The demand for energy and cost efficient buildings has made architects and contractors more aware of the resources consumed by the built environment. While the actual economic and environmental costs of future construction can never be completely predicted, energy simulations and cost modeling have become accepted ways to guide the design and construction process by comparing possible outcomes. These tools are now commonplace in the construction industry, and researchers are continuing to develop new and innovative strategies to optimize building design and construction. Previous research has proven that genetic algorithms are effective methods to evaluate and optimize building design in situations that contain a large number of possible solutions. The technique makes a computationally difficult multi-optimization process possible but is still a reactive and time consuming process that focuses on evaluation rather than solution generation. This research presented in this paper builds upon established multi-objective optimization techniques that use an energy simulator to estimate a conceptual building’s energy use as well as construction cost. The study compares simulations of a simplified model of a 3-story inpatient hospital located in Atlanta, Georgia using a defined set of variables. A combined global minimum of annual energy consumption and total construction is sought after using a method that utilizes a genetic algorithm. The second phase of this research uses a modified approach that combines the traditional genetic algorithm with a seeding method that utilizes previous results. A new set of simulations were established that duplicates the initial trials using a slightly modified set of design variables. The simulation was altered, and the phase one trials were utilized as the first generation of simulated solutions. The objective of this thesis is to explore one method of making energy use and cost estimating more accessible to the construction industry by combining simulation optimization and indexing. The results indicate that this study’s proposed augmented approach has potential benefits to building design optimization, although more research is required to validate this hypothesis in its entirety. This study concludes that the proposed approach can potentially reduce the time needed for individual optimization exercises by creating a cumulative, robust catalog of previous computations that will inform and seed future analyses. The research was conducted in five general stages. The first part defines the research problem and scope of research to be conducted. In the second part, the concepts of genetic algorithms and energy simulation are explored in a comprehensive literature review. The remaining parts explain the trial simulations performed in this study. Part three explains the experiment’s methodology, and part four describes the simulation results. The fifth and final part looks at what the possible conclusions that can be made from analyzing the study’s results.

Multidisciplinary cancer conferences (MCCs) provide an opportunity for health professionals to discuss diagnosis and treatment options with the goal of providing optimal patient management. No prior studies have explored the experiences of adopting and implementing MCCs in Canada. Methods: Using a grounded theory approach, interviews, participant-observation, and document analysis were triangulated to explore the experiences of implementing MCCs at four hospitals in Ontario, Canada. Constant comparative analysis was used to identify themes and assimilate them into a theoretical understanding of policy, administrative/organizational, and participant contributions to implementing MCCs. Results: Thirty-seven MCCs, in three hospitals, were observed, and 48 interviews were conducted. The core conceptual category was a perceived value for time balance, which was influenced by policy and administrative factors, and themes related to MCC structure and participant interaction. Conclusions: MCC implementation in Ontario is inconsistent. Future efforts should concentrate on a systematic implementation plan involving clinicians and administrators.

Non-planar lifting surfaces offer potentially significant gains in aerodynamic efficiency by lowering induced drag. Non-aerodynamic considerations, such as structures can impact the overall efficiency. Here, a panel method and equivalent beam finite element model are used to explore non-planar configurations taking into account the coupling between aerodynamics and structures. A single discipline aerodynamic optimization and a multidisciplinary aerostructural optimization are investigated. Due to the complexity of the design space and the presence of multiple local minima, an augmented Lagrangian particle swarm optimizer is used. The aerodynamic optimum solution found for rectangular lifting surfaces is a box wing, while allowing for sweep and taper yields a joined wing. Adding parasitic drag in the aerodynamic model reduces the size of the non--planar elements. The aerostructural optimal solution found is a winglet configuration when the span is constrained and a wing rake when there is no such constraint.

In this study an automated multidisciplinary design optimization code is developed for the minimum weight design of a composite wing box. The multidisciplinary static strength, aeroelastic stability, and manufacturing requirements are simultaneously addressed in a global optimization environment through a genetic search algorithm. The static strength requirements include obtaining positive margins of safety for all the structural parts. The modified engineering bending theory together with the coarse finite element model methodology is utilized to determine the stress distribution. The nonlinear effects, stemming from load redistribution in the structure after buckling occurs, are also taken into account. The buckling analysis is based on the Rayleigh-Ritz method and the Gerard method is used for the crippling analysis. The aeroelastic stability requirements include obtaining a flutter/divergence free wing box with a prescribed damping level. The root locus method is used for aeroelastic stability analysis. The unsteady aerodynamic loads in the Laplace domain are obtained from their counterparts in the frequency domain by using Rogers rational function approximations. The outer geometry of the wing is assumed fixed and the design variables included physical properties like thicknesses, cross sectional dimensions, the number of plies and their corresponding orientation angles. The developed code, which utilizes MSC/NASTRAN&reg / as a finite element solver, is used to design a single cell, wing box with internal metallic substructure and composite skins.

Multidisciplinary cancer conferences (MCCs) provide an opportunity for health professionals to discuss diagnosis and treatment options with the goal of providing optimal patient management. No prior studies have explored the experiences of adopting and implementing MCCs in Canada. Methods: Using a grounded theory approach, interviews, participant-observation, and document analysis were triangulated to explore the experiences of implementing MCCs at four hospitals in Ontario, Canada. Constant comparative analysis was used to identify themes and assimilate them into a theoretical understanding of policy, administrative/organizational, and participant contributions to implementing MCCs. Results: Thirty-seven MCCs, in three hospitals, were observed, and 48 interviews were conducted. The core conceptual category was a perceived value for time balance, which was influenced by policy and administrative factors, and themes related to MCC structure and participant interaction. Conclusions: MCC implementation in Ontario is inconsistent. Future efforts should concentrate on a systematic implementation plan involving clinicians and administrators.

Non-planar lifting surfaces offer potentially significant gains in aerodynamic efficiency by lowering induced drag. Non-aerodynamic considerations, such as structures can impact the overall efficiency. Here, a panel method and equivalent beam finite element model are used to explore non-planar configurations taking into account the coupling between aerodynamics and structures. A single discipline aerodynamic optimization and a multidisciplinary aerostructural optimization are investigated. Due to the complexity of the design space and the presence of multiple local minima, an augmented Lagrangian particle swarm optimizer is used. The aerodynamic optimum solution found for rectangular lifting surfaces is a box wing, while allowing for sweep and taper yields a joined wing. Adding parasitic drag in the aerodynamic model reduces the size of the non--planar elements. The aerostructural optimal solution found is a winglet configuration when the span is constrained and a wing rake when there is no such constraint.

This thesis presents a research project and results of design and optimization of a composite wing structure for a large aircraft in flying wing configuration. The design process started from conceptual design and preliminary design, which includes initial sizing and stressing followed by numerical modelling and analysis of the wing structure. The research was then focused on the minimum weight optimization of the /composite wing structure /subject to multiple design /constraints. The modelling, analysis and optimization process has been performed by using the NASTRAN code. The methodology and technique not only make the modelling in high accuracy, but also keep the whole process within one commercial package for practical application. The example aircraft, called FW-11, is a 250-seat commercial airliner of flying wing configuration designed through our MSc students Group Design Project (GDP) in Cranfield University. Started from conceptual design in the GDP, a high-aspect-ratio and large sweepback angle flying wing configuration has been adopted. During the GDP, the author was responsible for the structural layout design and material selection. Composite material has been chosen as the preferable material for both the inner and outer wing components. Based on the derivation of structural design data in the conceptual phase, the author continued with the preliminary design of the outer wing airframe and then focused on the optimization of the composite wing structure. Cont/d.

Experimentation and approximation are essential for efficiency and effectiveness in concurrent engineering analyses of large-scale complex systems. The approximation-based design strategy is not fully utilized in industrial applications in which designers have to deal with multi-disciplinary, multi-variable, multi-response, and multi-objective analysis using very complicated and expensive-to-run computer analysis codes or physical experiments. With current experimental design and metamodeling techniques, it is difficult for engineers to develop acceptable metamodels for irregular responses and achieve good design solutions in large design spaces at low prices. To circumvent this problem, engineers tend to either adopt low-fidelity simulations or models with which important response properties may be lost, or restrict the study to very small design spaces. Information from expensive physical or computer experiments is often used as a validation in late design stages instead of analysis tools that are used in early-stage design. This increases the possibility of expensive re-design processes and the time-to-market. In this dissertation, two methods, the Sequential Exploratory Experimental Design (SEED) and the Efficient Robust Concept Exploration Method (E-RCEM) are developed to address these problems. The SEED and E-RCEM methods help develop acceptable metamodels for irregular responses with expensive experiments and achieve satisficing design solutions in large design spaces with limited computational or monetary resources. It is verified that more accurate metamodels are developed and better design solutions are achieved with SEED and E-RCEM than with traditional approximation-based design methods. SEED and E-RCEM facilitate the full utility of the simulation-and-approximation-based design strategy in engineering and scientific applications. Several preliminary approaches for metamodel validation with additional validation points are proposed in this dissertation, after verifying that the most-widely-used method of leave-one-out cross-validation is theoretically inappropriate in testing the accuracy of metamodels. A comparison of the performance of kriging and MARS metamodels is done in this dissertation. Then a sequential metamodeling approach is proposed to utilize different types of metamodels along the design timeline. Several single-variable or two-variable examples and two engineering example, the design of pressure vessels and the design of unit cells for linear cellular alloys, are used in this dissertation to facilitate our studies.

The concept of applying several disciplines to the design and optimization processes may not be new, but it does not currently seem to be widely accepted in industry. The reason for this might be the lack of well-known tools for realizing a complete multidisciplinary design and analysis of a product. This study aims to propose a method that enables engineers in some design disciplines to perform a fairly detailed analysis and optimization of a design using commercially available software as well as codes developed at Georgia Tech. The ultimate goal is when the system is set up properly, the CAD model of the design, including all subsystems, will be automatically updated as soon as a new part or assembly is added to the design; or it will be updated when an analysis and/or an optimization is performed and the geometry needs to be modified. Such a design process takes dramatically less time to complete; therefore, it should reduce development time and costs. The optimization method is demonstrated on an existing helicopter rotor originally designed in the 1960's. The rotor is already an effective design with novel features. However, application of the optimization principles together with high-speed computing resulted in an even better design. The objective function to be minimized is related to the vibrations of the rotor system under gusty wind conditions. The design parameters are all continuous variables. Optimization is performed in a number of steps. First, the most crucial design variables of the objective function are identified. With these variables, Latin Hypercube Sampling method is used to probe the design space of several local minima and maxima. After analysis of numerous samples, an optimum configuration of the design that is more stable than that of the initial design is reached. The process requires several software tools: CATIA as the CAD tool, ANSYS as the FEA tool, VABS for obtaining the cross-sectional structural properties, and DYMORE for the frequency and dynamic analysis of the rotor. MATLAB codes are also employed to generate input files and read output files of DYMORE. All these tools are connected using ModelCenter.

<p>Aircrafttrajectory optimization is traditionally used forminimizing fuel consumption or time when going from one flightstate to another. This thesis presents a possible approach toincorporate tactical constraints in aircraft trajectoryoptimization.</p><p>The stealth technology of today focuses on making thetactics already in use more effective. Since tactics andstealth are closely interrelated, new and better results may beobtained if both aspects are considered simultaneously. Simplyreducing the radar cross section area in some directionswithout considering tactical aspects may result in little, ifany, improvement.</p><p>Flight tests have been performed in cooperation withEricsson Microwave Systems and the Swedish Air Force FlightAcademy. The aircraft used was the subsonic jet trainer Saab105, designated SK60 by the Swedish Air Force. The results showa decrease of 40% in the time interval between the instant theaircraft was first detected until it could pass above the radarstation. This corresponds to a reduced radar cross section(RCS) in the direction from the aircraft to the radar of almost90%, if classical RCS reduction techniques would have beenapplied.</p><p>If a modern aircraft with stealth properties would be used,the proposed methodology is believed to increase the possibleimprovements further. This is because the variation of themagnitude of RCS in different directions is greater for a shapeoptimized aircraft, which is the property exploited by thedeveloped method.</p><p>The methods presented are indeed an approach utilizing theideas of the network centric warfare (NCW) concept. Themethodology presented depends on accurate information about theadversary, while also providing up-to-date information to theother users in the information network.</p><p>The thesis focuses on aircraft but the methods are generaland may be adapted for missiles, shipsor land vehicles. Theproposed methods are also economically viable since they areuseful for existing platforms without costly modifications. Themethods presented are not limited to radar threats only. Thereasons for using radar in this thesis are the availablenon-classified data and that radar is known to pose a majorthreat against aircraft.</p>