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

The Horizon Simulation Framework (HSF) is an open-source community driven mod- eling and simulation tool developed over 15 years by a lineage of Cal Poly graduate students. The tool excels in its flexibility to model an assortment of complex systems, with prebuilt modeling elements available for the simulation of space missions. A high-level simulation tool like HSF lends itself to an agile development cycle as system constraints can be quickly identified through day in the life simulation of the modeled system. The objective of the work presented in this thesis is to refactor the way in which several modeling elements are loaded in the simulation framework. A focus is placed on improving how relationships between various modeling elements are initialized to allow the flow of information between distant assets that was previously not possible. Further improvements were made to the framework with the objective of standardizing how information is communicated from user input files to locations in the framework that depend on the inputs. After implementing these updates, a demonstration scenario was created to validate the developments implemented.

A general multidisciplinary design problem features coupling and feedback between contributing analyses. This feedback may lead to convergence issues requiring significant iteration in order to obtain a feasible design. This work casts the multidisciplinary design problem as a dynamical system in order to leverage the benefits of dynamical systems theory in a new domain. Three areas from dynamical system theory are chosen for investigation: stability analysis, optimal control, and estimation theory. Stability analysis is used to investigate the existence of a solution to the design problem and how that solution can be found. Optimal control techniques allow consideration of contributing analysis output and design variables constraints at the same level of the optimization hierarchy. Finally, estimation methods are employed to rapidly evaluate the robustness of the multidisciplinary design. These three dynamical system techniques are then combined in a methodology for the rapid robust design of linear multidisciplinary systems. While inherently linear, the developed robust design methodology is shown to be extensible to nonlinear systems. The applicability and performance of the developed technique is demonstrated through linear and nonlinear test problems including the design of a hypersonic aerodynamic surface for a system in which an increase in range or improvement in landed accuracy is sought. In addition, it is shown that the developed robust design methodology scales well compared to other methods.

Testing is an integral part of a satellite’s development, requirements verification and risk mitigation efforts. A robust test program serves to verify construction, integration and assembly workmanship, ensures component, subsystem and system level functionality and reduces risk of mission or capability loss on orbit. The objective of this thesis was to develop a detailed test program for pico-satellites with a focus on the Cal Poly CubeSat architecture. The test program established a testing baseline from which other programs or users could tailor to meet their needs. Inclusive of the test program was a detailed decomposition of discrete and derived test requirements compiled from the CubeSat and Launch Vehicle communities, military guidelines, and industry standards. The test requirements were integrated into a methodical, efficient and risk adverse test flow for verification.

This project develops a quantitative method to evaluate the seismic risk for portable GSE at Vandenberg Air Force Base. Using the latest probability data available from the USGS, risk thresholds are defined for portable GSE having the potential to cause a catastrophic event. Additionally, an example tool for design engineers was developed from the seismic codes showing the tipping hazard case can be simplified into strict geometrical terms. The misinterpretation and confusion regarding the Range Safety 24 Hour Rule exemption can be avoided by assessing seismic risk for portable GSE. By using the methods herein to quantify and understand seismic risk, more informed risk decisions can be made by engineering and management. The seismic codes and requirements used and referenced throughout include but are not limited to IBC, ASCE 7, EWR 127-1, and AFSPCMAN 91-710.

Unmanned Aerial Systems (UAS) are a growing asset. Currently UAS are on the cutting edge with resources being spent developing the capabilities mostly for military use. This project is intended to create a system for non-defense customers. Specifically, the Operationally Responsive Aircraft (ORA) will appeal to academic institutions, individual consumers, future customers new to the UAS industry, as well as anybody trying to get airtime for custom sensors. The system developed in this project utilizes dual aluminum external payload bays attached to a ParkZone Radian aircraft. Each external payload bay can contain approximately 500 $\text{cm}^3$, with a height and width limit of 4.1 cm and 11.0 cm respectively. The custom sensors must weigh less than or equal to 3.2 lbs combined. The external payload bays were designed to hold an imaging payload which produces a composite map of the land surveyed. The system incorporates an Arduino Uno, SD Shield, as well as a CMOS camera and board. The processor saves individual images to an SD card. Once the aircraft has landed, the operator combines the images with Microsoft Research Image Composite Editor to create the composite map. This imaging payload has a NIIRS value of 4.0 +/- 0.4, which is equivalent to identifying a basketball court within a residential environment.

The Naval Postgraduate School is currently developing their first CubeSat, the Solar Cell Array Tester CubeSat, or NPS-SCAT. Launching a CubeSat, such as NPS-SCAT, requires environmental testing to ensure not only the success of the mission, but also the safety of other CubeSats housed in the same deployer. This thesis will address the development of CubeSat vibration testing methodology at NPS, including subsystem testing, engineering unit qualification, and flight unit testing. In addition, the new Cal Poly CubeSat Test POD Mk III will be introduced and evaluated based upon comparison with the Poly Picosatellite Orbital Deployer (P-POD). Using examples from the development of NPS-SCAT and test data from Cal Poly’s Test POD Mk III and P-POD, the current CubeSat testing methodology will be verified and an improved method for NPS CubeSat subsystem testing will be presented.

Truely optimal solutions to system design can only be obtained if the entire system is considered. In this research we consider design of commercial aircraft, but we expand the system to include a family of planes. A multidisciplinary design optimization framework is developed in which multiple aircraft, each with different missions, can be optimized simultaneously. Results are presented for a two-member family whose individual missions differ significantly. We show that both missions can be satisfied with common designs, and that by optimizing both planes simultaneously rather than following the traditional baseline plus derivative approach, the common solution is vastly improved. The new framework is also used to gain insight to the effect of design variable scaling on the optimization algorithm. / Singapore-MIT Alliance (SMA)

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.

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.