As engineering technologies continue to grow and improve, the complexities in the engineering models which utilize these technologies also increase. This seemingly endless cycle of increased computational power and demand has sparked the need to create representative models, or metamodels, which accurately reflect these complex design spaces in a computationally efficient manner. As research into metamodeling and using advanced metamodeling techniques continues, it is important to remember design engineers who need to use these advancements. Even experienced engineers may not be well versed in the material and mathematical background that is currently required to generate and fully comprehend advanced complex metamodels. A metamodeling environment which utilizes an advanced metamodeling technique known as Gaussian Process is being developed to help bridge the gap that is currently growing between the research community and design engineers. This tool allows users to easily create, modify, query, and visually/numerically assess the quality of metamodels for a broad spectrum of design challenges.

No / A species conservation technique takes inspiration from the field of ecology, in which the population is divided into several species according to their similarity. Based on this technique, a Species Conservation Genetic Algorithms (SCGA) was established and had been proved to be very effective in finding multiple solutions of multimodal optimisation problems, including some problems known to be deceptive for genetic algorithms (GAs). In this paper, the SCGA is introduced to engineering structure design, and two structure designs are used to demonstrate the performances of the SCGA and how the choice of a meaningful measure of similarity will help in exploration of significant designs.

<p> The optimization study of space frames has been considered in two aspects in this project work. The first was to develop a suitable optimization technique for a nonlinear programming problem including equality constraints, without any particular reference to structural optimization. The necessacity for the above requirement was due to the fact that almost all existing methods on optimization have some limitation. The second object of this study was to set up the necessary equations for the constraints on stress and on frequency for the structural model used, and then to use the developed technique to optimize the structural model for minimum weight. </p> <p> A simple and effective strategy, which is a combination of direct search and linear approximate programming is believed to have been developed for optimization of simple nonlinear type equations. </p> <p> The analysis of the space structure and the study of structural optimization revealed several difficulties inherent in the evaluation of constraining equations for the stresses and frequencies, which makes the optimization very difficult. </p> / Thesis / Master of Engineering (ME)

Reliable, affordable access to electrical power is a requirement for almost all aspects of developed societies. Challenges associated with reducing carbon emissions has led to growing interest in nuclear-renewable hybrid energy systems (N-RHES). Much work has already been done in suggesting and analyzing various N-RHES using a variety of optimization techniques and assumptions. This work builds upon previous techniques for simultaneous combined design and dispatch optimization (CDDO) for hybrid energy systems (HES). The first contribution of this work is the development and application of sensitivity analysis tailored to the combined design and dispatch optimization problem. This sensitivity analysis cover uncertainty in design parameters, time series and dispatch horizon lengths. The result is a deeper insight into which sources of uncertainty are most important to account for and how the uncertainty around these sources can be quantified. The second contribution of this work is a novel multi-scale optimization algorithm for the combined HES design and dispatch optimization. This algorithm supports optimization of nonlinear models over very long-time horizons. This method is based on a multi-dimensional distribution of the optimal capacities for a system as determined by a large number of combined design and dispatch optimization problems each covering a subset of the complete time horizon. This method shows good agreement with the direct solution to multiple example systems and is then used to solve a problem with a dispatch horizon length 112.5 times longer than is solvable directly. The third contribution of this work is the application of the novel multi-scale method to three HES. Each of the application systems is used to demonstrate the strengths, validation and applicability of the developed algorithm to a wide range of possible HES/NHES designs.

No description available.

No description available.

No description available.

<p> Global routing in VLSI (very large scale integration) design is one of the most challenging discrete optimization problems in computational theory and practice. In this thesis, we present a polynomial time approximation algorithm for the global routing problem based on an integer programming formulation. The algorithm features a theoretical approximation bound, while ensuring all the routing demands are concurrently satisfied.</p> <p> We provide both a serial and a parallel implementation, as well as develop several heuristics to improve the quality of the solution and reduce running time. Our computational tests on a well-known benchmark set show that, combined with certain heuristics, our new algorithms perform very well compared with other integer programming approaches.</p> / Thesis / Master of Science (MSc)

Recent transonic airliner designs have generally converged upon a common cantilever low-wing configuration. It is unlikely that further large strides in performance are possible without a significant departure from the present design paradigm. One such alternative configuration is the strut-braced wing, which uses a strut for wing bending load alleviation, allowing increased aspect ratio and reduced wing thickness to increase the lift to drag ratio. The thinner wing has less transonic wave drag, permitting the wing to unsweep for increased areas of natural laminar flow and further structural weight savings. High aerodynamic efficiency translates into reduced fuel consumption and smaller, quieter, less expensive engines with lower noise pollution. A Multidisciplinary Design Optimization (MDO) approach is essential to understand the full potential of this synergistic configuration due to the strong interdependency of structures, aerodynamics and propulsion. NASA defined a need for a 325-passenger transport capable of flying 7500 nautical miles at Mach 0.85 for a 2010 date of entry into service. Lockheed Martin Aeronautical systems (LMAS), our industry partner, placed great emphasis on realistic constraints, projected technology levels, manufacturing and certification issues. Numerous design challenges specific to the strut-braced wing became apparent through the interactions with LMAS, and modifications had to be made to the Virginia Tech code to reflect these concerns, thus contributing realism to the MDO results. The SBW configuration is 9.2-17.4% lighter, burns 16.2-19.3% less fuel, requires 21.5-31.6% smaller engines and costs 3.8-7.2% less than equivalent cantilever wing aircraft. / Master of Science

When designing aircraft wings shapes, it is important to ensure that the flight envelope does not overlap with regions of flutter or Limit Cycle Oscillation (LCO). A quick assessment of these dynamic aeroelastic for various design candidates is key to successful design. Flutter based design requires the sensitivity of flutter parameters to be known with the respect of design parameters. Traditionally, frequency domain based methods have been used to predict flutter characteristics and its sensitivity. However, this approach is only applicable for linear or linearized models and cannot be applied to systems undergoing LCO or other nonlinear effects. Though the time accurate approach can be implemented to overcome this problem, it is computationally expensive. Also, the unsteady adjoint formulation for sensitivity analysis, requires the state and adjoint variables to be stored at every time step, which prohibitively increases the memory requirement. In this work, these problems have been overcome by implementing a time spectral method based approach to compute flutter onset, LCOs and their design sensitivities in a computationally efficient manner. The time spectral based formulation approximates the solution as a discrete Fourier series and directly solves for the periodic steady state, leading to a steady formulation. This can lead to the time spectral approach to be faster than the time accurate approach. More importantly, the steady formulation of the time spectral method also eliminates the memory issues faced by the unsteady adjoint formulation. The time spectral based flutter/LCO prediction method was used to predict flutter and LCO characteristics of the AGARD 445.6 wing and pitch/plunge airfoil section with NACA 64A010 airfoil. Furthermore, the adjoint based sensitivity analysis was used to carry out aerodynamic shape optimization, with an objective of maximizing the flutter velocity with and without constraints on the drag coefficient. The resulting designs show significant increase in the flutter velocity and the corresponding LCO velocity profile. The resulting airfoils display a greater sensitivity to the transonic shock which in turn leads to greater aerodynamic damping and hence leading to an increase in flutter velocity. / Doctor of Philosophy / When designing aircrafts, dynamic aeroelastic effects such as flutter onset and Limit Cycle Oscillations need to considered. At low enough flight speeds, any vibrations arising in the aircraft structure are damped out by the airflow. However, beyond a certain flight speed, instead of damping out the vibrations, the airflow accentuates these vibrations. This is known as flutter and it can lead to catastrophic structural failure. Hence, during the aircraft design phase, it must be ensured that the aircraft would not experience flutter during the flight conditions. One of the contribution of this work has been to come up with a fast and accurate method to predict flutter using computational modelling. Depending on the scenario, it is also possible that during flutter, the vibrations in the structure increase to a certain amplitude before leveling off due to interaction of non-linear physics. This condition is known as limit cycle oscillation. While they can arise due to different kinds of non-linearities, in this work the focus has been on aerodynamic non-linearities arising from shocks in transonic flight conditions. While limit cycle oscillations are undesirable as they can cause structural fatigue, they can also save the aircraft from imminent structural fracture and hence it is important to accurately predict them as well. The main advantage of the method developed in this work is that the same method can be used to predict both the flutter onset condition and limit cycle oscillations. This is a novel development as most of the traditional approaches in dynamic aeroelasticity cannot predict both the effects. The developed flutter/LCO prediction method has then been used in design with the goal of achieving superior flutter characteristics. In this study, the shape of the baseline airfoil is changed with the goal of increasing the flutter velocity. This enables the designed system to fly faster without addition of weight. Since the design has been carried out using gradient based optimization approach, an efficient way to compute the gradient needs to be used. Traditional approaches to compute the gradient, such as Finite Difference Method, have computational cost proportional to the number of design variables. This becomes a problem for shape design optimization, where a large number of design variables are required. This has been overcome by developing an adjoint based sensitivity analysis method. The main advantage of the adjoint based sensitivity analysis is that it its computational cost is independent of the number of design variables, and hence a large number of design variables can be accommodated. The developed flutter/LCO prediction and adjoint based sensitivity analysis framework was used to carry out shape design for a pitch/plunge airfoil section. The objective of the design process was to maximize the flutter onset velocity with and without constraints on drag. The resulting optimized airfoils showed significant increase in the flutter velocity.