Multidisciplinary design optimization (MDO) can be used as an effective tool to improve the design of automotive structures. Large-scale MDO problems typically involve several groups who must work concurrently and autonomously for reasons of efficiency. When performing MDO, a large number of designs need to be rated. Detailed simulation models used to assess automotive design proposals are often computationally expensive to evaluate. A useful MDO process must distribute work to the groups involved and be computationally efficient. In this thesis, MDO methods are assessed in relation to the characteristics of automotive structural applications. Single-level optimization methods have a single optimizer, while multi-level optimization methods have a distributed optimization process. Collaborative optimization and analytical target cascading are possible choices of multi-level optimization methods for automotive structures. They distribute the design process, but are complex. One approach to handle the computationally demanding simulation models involves metamodel-based design optimization (MBDO), where metamodels are used as approximations of the detailed models during optimization studies. Metamodels can be created by individual groups prior to the optimization process, and therefore also offer a way of distributing work. A single-level optimization method in combination with metamodels is concluded to be the most straightforward way of implementing MDO into the development of automotive structures.

Les produits mécatroniques sont complexes et multidisciplinaires par nature. Les exigences pour les concevoir sont souvent contradictoires et doivent être validées par les différentes équipes d'ingénierie disciplinaire (ID). Pour répondre à cette complexité et réduire le temps de conception, les ingénieurs disciplinaires ont besoin de collaborer dynamiquement, de résoudre les conflits interdisciplinaires et de réutiliser les connaissances de projets antérieurs. De plus, ils ont besoin de collaborer en permanence avec l’équipe d’ingénierie systèmes (IS) pour avoir un accès direct aux exigences et l’équipe d’optimisation multidisciplinaire (OMD) pour valider le système dans sa globalité.Nous proposons d'utiliser des techniques de gestion des connaissances pour structurer les connaissances générées lors des activités de collaboration afin d'harmoniser le cycle de conception. Notre principale contribution est une approche d'unification qui explique comment IS, ID et OMD se complètent et peuvent être utilisés en synergie pour un cycle de conception intégré et continu. Notre méthodologie permet de centraliser les connaissances nécessaires à la collaboration et au suivi des exigences. Elle assure également la traçabilité des échanges entre les ingénieurs grâce à la théorie des graphes. Cette connaissance formalisée du processus de collaboration permet de définir automatiquement un problème OMD. / Mechatronic products are complex and multidisciplinary in nature. The requirements to design them are often contradictory and must be validated by the various disciplinary engineering (DE) teams. To address this complexity and reduce design time, disciplinary engineers need to collaborate dynamically, resolve interdisciplinary conflicts, and reuse knowledge from previous projects. In addition, they need to work seamlessly with the Systems Engineering (SE) team to have direct access to requirements and the Multidisciplinary Design Optimization (MDO) team for global validation. We propose to use Knowledge Management techniques to structure the knowledge generated during collaboration activities and harmonize the overall design cycle. Our primary contribution is a unification approach, elaborating how SE, DE, and MDO complement each-other and can be used in synergy for an integrated and continuous design cycle. Our methodology centralizes the product knowledge necessary for collaboration. It ensures traceability of the exchange between disciplinary engineers using graph theory. This formalized process knowledge facilitates MDO problem definition.

In order to enhance accessibility to microgravity research, the design process for experiments on the ISS must be streamlined and accessible to all scientific disciplines, not just aerospace engineers. Thus, a general design and analysis toolbox with accompanying best practices manual for microgravity liquid containment is proposed. The work presented in this thesis improves the design process by introducing a modular liquid tank design which can be filled, drained, or act as a passive liquid-gas separation device. It can also be pressurized, and used for aerosol spray. This tank can be modified to meet the design requirements of various experimental setups and liquids. Furthermore, rough simulations of this tank are presented and available to the user for modification. The simulation and design methodology for other general cases is discussed as well. After reading this thesis, the user should have a basic understanding of how liquids behave in microgravity. She will be able to run simple simulations, design, build, test, and fly a liquid management device which has been modified to suit the requirements of her specific experiment. The general tank design can be manufactured using 3-D printing, traditional CNC milling, or a combination thereof. The design methodology and best practices presented here have been used to design tanks used in experiments on the International Space Station for Budweiser and Lambda Vision. Both tanks functioned nominally on orbit. While the specific data from these experiments cannot be presented due to proprietary restrictions, using this thesis as a design guide for new experiments should yield favorable results when applied to new tank designs. If the reader has any questions or would like an updated design process, the author’s preferred contact information can be found using the Orcid iD: 0000-0002-2617-2957 .

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The Cal Poly Spacecraft Simulator is currently being developed for future testing and verifying theoretical control applications. This paper details the effort to balance the platform and remove undesired external torque from the system using System Identification technique developed by Patrick Healy. Since the relationship between the input and output of the system is linear, the least square method is proposed to identify the mass properties and location of center of mass of the system. The tests use four sine wave generators that are out of phase with different amplitudes as the inputs to excite various structural modes of the system. The outputs, angular rates of the platform, are measured by the newly implemented LN-200 Inertial Measurement Unit that helps reducing the measurement noise. Two test cases of 90o yaw rotations with the identified inertia were performed and validated against the computer simulation model; and the result shows that the test cases trajectories followed closely with the computer simulation model.

The purpose of this research is to develop and architect a preliminary multidisciplinary design optimization (MDO) tool that creates multiple types of generalized rocket fairing models. These models are sized relative to input geometric models and are analyzed and optimized, taking into account the primary objectives, namely the structural, thermal, and aerodynamic aspects of standard rocket flights. A variety of standard nose cone shapes is used as optimization proof of concept examples, being sized and compared to determine optimal choices based on the input specifications, such as the rocket body geometry and the specified trajectory paths. Any input models can be optimized to their respective best nose cone style or optimized to each of the cone styles individually, depending on the desired constraints. Two proof of concept example rocket model studies are included with varying sizes and speeds. Both have been optimized using the processes described to provide delineative instances into how results are improved and time saved. This is done by optimizing shape and thickness of the fairings while ascertaining if the remaining length downstream on the designated rocket model remains within specified stress and temperature ranges. The first optimized example exhibits a region of high stress downstream on the rocket body model that champions how these tools can be used to catch weaknesses and improve the overall integrity of a rocket design. The second example demonstrates how more established rocket designs can decrease their weight and drag through optimization of the fairing design.

Small electric uninhabited aerial vehicles (UAV) represent a rapidly expanding market requiring optimization in both efficiency and weight; efficiency is critical during cruise or loiter where the vehicle operates at part power for up to 99% of the mission time. Of the four components (battery, motor, propeller, and electronic speed controller (ESC)) of the electric propulsion system used in small UAVs, the ESC has no accepted performance model and almost no published performance data. To collect performance data, instrumentation was developed to measure electrical power in and out of the ESC using the two wattmeter method and current sense resistors; data was collected with a differential simultaneous data acquisition system. Performance of the ESC was measured under different load, commanded throttle, bus voltage, and switching frequency, and it was found that ESC efficiency decreases with increasing torque and decreasing bus voltage and does not vary much with speed and switching frequency. The final instrumentation was limited to low-voltage systems and error propagation calculations indicate a great deal of error at low power measurements; despite these limitations, an understanding of ESC performance appropriate for conceptual design of these systems was obtained. MODELING AND TEST OF THE EFFICIENCY OF ELECTRONIC SPEED CONTROLLERS FOR BRUSHLESS DC MOTORS

A systematic customer value assessment process (CVAP) was developed to give system engineering teams the capability to qualitatively and quantitatively assess customer values. It also provides processes and techniques used to create and identify alternatives, evaluate alternatives in terms of effectiveness, cost, and risk. The ultimate goal is to provide customers (or decision makers) with objective and traceable procurement recommendations. The creation of CVAP was driven by an industry need to provide ballistic missile defense (BMD) customers with a value proposition of contractors’ BMD systems. The information that outputs from CVAP can be used to guide BMD contractors in formulating a value proposition, which is used to steer customers to procure their BMD system(s) instead of competing system(s). The outputs from CVAP also illuminate areas where systems can be improved to stay relevant with customer values by identifying capability gaps. CVAP incorporates proven approaches and techniques appropriate for military applications. However, CVAP is adaptable and may be applied to business, engineering, and even personal every-day decision problems and opportunities. CVAP is based on the systems decision process (SDP) developed by Gregory S. Parnell and other systems engineering faculty at the Unites States Military Academy (USMA). SDP combines Value-Focused Thinking (VFT) decision analysis philosophy with Multi-Objective Decision Analysis (MODA) quantitative analysis of alternatives. CVAP improves SDP’s qualitative value model by implementing Quality Function Deployment (QFD), solution design implements creative problem solving techniques, and the qualitative value model by adding cost analysis and risk assessment processes practiced by the U.S DoD and industry. CVAP and SDP fundamentally differ from other decision making approaches, like the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), by distinctly separating the value/utility function assessment process with the ranking of alternatives. This explicit value assessment allows for straightforward traceability of the specific factors that influence decisions, which illuminates the tradeoffs involved in making decisions with multiple objectives. CVAP is intended to be a decision support tool with the ultimate purpose of helping decision makers attain the best solution and understanding the differences between the alternatives. CVAP does not include any processes for implementation of the alternative that the customer selects. CVAP is applied to ballistic missile defense (BMD) to give contractors ideas on how to use it. An introduction of BMD, unique BMD challenges, and how CVAP can improve the BMD decision making process is presented. Each phase of CVAP is applied to the BMD decision environment. CVAP is applied to a fictitious BMD example.

The Cal Poly CubeSat Laboratory (CPCL) is currently facing unprecedented engineering challenges—both technically and programmatically—due to the increasing cost and complexity of CubeSat flight missions. In responding to recent RFPs, the CPCL has been forced to find commercially available solutions to entire mission critical spacecraft subsystems such as propulsion and attitude determination & control, because currently no in-house options exist for consideration. The commercially available solutions for these subsystems are often extremely expensive and sometimes provide excessively good performance with respect to mission requirements. Furthermore, use of entire commercial subsystems detracts from the hands-on learning objectives of the CPCL by removing engineering responsibility from students. Therefore, if these particular subsystems can be designed, tested, and integrated in-house at Cal Poly, the result would be twofold: 1) the space of missions supportable by the CPCL under tight budget constraints will grow, and 2) students will be provided with unique, hands-on guidance, navigation, and control learning opportunities. In this thesis, the CPCL’s attitude determination and control system design and analysis toolkit is significantly improved to support in-house ADCS development. The toolkit—including the improvements presented in this work—is then used to complete the existing, partially complete CPCL ADCS design. To fill in missing gaps, particular emphasis is placed on guidance and control algorithm design and selection of attitude actuators. Simulation results show that the completed design is competitive for use in a large class of small satellite missions for which pointing accuracy requirements are on the order of a few degrees.