A multidisciplinary design optimization framework is developed that integrates control system design with aerostructural design for a highly-deformable wing. The objective of this framework is to surpass the existing aircraft endurance limits through the use of an active load alleviation system designed concurrently with the rest of the aircraft. The novelty of this work is two fold. First, a unified dynamics framework is developed to represent the full six-degree-of-freedom rigid-body along with the structural dynamics. It allows for an integrated control design to account for both manoeuvrability (flying quality) and aeroelasticity criteria simultaneously. Secondly, by synthesizing the aircraft control system along with the structural sizing and aerodynamic shape design, the final design has the potential to exploit synergies among the three disciplines and yield higher performing aircraft. A co-rotational structural framework featuring Euler--Bernoulli beam elements is developed to capture the wing's nonlinear deformations under the effect of aerodynamic and inertial loadings. In this work, a three-dimensional aerodynamic panel code, capable of calculating both steady and unsteady loadings is used. Two different control methods, a model predictive controller (MPC) and a 2-DOF mixed-norm robust controller, are considered in this work to control a highly flexible aircraft. Both control techniques offer unique advantages that make them promising for controlling a highly flexible aircraft. The control system works towards executing time-dependent manoeuvres along with performing gust/manoeuvre load alleviation. The developed framework is investigated for demonstration in two design cases: one in which the control system simply worked towards achieving or maintaining a target altitude, and another where the control system is also performing load alleviation. The use of the active load alleviation system results in a significant improvement in the aircraft performance relative to the optimum result without load alleviation. The results show that the inclusion of control system discipline along with other disciplines at early stages of aircraft design improves aircraft performance. It is also shown that structural stresses due to gust excitations can be better controlled by the use of active structural control systems which can improve the fatigue life of the structure.

Automatic Implementation of Multidisciplinary Design Optimization Architectures Using piMDO Christopher Marriage Masters of Applied Science Graduate Department of Aerospace Engineering University of Toronto 2008 Multidisciplinary Design Optimization (MDO) provides optimal solutions to complex, coupled, multidisciplinary problems. MDO seeks to manage the interactions between disciplinary simulations to produce an optimum, and feasible, design with a minimum of computational effort. Many MDO architectures and approaches have been developed, but usually in isolated situations with little chance for comparison. piMDO was developed to provide a unified framework for the solution of coupled op- timization problems and refinement of MDO approaches. The initial implementation of piMDO showed the benefits of a modular, object oriented, approach and laid the groundwork for future development of MDO architectures. This research furthered the development of piMDO by expanding the suite of available problems, incorporat- ing additional MDO architectures, and extending the object oriented approach to all of the required components for MDO. The end result is a modular, flexible software framework which is user friendly and intuitive to the practitioner. It allows complex problems to be quickly implemented and optimized with a variety of powerful numerical tools and MDO architectures. Importantly, it allows any of its components to be reorganized and sets the stage for future researchers to continue the development of MDO methods.

The growing effect of combustion pollutant emission on the environment and increasing petroleum prices are driving development of design methodologies for clean and efficient industrial combustion technologies. The design optimization methodology employs numerical algorithms to find the optimal solution of a design problem by converting it into a multivariate minimization problem. This is done by defining a vector of design parameters that specifies the design configuration, and an objective function that quantifies the performance of the design, usually so the optimal design outcome minimizes the objective function. A numerical algorithm is then employed to find the design parameters that minimize the objective function; these parameters thus specify the optimal design. However this technique is used in several other fields of research, its application to industrial combustion is fairly new. In the present study, a statistical optimization method called response surface methodology is connected to a CFD solver to find the highest combustion efficiency by changing the inlet air swirl number and burner quarl angle in a furnace. OpenFOAM is used to model the steady-state combustion of natural gas in the 300 KW BERL combustor. The main barrier to applying optimization in the design of industrial combustion equipment is the substantial computational effort needed to carry out the CFD simulation every time the objective function needs to be evaluated. This is intensified by the stiffness of the coupled governing partial differential equations, which can cause instability and divergent simulations. The present study addresses both of these issues by initializing the flow field for each objective function evaluation with the numerical results of the previously converged point. This modification dramatically reduced computation time. The combustion of diesel spray in the GenTex 50M process heater is investigated in the next part of this thesis. Experimental and numerical studies were carried out for both the cold spray and the diesel combustion where the numerical results satisfactorily predicted the observations. The simulation results show that, when carrying out a parametric design of a liquid fuel-fired combustor it is necessary to consider the effect of design parameters on the spray aerodynamic characteristics and size distribution, the air/spray interactions, and the size of the recirculation zones.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 209-213). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 209-213). Also available on the Internet.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Schaefer, Dirk; Committee Member: Panchal, Jitesh; Committee Member: Paredis, Chris; Committee Member: Rosen, David; Committee Member: Yoder, Douglas. Part of the SMARTech Electronic Thesis and Dissertation Collection.

The purpose of this thesis was to identify the optimal design parameters for a jet nozzle which obtains a local maximum shear stress while maximizing the average shear stress on the floor of a fluid filled system. This research examined how geometric parameters of a jet nozzle, such as the nozzle's angle, height, and orifice, influence the shear stress created on the bottom surface of a tank. Simulations were run using a Computational Fluid Dynamics (CFD) software package to determine shear stress values for a parameterized geometric domain including the jet nozzle. A response surface was created based on the shear stress values obtained from 112 simulated designs. A multi-objective optimization software utilized the response surface to generate designs with the best combination of parameters to achieve maximum shear stress and maximum average shear stress. The optimal configuration of parameters achieved larger shear stress values over a commercially available design.

In this article, a design methodology for complex composite aircraft structures is presented. The developed approach combines a multi-objective optimization method and a parameterized simulation model using a design concept database. Due to the combination of discrete and continuous design variables describing the structures, evolutionary algorithms are used within the presented optimization approach. The approach requires an evaluation of the design alternatives that is performed by parameterized simulation models. The variability of these models is achieved using a design concept database that contains different layouts for each implemented structural part. Due to the complexity of the generated aircraft structures, the finite element method is applied for the calculation of the structural behaviour. The applicability of the developed design approach will be demonstrated by optimizing two composite aircraft fuselage examples. The obtained results show that the developed methodology is useful and reliable for designing complex aircraft structures.

An unmanned aerial vehicle (UAV) swarm allows for a more time-efficient method of searching a specified area than a single UAV or piloted plane. There are a variety of factors that affect how well an area is surveyed. We specifically analyzed the effect both vehicle properties and communication had on the swarm search performance. We used non-dimensionalization so the results can be applied to any domain size with any type of vehicle. We found that endurance was the most important factor. Vehicles with good endurance sensed approximately 90% to 100% of the grid, even when other properties were lacking. If the vehicles lacked endurance, the amount of area the vehicles could sense at a given time step became more important and 10% more of the grid was sensed with the increase in sensed area. The maneuverability of the vehicles was measured as the vehicles' radii of turn compared to the search domain size. The maneuverability mattered the most in the middle-range endurance cases. In some cases 30% more of the grid was searched with improving vehicle maneuverability. In addition, we also examined four communication cases with different amounts of information regarding vehicle location. We found communication increased search performance by at least 6.3%. However, increasing the amount of information only changed the performance by 2.3%. We also studied the impact the range of vehicle communication had on search performance. We found that simulations benefited most from increasing the communication range when the amount of area sensed at a given time step was small and the vehicles had good maneuverability. We also extended the optimization to a multi-objective process with the inclusion of target tracking. We analyzed how the different weightings of the objectives affected the performance outcomes. We found that target tracking performance dramatically changes based on the given weighting of each objective and saw an increase of approximately 52%. However, the amount of the grid that was sensed only dropped by approximately 10%.

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