This study uses numerical design optimization with advanced metamodeling techniques to investigate the effects of material substitution and dummy models on crashworthiness characteristics of automotive structures. A full-scale Dodge Neon LS-DYNA finite element model is used in all structural analysis and optimization calculations. Optimization is performed using vehicle-based responses for multiple crash scenarios and occupant-based responses for one crash scenario. An AZ31 magnesium alloy is substituted for the baseline steel in twenty-two vehicle parts. Five base metamodels and an Optimized Ensemble metamodel are used to develop global surrogate models of crash-induced responses. Magnesium alloy is found to maintain or improve vehicle crashworthiness with an approximate 50% reduction in selected part mass using vehicle-based responses while dummy-based designs show less percentage decrease in weight. Vehicle-based responses selected to approximate dummy injury metrics do not show the same relative change compared to dummy-based responses.

As engineering systems grow in complexity so too must the design tools that we use evolve and allow for decision makers to efficiently ask questions of their model and obtain meaningful answers. The process of whitespace exploration has recently been developed to aid in engineering design and provide insight into a design space where traditional design exploration methods may fail. In an effort to further the research and development of whitespace exploration algorithms, a software package called Thalia has been created to allow for automated data collection and experimentation with the whitespace exploration methodology. In this work, whitespace exploration is defined and the current state of the art of whitespace exploration algorithms is reviewed. The whitespace exploration library Thalia along with a collection of benchmarking cases are described in detail. A set of experiments on the benchmark cases are run and analyzed to further understand the behavior of the algorithm and outline initial performance results which can later be used for comparison to aid in improving the methodology.

Many companies use product families in order to offer product variants that appeal to different market segments while minimizing costs. Because the market demand is generally not uniform for all possible product variants, during the design phase a decision must be made as to which variants will be offered and how many. This thesis presents a new approach to solving this problem. The product is defined in terms of performance parameters. The market demand is captured in a preference model and applied to these parameters in order to represent the total potential market. The number and placement of the product variants are optimized in order to maximize percentage of the potential market that they span. This method is applied to a family of mountain bikes and a family of flow-regulating disks used in industrial applications. These examples show that usage of this method can result in a significant increase in potential market and a significant reduction in production costs.

In the field of control theory, optimal performance is generally defined as the best possible controlled performance given a static, unchangeable plant system. However, principled design of the underlying system can make designing effective controllers easier and dramatically improve the final control performance beyond what any finely tuned controller could achieve alone. This work develops performance metrics for serial robot arms which help guide the design and optimization of the structure of the arm to achieve greater final performance. First, a kinematic (motion-based) metric called the Actuator Independence Metric (AIM) measures the uniqueness of the movement capabilities of the different joints in a robot arm. Arms which are optimized with respect to the AIM exhibit a greater freedom of movement. In particular, it is shown that the AIM score of a robot correlates strongly with their ability to find solutions to the Inverse Kinematics problem, and that redundant arms with a high AIM score have more useful null-spaces with significant ability to change configuration while maintaining a fixed end-effector pose. Second, a dynamic metric called the Acceleration Radius is explored. The acceleration radius measures the maximum acceleration which a robot arm is capable of generating in any direction. An efficient algorithm for calculating the acceleration radius is developed which exploits the geometry of the mapping from joint torques to acceleration. A design optimization is carried out to demonstrate how the acceleration radius predicts the dynamic movement capabilities of robot arms. It is shown that arms which are optimal with respect to the acceleration radius can follow faster paths through a task space. The metrics developed in this thesis can be used to create customized robot arm designs for specific tasks, which will exhibit desirable control performance.

Requirements verification is typically the costliest part of the systems engineering design process. In the commercial aircraft industry, as the software and hardware design evolves, it must be verified to conform to requirements. In addition, when new design releases are made, regression analysis must be performed which usually requires repeat testing. To streamline verification, a suite of automated verification tools is described in this document which can reduce the test effort. This test suite can be qualified to be used to verify systems at any DO-178B design assurance level. Some of the software tools are briefly described below. There are major advantages of this automated verification effort. The tools can either be internally developed by a company or purchased "off the shelf", depending upon budget and staff constraints. Every automated test case can be run with the click of a button and failures caused by human factors are reduced. The station can be qualified per DO-178B guidelines, and can also be expanded to support ARINC 429, AFDX, Ethernet, and MIL-STD-1553 interfaces. The expansion of these test programs would enable the creation of a universal avionics test suite with minimal cost and a reduction of the overall program verification effort. The following is a presentation of an automated test station capable of reducing verification time and cost. The hardware and software aspects needed to create the test station are examined. Also, steps are provided to help guide a designer through the tool qualification process. Lastly, a full suite of test functions are included that can be implemented and customized to verify a wide range of avionics communication characteristics.

The purpose of this work is to help bridge the gap between aircraft conceptual design and analysis. Much work is needed, but distilling essential characteristics from a design and collecting them in an easily accessible format that is amenable to use by inexpensive analysis tools is a significant contribution to this goal. Toward that end, four types of reduced-fidelity or degenerate geometric representations have been defined and implemented in VSP, a parametric geometry modeler. The four types are degenerate surface, degenerate plate, degenerate stick, and degenerate point, corresponding to three-, two-, one-, and zero- dimensional representations of underlying geometry, respectively. The information contained in these representations was targeted specifically at lifting line, vortex lattice, equivalent beam, and equivalent plate theories, with the idea that suitability for interface with these methods would imply suitability for use with many other analysis techniques. The ability to output this information in two plain text formats— comma separated value and Matlab script—has also been implemented in VSP, making it readily available for use. A modified Cessna 182 wing created in VSP was used to test the suitability of degenerate geometry to interface with the four target analysis techniques. All four test cases were easily completed using the information contained in the degenerate geometric types, and similar techniques utilizing different degenerate geometries produced similar results. The following work outlines the theoretical underpinnings of degenerate geometry and the fidelity-reduction process. It also describes in detail how the routines that create degenerate geometry were implemented in VSP and concludes with the analysis test cases, stating their results and comparing results among different techniques.

The Horizon Simulation Framework is a modeling and simulation framework developed to verify system level requirements. In this thesis, the framework is extended to include the Dynamic position type that existed in the early development phase of the framework. The Dynamic position type is tested through the modeling and simulation of a sounding rocket. An active control system based on linear-quadratic regulator (LQR) control theory is implemented and tested in the simulation to determine the overall effect on altitude. A first order aerodynamics and aeroprediction model are created within the framework to allow for rapid changes early in the design process of the sounding rocket. The flight dynamics are compared to two different sounding rocket flights and the aeroprediction model is validated against public wind tunnel test data.

This thesis work presents the formulation for a tool developed in MATLAB to determine the mass of a space object from the fusion of astrometric and photometric data. The application for such a tool is to better model the mass estimation method used for high area-to-mass ratio objects found in high altitude orbit regimes. Typically, the effect of solar radiation pressure is examined with angles observations to deduce area-to-mass ratio calculations for space objects since the area-to-mass ratio can greatly affect its orbital dynamics. On the other hand, photometric data is not sensitive to mass but is a function of the albedo-area and the rotational dynamics of the space object. Thus from these two data types it is possible to disentangle intrinsic properties using albedo-area and area-to-mass and ultimately determine the mass of a space object. Three case studies were performed for the different orbit regimes: geosynchronous, highly elliptic, and medium earth orbit. The position states were either initialized with a two line element set or with initial orbit determination methods to simulate data which was run through an unscented Kalman filter to estimate the translational and rotational states of the space object as well as the mass an albedo area. In the geosynchronous and highly elliptic cases the tool was able to accurately predict the mass value to within 5kg of the true value based on a 95% confidence interval which will allow applications to understanding high area-to-mass objects with high certainty.

On February 13, 2012, California Polytechnic State University, San Luis Obispo flew three Poly-Picosatellite Orbital Deployers (P-PODs), carrying seven European University CubeSats sponsored by the European Space Agency (ESA), on the Vega Maiden Flight. This was the first time CubeSats shared a ride to space with other payloads on an ESA-owned launch opportunity. In order to meet launch requirements, it must be proven through proper documentation that the P-POD would operate properly and not interfere with the launch vehicle or other payloads on the mission. This thesis outlines the program flow, required documentation, and issues encountered during the launch campaign to get the P-PODs properly qualified and integrated on to the Vega launch vehicle. This mission required Cal Poly to create several unique solutions, which were only implemented for this mission, in order to meet unique technical requirements and programmatic goals. As a result of this mission’s success the ESA Education Office implemented the Fly Your Satellite Program, which has continued to support and launch CubeSats developed by European universities.

We are in an era of massive spending cuts in educational institutions, aerospace companies and governmental entities. Educational institutions are pursuing more training for less money, aerospace companies are reducing the cost of gaining ight heritage and the government is cutting budgets and their response times. Organizations are accomplishing this improved efficiency by moving away from large-scale satellite projects and developing pico and nanosatellites following the CubeSat specifications. One of the major challenges of developing satellites to the standard CubeSat mission requirements is meeting the exceedingly tight power, data and communication constraints. A MATLAB toolbox was created to assist the CubeSat community with understanding these restrictions, optimizing their systems, increasing mission success and decreasing the time building to these initial requirements. The Toolbox incorporated the lessons learned from the past nine years of CubeSats' successes and Analytical Graphics, Inc. (AGI)'s Satellite Tool Kit (STK). The CubeSat Mission Planning Toolbox (CMPT) provides graphical representations of the important requirements a systems engineer needs to plan their mission. This includes requirements for data storage, ground station facilities, orbital parameters, and power. CMPT also allows for a comparison of broadcast (BC) downlinking to Ground Station Initiated (GSI) downlinking for payload data using federated ground station networks. Ultimately, this tool saves time and money for the CubeSat systems engineer