Attitude control system for sounding rockets Patent

Development of attitude control system for sounding rocket stabilization during ballistic phase of fligh

Towards Handling Uncertainty in Prognostic Scenarios: Advanced Learning from the Past

Das Forschungsprogramm „Earth System Sciences (ESS)“, ein Programm des Bundesministeriums für Wissenschaft, Forschung und Wirtschaft (BMWFW), durchgeführt von der ÖAW, hat die Erforschung des Systems Erde zum Ziel. Im Rahmen von Ausschreibungen werden wissenschaftliche Forschungsprojekte gefördert, die dem neusten Stand der Wissenschaft entsprechen. Das Programm ESS sieht es als seine Aufgabe, Lücken in der österreichischen Förderungslandschaft zu schließen. Dies bezieht sich etwa auf interdisziplinäre Projekte, Projekte zur Langzeitforschung sowie auf Projekte, die auf derzeit noch gering beforschte Bereiche fokussiert sind und denen wissenschaftlich

Dynamic behavior of domain walls in double layer self-biasing bubble garnet films

Radial expansion of bubbles and gradient bubble propagation experiments were conducted in a double layer garnet film with perpendicular anisotropy in both layers. Implanted and as-grown samples are compared. In radial expansion the side walls of the bubble exhibit a linear mobility much lower than calculated from γΔ/α. Saturation occurs at high drives (35 Oe). At drives above 50 Oe the saturation velocity of 27 m/s occurs only in the first 120 ns of the motion. After that the velocity drops to 17.5 m/s still independent of drive. This break in velocity does not occur in implanted samples, where the saturation velocity depends on implantation conditions. In gradient propagation saturation occurs at fields an order of magnitude smaller. The saturation velocity is independent of implantation, but overshoot depends strongly on it. No creep was detected. The 180° head-on domain wall between the two layers is found to have little effect on the dynamics of the side walls of the bubble. The motion of the head-on wall is also investigated and its velocity estimated. This head-on wall exhibits a linear mobility and a saturation velocity at high drives

Fossils as Key Resources of Hydrocarbons for the Chemical Industry - The Burning Problem of Industrial Development

Intensive research is being pursued world-wide to establish a methodology for industrial development. Many types of changes play an important role in the dynamics of the industrial structure in both large and small economies. The global energy supply and future substitution of crude oil are among the most important and widely investigated constraints. With the existing patterns of production and development strongly determined by the specific conditions in a given region, the development of various raw materials for the chemical industry is of great importance. The impact of changing production methods in feedstock hydrocarbons on industrial development requires further intensive research. A non-uniform demand vector and a variety of possible production processes, with a constrained supply of resources in different economic regions and countries, open a number of possibilities for new and non-conventional solutions. Further, hydrocarbon synthesis for the chemical industry should be a high priority research goal, not only because of the scale of demand, but because of the properties of the substances themselves. Provided the problem of production of hydrocarbon feedstock for the chemical industry can be solved successfully, the same methodology could also be used for the analysis of synfuel production: It would contribute to a better understanding of the dynamics of the industrial structure

Towards Handling Uncertainty in Prognostic Scenarios: Advanced Learning from the Past

In this report we introduce the paradigm of learning from the past which is realized in a controlled prognostic context. It is a data-driven exploratory approach to assessing the limits to credibility of any expectations about the system’s future behavior which are based on a time series of a historical observations of the analyzed system. This horizon of the credible expectations is derived as the length of explainable outreach of the data, that is, the spatio-temporal extent which, in lieu of the knowledge contained in the historical observations, we are justified in believing contains the system’s future observations. Explainable outreach is of practical interest to stakeholders since it allows them to assess the credibility of scenarios produced by models of the analyzed system. It also indicates the scale of measures required to overcome the system’s inertia. In this report we propose a method of learning in a controlled prognostic context which is based on a polynomial regression technique. A polynomial regression model is used to understand the system’s dynamics, revealed by the sample of historical observations, while the explainable outreach is constructed around the extrapolated regression function. The proposed learning method was tested on various sets of synthetic data in order to identify its strengths and weaknesses, and formulate guidelines for its practical application. We also demonstrate how it can be used in context of earth system sciences by using it to derive the explainable outreach of historical anthropogenic CO2 emissions and atmospheric CO2 concentrations. We conclude that the most robust method of building the explainable outreach is based on linear regression. However, the explainable outreach of the analyzed datasets (representing credible expectations based on extrapolation of the linear trend) is rather short

Alternative Routes from Fossil Resources to Chemical Feedstocks

The chemical industry depends very heavily on hydrocarbon feedstocks, which are presently derived almost exclusively from crude oil. Although only about seven percent of the hydrocarbons suitable for chemical processing are actually used in this way, it is already clear that there is a potential conflict between the needs of the energy sector and those of the chemical industry: they are competing for increasingly scarce liquid hydrocarbon resources. The authors suggest that the supply of hydrocarbon feedstocks to the chemical industry could be protected against the effects of changing patterns of energy use by modifying the underlying industrial structure. They have developed an approach which takes a variety of production processes (either in use or under development), compares their efficiency their consumption of different resources, etc., and finds the combination of technologies that best satisfies a particular demand while staying within the limits imposed by resource availability. This approach uses the techniques of interactive decision analysis to incorporate the unquantifiable social and political factors that must influence any development decision. By way of illustration, the method is applied to one very small part of the problem area: the different routes to the production of methanol. This report does not attempt to provide any final answer to the problem of feedstock supply, but rather to explain one possible approach to the problem and discuss some intermediate results. It is addressed not only to researchers, but also, and in particular, to all decision makers and industrial consultants facing problems of this type

Taking advantage of the UNFCCC Kyoto Policy Process: What can we learn about learning?

Learning is difficult to anticipate when it happen instantaneously, e.g. in the context of innovations [2]. However, even if learning is anticipated to happen continuously, it is difficult to grasp, e.g. when it occurs outside well-defined lab conditions, because adequate monitoring had not been put in place. Our study is retrospective. It focuses on the emissions of greenhouse gases (GHGs)that had been reported by countries (Parties) under the Kyoto Protocol (KP) to the United Nations Framework on Climate Change (UNFCCC). Discussions range widely on (i) whether the KP is considered a failure [6] or a success [5] ; and (ii) whether international climate policy should transit from a centralized model of governance to a 'hybrid' decentralized approach that combines country-level mitigation pledges with common principles for accounting and monitoring [1] . Emissions of GHGs - in the following we refer to CO2 emissions from burning fossil fuels at country level, particularly in the case of Austria - provide a perfect means to study learning in a globally relevant context. We are not aware of a similar data treasure of global relevance. Our mode of grasping learning is novel, i.e. it may have been referred to in general but, to the best of our knowledge, had not been quantifed so far. (That is, we consider the KP a success story potentially and advocate for the hybrid decentralized approach.) Learning requires 'measuring' differences or deviations. Here we follow Marland et al. [3] who discuss this issue in the context of emissions accounting: 'Many of the countries and organizations that make estimates of CO2 emissions provide annual updates in which they add another year of data to the time series and revise the estimates for earlier years. Revisions may reflect revised or more complete energy data and ... more complete and detailed understanding of the emissions processes and emissions coefficients. In short, we expect revisions to reflect learning and a convergence toward more complete and accurate estimates.' The United Nations Framework Convention on Climate Change (UNFCCC)requires exactly this to be done. Each year UNFCCC signatory countries are obliged to provide an annual inventory of emissions (and removals) of specified GHGs from five sectors (energy; industrial processes and product use; agriculture; land use, land use change and forestry; and waste) and revisit the emissions (and removals) for all previous years, back to the country specified base years (or periods). These data are made available by means of a database [4]. The time series of revised emission estimates reflect learning, but they are 'contaminated' by (i) structural change (e.g., when a coal-power plant is substituted by a gas-power plant); (ii) changes in consumption; and, rare but possible, (iii)methodological changes in surveying emission related activities. De-trending time series of revised emission estimates allows this contamination to be isolated by country, for which we provide three approaches: (I) parametric approach employing polynomial trend; (II) non-parametric approach employing smoothing splines; and (III) approach in which the most recent estimate is used as trend. That is, after de-trending for each year we are left with a set of revisions that reflect 'pure'(uncontaminated) learning which, is expected to be independent of the year under consideration (i.e., identical from year to year). However, we are confronted with two non-negligible problems (P): (P.1) the problem of small numbers - the remaining differences in emissions are small (before and after de-trending); and (P.2) the problem of non-monotonic learning - our knowledge of emission-generating activities and emission factors may not become more accurate from revision to revision