Mixed Reality experiences, that blend physical and virtual objects, have become commonplace on handheld computing devices. One common application of these technologies is their use in cultural heritage "walking tours." These tours provide information about the surrounding environment in a variety of contexts, to suit the needs and interests of different groups of participants. Using the familiar "campus tour" as a canonical example, this dissertation investigates the technical and cognitive processes involved in transferring this tour from its physical and analog form into Mixed Reality. Using the concept of spatial scale borrowed from cognitive geography, this work identifies the need to create and maintain continuity across different scales of spatial experience as being of paramount importance to successful Mixed Reality walking tours. The concepts of scale transitions, coordination of representations across scales, and scale-matching are shown to be essential to maintaining the continuity of experience. Specific techniques that embody these concepts are also discussed and demonstrated in a number of Mixed Reality examples, including in the context of a successful deployment of a Mixed Reality Tour of the Georgia Tech campus. The potential for a "Language of Mixed Reality" based on the concepts outlined in this work is also discussed, and a general framework, called the Mixed Reality Scale Framework is shown to meet all the necessary criteria for being a cognitive theory of Human-Centered Computing in the context of Mixed Reality.

One of the important factors to be considered in designing an engineering system is uncertainty, which emanates from natural randomness, limited data, or limited knowledge of systems. In this study, a robust design methodology is established in order to design multifunctional materials, employing multi-time and length scale analyses. The Robust Concept Exploration Method with Error Margin Index (RCEM-EMI) is proposed for design incorporating non-deterministic system behavior. The Inductive Design Exploration Method (IDEM) is proposed to facilitate distributed, robust decision-making under propagated uncertainty in a series of multiscale analyses or simulations. These methods are verified in the context of Design of Multifunctional Energetic Structural Materials (MESM). The MESM is being developed to replace the large amount of steel reinforcement in a missile penetrator for light weight, high energy release, and sound structural integrity. In this example, the methods facilitate following state-of-the-art design capabilities, robust MESM design under (a) random microstructure changes and (b) propagated uncertainty in a multiscale analysis chain. The methods are designed to facilitate effective and efficient materials design; however, they are generalized to be applicable to any complex engineering systems design that incorporates computationally intensive simulations or expensive experiments, non-deterministic models, accumulated uncertainty in multidisciplinary analyses, and distributed, collaborative decision-making.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21757号 / 工博第4574号 / 新制||工||1713(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 西脇 眞二, 教授 髙田 滋, 教授 鈴木 基史 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The complexity in multiscale systems design is significantly greater than in conventional systems because in addition to interactions between components, couplings between physical phenomena and scales are also important. This complexity amplifies two design challenges: a) complexity of coupled simulation models prohibits design space exploration, and b) unavailability of complete simulation models that capture all the interactions. Hence, the challenge in design of multiscale systems lies in managing this complexity and utilizing the available simulation models and information in an efficient manner to support effective decision-making. In order to address this challenge, our primary hypothesis is that the information and computational resources can be utilized in an efficient manner by designing design-processes (meta-design) along with the products. The primary hypothesis is embodied in this dissertation as a framework for integrated design of products and design processes. The framework consists of three components 1) a Robust Multiscale Design Exploration Method (RMS-DEM), 2) information-economics based metrics and methods for simplification of complex design processes and refinement of simulation models, and 3) an information modeling strategy for implementation of the theoretical framework into a computational environment. The framework is validated using the validation-square approach that consists of theoretical and empirical validation. Empirical validation of the framework is carried out using various examples including: pressure vessel design, datacenter cooling system design, linear cellular alloy design, and multifunctional energetic structural materials design. The contributions from this dissertation are categorized in three research domains: a) multiscale design methodology, b) materials design, and c) computer-based support for collaborative, simulation-based multiscale design. In the domain of design methodology, new methods and metrics are developed for integrating the design of products and design processes. The methods and metrics are applied in the field of materials design to develop design-processes and specifications for Multifunctional Energetic Structural Materials. In the domain of computer-based support for design, an information modeling strategy is developed to provide computational support for meta-design. Although the framework is developed in the context of multiscale systems it is equally applicable to design of any other complex system.