Thesis: Sc. D., Massachusetts Institute of Technology. Department of Aeronautical Engineering, 1916. / MIT Institue Archives Thesis Coll.: copy is the Smithsoniam Institution publication. / Publication 2414. Hodgkins fund. Originaly prepared by Hunsaker as his Eng. D. Thesis, Massachusetts Institute of Technology, Dept. of Aeronautical Engineering, 1916. According to the MIT Registrar's Office, this degree was changed to an Sc.D., 1923 June 12. Original thesis did not contain the three plates. / by Jerome C. Hunsaker ... assisted by T. H. Huff, S. B., D. W. Douglas, S. B., H. K. Chow, S. M., and V. E. Clark. / Sc. D.

Driving aim of this study was to develop a solver which is accurate enough to be used in analysis and fast enough to be used in optimization purposes. As a first step, a three-dimensional potential flow solver is developed using Fast Multipole Boundary Element (FMBEM) for calculating the pressure distributions in non-lifting flows. It is a steady state solver which uses planar triangular unstructured mesh. After the geometry is introduced, the program creates a prescribed wake surface attached to the trailing edge(s), obtains a solution using panel elements on which the doublet and source strengths vary linearly. The reason for using FMBEM instead of classical BEM is the availability of solutions of systems having DOFs up to several millions within a few hours using a standard computer which is impossible to accomplish with classical BEM. Solutions obtained for different test cases are compared with the analytical solution (if applicable), the experimental data or the results obtained by JavaFoil.

This study presented the design and implementation of a spatial Hinf controller to suppress the free and forced vibrations of a cantilevered smart beam. The smart beam consists of a passive aluminum beam with surface bonded PZT (Lead-Zirconate-Titanate) patches. In this study, the PZT patches were used as the actuators and a laser displacement sensor was used as the sensor. In the first part of the study, the modeling of the smart beam by the assumed-modes method was conducted. The model correction technique was applied to include the effect of out-of-range modes on the dynamics of the system. Later, spatial system identification work was performed in order to clarify the spatial characteristics of the smart beam. In the second part of the study, a spatial Hinf controller was designed for suppressing the first two flexural vibrations of the smart beam. The efficiency of the controller was verified both by simulations and experimental implementation. As a final step, the comparison of the spatial and pointwise Hinf controllers was employed. A pointwise Hinf controller was designed and experimentally implemented. The efficiency of the both controllers was compared by simulations.

In this study, the non-equilibrium Johnson and King Turbulence Model (JK model) is implemented in a three-dimensional, Navier-Stokes flow solver. The main program is a structured Euler/Navier-Stokes flow solver in which spatial discretization is accomplished by a finite volume formulation and a multigrid technique is used as a convergence accelerator. The aim is the validation of this in-house developed CFD (Computational Fluid Dynamics) tool with this enhanced enlarged capability in order to obtain a reliable flow solver that can solve flows over swept wings accurately. Various test cases were evaluated against reference solutions in order to demonstrate the accuracy of the newly implemented JK turbulence model. The selected test cases are NACA 0012 airfoil, ONERA M6 wing, DLR-F4 wing and two wings taken from the 3rd Drag Prediction Workshop. The solutions were analyzed and discussed in detail. The results show appreciably good agreement with the experimental data including force coefficients and surface pressure distributions.

In this study, the structural optimization of a cruise missile wing is accomplished for the aerodynamic loads for four different flight conditions. The flight conditions correspond to the corner points of the V-n diagram. The structural analysis and optimization is performed using the ANSYS finite element program. In order to construct the flight envelope and to find the pressure distribution in each flight condition, FASTRAN Computational Fluid Dynamics program is used. The structural optimization is performed for two different wing configurations. In the first wing configuration all the structural members are made up of aluminum material. In the second wing configuration, the skin panels are all composite material and the other members are made up of aluminum material. The minimum weight design which satisfies the strength and buckling constraints are found for both wings after the optimization analyses.

In this thesis, gas-kinetic methods for inviscid and viscous flow simulations are developed. Initially, the finite volume gas-kinetic methods are investigated for 1-D flows as a preliminary study and are discussed in detail from theoretical and numerical points of view. The preliminary results show that the gas-kinetic methods do not produce any unphysical flow phenomena. Especially the Gas-Kinetic BGK method, which takes into account the particle collisions, predicts compressible flows accurately. The Gas-Kinetic BGK method is then extended for the solution of 2-D and 3-D inviscid and viscous flows on unstructured/hybrid grids. The computations are performed in parallel. Various inviscid and viscous test cases are considered and it is shown that the Gas-Kinetic BGK method predicts both inviscid and viscous flow fields accurately. The implementation of hybrid grids for viscous flows reduces the overall number of grid cells while enabling the resolution of boundary layers. The parallel computations significantly improve the computation time of the Gas-Kinetic BGK method which, in turn, enable the method for the computation of practical aerodynamic flow problems.

A dynamic flight model of a jet trainer aircraft is developed in MATLAB-SIMULINK. Using a six degree of freedom mathematical model, non-linear simulation is used to observe the longitudinal and lateral-directional motions of the aircraft following a pilot input. The mathematical model is in state-space form and uses aircraft stability and control derivatives calculated from the aircraft geometric and aerodynamic characteristics. The simulation takes the changes in speed and altitude into consideration due to pilot input and demonstrates the non-linearity of the aircraft motion. The results from the simulation are compared with the results from flight characteristics manual of the actual aircraft to validate the mathematical model used. The simulation is carried out for a number of airspeed and altitude combinations to examine the effect of changing speed and altitude on the aircraft dynamic response.

To decrease the computational cost of genetic algorithm optimizations, surrogate models are used during optimization. Online update of surrogate models and repeated exchange of surrogate models with exact model during genetic optimization converts static optimization problems to dynamic ones. However, genetic algorithms fail to converge to the global optimum in dynamic optimization problems. To address these problems, a multiploid genetic algorithm optimization method is proposed. Multi-fidelity surrogate models are assigned to corresponding levels of fitness values to sustain the static optimization problem. Low fidelity fitness values are used to decrease the computational cost. The exact/highest-fidelity model fitness value is used for converging to the global optimum. The algorithm is applied to single and multi-objective turbine blade aerodynamic optimization problems. The design objectives are selected as maximizing the adiabatic efficiency and torque so as to reduce the weight, size and the cost of the gas turbine engine. A 3-D steady Reynolds-Averaged Navier-Stokes solver is coupled with an automated unstructured grid generation tool. The solver is validated by using two well known test cases. Blade geometry is modelled by 37 design variables. Fine and coarse grid solutions are respected as high and low fidelity surrogate models, respectively. One of the test cases is selected as the baseline and is modified in the design process. The effects of input parameters on the performance of the multiploid genetic algorithm are studied. It is demonstrated that the proposed algorithm accelerates the optimization cycle while providing convergence to the global optimum for single and multi-objective problems.

Accuracy of the finite difference sensitivity calculations are improved by calculating the optimum finite difference interval sizes. In an aerodynamic inverse design algorithm, a compressor cascade geometry is perturbed by shape functions and finite differences sensitivity derivatives of the flow variables are calculated with respect to the base geometry flow variables. Sensitivity derivatives are used in an optimization code and a new airfoil is designed verifying given design characteristics. Accurate sensitivities are needed for optimization process. In order to find the optimum finite difference interval size, a method is investigated. Convergence error estimation techniques in iterative solutions and second derivative estimations are investigated to facilitate this method. For validation of the method, analytical sensitivity calculations of Euler equations are used and several applications are performed. Efficiency of the finite difference sensitivity calculations is improved by parallel computing. Finite difference sensitivity calculations are independent tasks in an inverse aerodynamic design algorithm and can be computed separately. Sensitivity calculations are performed on parallel processors and computing time is decreased.

In this thesis, structural optimization study is performed by using three different methods. In the first method, optimization is performed using MSC.NASTRAN Optimization Module, a commercial structural analysis program. In the second method, optimization is performed using the optimization code prepared in MATLAB and MSC.NASTRAN as the solver. As the third method, optimization is performed by using the optimization code prepared in MATLAB and analytical equations as the solver. All three methods provide certain advantages in the solution of optimization problems. Therefore, within the context of the thesis these methods are demonstrated and the interface codes specific to the programs used in this thesis are explained in detail. In order to compare the results obtained by the methods, the verification study has been performed on a cantilever beam with rectangular cross-section. In the verification study, the height and width of the cross-section of the beam are taken as the two design parameters. This way it has been possible to show the design space on the two dimensional graph, and it becomes easier to trace the progress of the optimization methods during each step. In the last section structural optimization of a multi-element wing torque box has been performed by the MSC.NASTRAN optimization module. In this section geometric property optimization has been performed for constant tip loading and variable loading along the wing span. In addition, within the context of shape optimization optimum rib placement problem has also been solved.