are not computationally feasible. Moreover, the iterative procedure in the adjoint solver should be adapted to the iteration scheme in the flow solver and to the morphing rate  

Most researches on the application of the adjoint method in turbine blade design are concentrated on the aerodynamic shape optimization without considering the heat transfer to/from the blade material. In this study, the adjoint method is extended to the conjugate heat transfer problems in which the viscous flow field is coupled to heat transfer in the solid region. Introducing a new adjoint variable in the solid domain, a heat adjoint equation is derived which is coupled with the energy adjoint equation in the fluid zone at the fluid/solid interface. The detailed mathematical description associated with the derivation of the heat adjoint equation with corresponding boundary conditions are... 

The problem of aerodynamic shape optimization of unguided projectiles has been investigated. Two stochastic optimization methods have been applied to solve the problem. These include a Genetic Algorithm (GA) and the recently developed Continuous Ant Colony System (CACS), which is based on the well-known Ant Colony Optimization meta-heuristic. The objective function is defined as the summation of normal force coefficients over a set of given flight conditions. An engineering code (EC) is used to calculate the normal force coefficients over the flight conditions. The obtained results of CACS+EC are compared with those of GA+EC, as well as the results of a previous work (GA +AeroDesign). The... 

In this research, numerical optimization of the rear part of a gas turbine, consisting of a single stage axial turbine is carried out. Automated aerodynamic shape optimization is performed by coupling a CFD flow simulation code with the Genetic Algorithm. An effective multi-point optimization method to improve efficiency and/or pressure ratio of the axial turbine is performed. Some variations of optimization parameters such as lean and sweep angels of stator and rotor blades are accomplished. Furthermore, during the optimization process, three-dimensional and turbulent flow field is numerically investigated using a compressible Navier-Stokes solver. The gas turbine experimental... 

The axial turbine is one of the most challenging components of gas turbines for industrial and aerospace applications. With the ever-increasing requirement for high-aerodynamic performance blades, three-dimensional aerodynamic shape optimization is of great importance. In this research, the rear part of a gas turbine consisting of a one-stage axial turbine is optimized numerically. A useful optimization algorithm is presented to improve the efficiency and/or pressure ratio of the axial turbine with two different objective functions. The three-dimensional blade-shape optimization is employed to study the effects of the turbine stator and rotor lean and sweep angles on the turbine performance....