2,466 research outputs found

    N plus 3 Advanced Concept Studies for Supersonic Commercial Transport Aircraft Entering Service in the 2030-2035 Period

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    Boeing, with Pratt & Whitney, General Electric, Rolls-Royce, M4 Engineering, Wyle Laboratories and Georgia Institute of Technology, conducted a study of supersonic commercial aircraft concepts and enabling technologies for the year 2030-2035 timeframe. The work defined the market and environmental/regulatory conditions that could evolve by the 2030/35 time period, from which vehicle performance goals were derived. Relevant vehicle concepts and technologies are identified that are anticipated to meet these performance and environmental goals. A series of multidisciplinary analyses trade studies considering vehicle sizing, mission performance and environmental conformity determined the appropriate concepts. Combinations of enabling technologies and the required technology performance levels needed to meet the desired goals were identified. Several high priority technologies are described in detail, including roadmaps with risk assessments that outline objectives, key technology challenges, detailed tasks and schedules and demonstrations that need to be performed. A representative configuration is provided for reference purposes, along with associated performance estimates based on these key technologies

    2020 NASA Technology Taxonomy

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    This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

    Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

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    Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion

    NASA Strategic Roadmap Summary Report

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    In response to the Vision, NASA commissioned strategic and capability roadmap teams to develop the pathways for turning the Vision into a reality. The strategic roadmaps were derived from the Vision for Space Exploration and the Aldrich Commission Report dated June 2004. NASA identified 12 strategic areas for roadmapping. The Agency added a thirteenth area on nuclear systems because the topic affects the entire program portfolio. To ensure long-term public visibility and engagement, NASA established a committee for each of the 13 areas. These committees - made up of prominent members of the scientific and aerospace industry communities and senior government personnel - worked under the Federal Advisory Committee Act. A committee was formed for each of the following program areas: 1) Robotic and Human Lunar Exploration; 2) Robotic and Human Exploration of Mars; 3) Solar System Exploration; 4) Search for Earth-Like Planets; 5) Exploration Transportation System; 6) International Space Station; 7) Space Shuttle; 8) Universe Exploration; 9) Earth Science and Applications from Space; 10) Sun-Solar System Connection; 11) Aeronautical Technologies; 12) Education; 13) Nuclear Systems. This document contains roadmap summaries for 10 of these 13 program areas; The International Space Station, Space Shuttle, and Education are excluded. The completed roadmaps for the following committees: Robotic and Human Exploration of Mars; Solar System Exploration; Search for Earth-Like Planets; Universe Exploration; Earth Science and Applications from Space; Sun-Solar System Connection are collected in a separate Strategic Roadmaps volume. This document contains memebership rosters and charters for all 13 committees

    Sustainable Design of Industrial Energy Supply Systems - Development of a model-based decision support framework

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    Energy and media supply systems and related infrastructure at industrial sites have grown historically and is largely dependent on the use of fossil fuels. High fuel prices and the emission reduction targets of companies challenge existing supply concepts. Supply concepts usually remain in place for decades due to the long-lived nature of generation technologies and distribution systems. Today's investment decisions are therefore confronted with a changing environment in which the share of volatile renewables from solar and wind is continuously increasing. The long planning horizons make design decisions very complex. Optimization-based design approaches automatically derive cost- or carbon-optimal selections of generation technologies and procurement tariffs. Thus, they enable faster and more accurate planning decisions in techno-economic feasibility studies. In this work, a novel optimization model for techno-economic feasibility studies in industrial sites is developed. The optimization model uses a generic technology formulation with base classes, which takes into account the large variety of technologies and procurement tariffs at industrial sites. The optimization model also includes two reserve concepts: an operating reserve concept for short-term disruptions and a redundancy concept for long-term plant failures. The two concepts ensure security of supply for production-related energy requirements and thereby contributes to avoidance of costly production outages. The optimization model is integrated into an optimization framework to effectively calculate decarbonization strategies. The framework uses time series aggregation and heuristic decomposition techniques. Time series aggregation is performed by an integer program and results in a robust selection of representative days. The selection of representative days is used in a multi-year planning model to derive transformation roadmaps. Transformation roadmaps analyze the evolution of energy supply systems to long-term trends and consider adaptive investment decisions. A transformation strategy with myopic foresight (MYOP) solves the multi-year planning problem sequentially and is solved up to 98 % faster than a transformation approach with perfect foresight (PERF). The high uncertainties in early planning phases and the resulting need for detailed sensitivity analysis make this approach the preferred choice for many feasibility studies. The newly developed optimization framework is used in numerous research and consulting projects for urban districts, microgrids and factories. In this work, the capabilities of the framework are demonstrated for three use cases (automotive, pharmaceutical, dairy) of factory sites in southern Germany. In the use cases, decarbonization strategies for electricity, steam, heating and cooling supply are analyzed. Simulation evaluations identify changing operating patterns of combined heat and power (CHP) plants along the 15-year planning horizon. In addition, electrification of heating demand leads to a significant increase of total electricity demands. The results derived with the framework provide decision makers in industrial companies a clear view of the long-term impact of their investment decisions on decarbonization strategies

    UNDERSTANDING USER PERCEPTIONS AND PREFERENCES FOR MASS-MARKET INFORMATION SYSTEMS – LEVERAGING MARKET RESEARCH TECHNIQUES AND EXAMPLES IN PRIVACY-AWARE DESIGN

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    With cloud and mobile computing, a new category of software products emerges as mass-market information systems (IS) that addresses distributed and heterogeneous end-users. Understanding user requirements and the factors that drive user adoption are crucial for successful design of such systems. IS research has suggested several theories and models to explain user adoption and intentions to use, among them the IS Success Model and the Technology Acceptance Model (TAM). Although these approaches contribute to theoretical understanding of the adoption and use of IS in mass-markets, they are criticized for not being able to drive actionable insights on IS design as they consider the IT artifact as a black-box (i.e., they do not sufficiently address the system internal characteristics). We argue that IS needs to embrace market research techniques to understand and empirically assess user preferences and perceptions in order to integrate the "voice of the customer" in a mass-market scenario. More specifically, conjoint analysis (CA), from market research, can add user preference measurements for designing high-utility IS. CA has gained popularity in IS research, however little guidance is provided for its application in the domain. We aim at supporting the design of mass-market IS by establishing a reliable understanding of consumer’s preferences for multiple factors combing functional, non-functional and economic aspects. The results include a “Framework for Conjoint Analysis Studies in IS” and methodological guidance for applying CA. We apply our findings to the privacy-aware design of mass-market IS and evaluate their implications on user adoption. We contribute to both academia and practice. For academia, we contribute to a more nuanced conceptualization of the IT artifact (i.e., system) through a feature-oriented lens and a preference-based approach. We provide methodological guidelines that support researchers in studying user perceptions and preferences for design variations and extending that to adoption. Moreover, the empirical studies for privacy- aware design contribute to a better understanding of the domain specific applications of CA for IS design and evaluation with a nuanced assessment of user preferences for privacy-preserving features. For practice, we propose guidelines for integrating the voice of the customer for successful IS design. -- Les technologies cloud et mobiles ont fait Ă©merger une nouvelle catĂ©gorie de produits informatiques qui s’adressent Ă  des utilisateurs hĂ©tĂ©rogĂšnes par le biais de systĂšmes d'information (SI) distribuĂ©s. Les termes “SI de masse” sont employĂ©s pour dĂ©signer ces nouveaux systĂšmes. Une conception rĂ©ussie de ceux-ci passe par une phase essentielle de comprĂ©hension des besoins et des facteurs d'adoption des utilisateurs. Pour ce faire, la recherche en SI suggĂšre plusieurs thĂ©ories et modĂšles tels que le “IS Success Model” et le “Technology Acceptance Model”. Bien que ces approches contribuent Ă  la comprĂ©hension thĂ©orique de l'adoption et de l'utilisation des SI de masse, elles sont critiquĂ©es pour ne pas ĂȘtre en mesure de fournir des informations exploitables sur la conception de SI car elles considĂšrent l'artefact informatique comme une boĂźte noire. En d’autres termes, ces approches ne traitent pas suffisamment des caractĂ©ristiques internes du systĂšme. Nous soutenons que la recherche en SI doit adopter des techniques d'Ă©tude de marchĂ© afin de mieux intĂ©grer les exigences du client (“Voice of Customer”) dans un scĂ©nario de marchĂ© de masse. Plus prĂ©cisĂ©ment, l'analyse conjointe (AC), issue de la recherche sur les consommateurs, peut contribuer au dĂ©veloppement de systĂšme SI Ă  forte valeur d'usage. Si l’AC a gagnĂ© en popularitĂ© au sein de la recherche en SI, des recommandations quant Ă  son utilisation dans ce domaine restent rares. Nous entendons soutenir la conception de SI de masse en facilitant une identification fiable des prĂ©fĂ©rences des consommateurs sur de multiples facteurs combinant des aspects fonctionnels, non-fonctionnels et Ă©conomiques. Les rĂ©sultats comprennent un “Cadre de rĂ©fĂ©rence pour les Ă©tudes d'analyse conjointe en SI” et des recommandations mĂ©thodologiques pour l'application de l’AC. Nous avons utilisĂ© ces contributions pour concevoir un SI de masse particuliĂšrement sensible au respect de la vie privĂ©e des utilisateurs et nous avons Ă©valuĂ© l’impact de nos recherches sur l'adoption de ce systĂšme par ses utilisateurs. Ainsi, notre travail contribue tant Ă  la thĂ©orie qu’à la pratique des SI. Pour le monde universitaire, nous contribuons en proposant une conceptualisation plus nuancĂ©e de l'artefact informatique (c'est-Ă -dire du systĂšme) Ă  travers le prisme des fonctionnalitĂ©s et par une approche basĂ©e sur les prĂ©fĂ©rences utilisateurs. Par ailleurs, les chercheurs peuvent Ă©galement s'appuyer sur nos directives mĂ©thodologiques pour Ă©tudier les perceptions et les prĂ©fĂ©rences des utilisateurs pour diffĂ©rentes variations de conception et Ă©tendre cela Ă  l'adoption. De plus, nos Ă©tudes empiriques sur la conception d’un SI de masse sensible au respect de la vie privĂ©e des utilisateurs contribuent Ă  une meilleure comprĂ©hension de l’application des techniques CA dans ce domaine spĂ©cifique. Nos Ă©tudes incluent notamment une Ă©valuation nuancĂ©e des prĂ©fĂ©rences des utilisateurs sur des fonctionnalitĂ©s de protection de la vie privĂ©e. Pour les praticiens, nous proposons des lignes directrices qui permettent d’intĂ©grer les exigences des clients afin de concevoir un SI rĂ©ussi
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