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

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.

Yes / This paper introduces a novel method referred to as Enhanced Sequence Diagram (ESD) to support rigorous functional modelling of complex multidisciplinary systems. The ESD concept integrates an exchanges based functional requirements reasoning based on a coherent graphical schema, integrated with the system operational analysis based on a sequence diagram. The effectiveness of the method to support generic function modelling of complex multidisciplinary systems at the early conceptual design stages is discussed in conjunction with an electric vehicle powertrain example, followed by an assessment of potential impact for broader application of the method in the industry.

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