Homologous flare–CME events and their metric type II radio burst association

Active region NOAA 11158 produced many flares during its disk passage. At least two of these flares can be considered as homologous: the C6.6 flare at 06:51 UT and C9.4 flare at 12:41 UT on February 14, 2011. Both flares occurred at the same location (eastern edge of the active region) and have a similar decay of the GOES soft X-ray light curve. The associated coronal mass ejections (CMEs) were slow (334 and 337 km/s) and of similar apparent widths (43° and 44°), but they had different radio signatures. The second event was associated with a metric type II burst while the first one was not. The COR1 coronagraphs on board the STEREO spacecraft clearly show that the second CME propagated into the preceding CME that occurred 50 min before. These observations suggest that CME–CME interaction might be a key process in exciting the type II radio emission by slow CMEs.     

The Spacelab-Mir-1 "Greenhouse-2" experiment.

The Spacelab-Mir-1 (SLM-1) mission is the first docking of the Space Shuttle Atlantis (STS-71) with the Orbital Station Mir in June 1995. The SLM-1 "Greenhouse-2" experiment will utilize the Russian-Bulgarian-developed plant growth unit (Svet). "Greenhouse-2" will include two plantings (1) designed to test the capability of Svet to grow a crop of Superdwarf wheat from seed to seed, and (2) to provide green plant material for post-flight analysis. Protocols, procedures, and equipment for the experiment have been developed by the US-Russian science team. "Greenhouse-2" will also provide the first orbital test of a new Svet Instrumentation System (SIS) developed by Utah State University to provide near real time data on plant environmental parameters and gas-exchange rates. SIS supplements the Svet control and monitoring system with additional sensors for substrate moisture, air temperature, IR leaf temperature, light, oxygen, pressure, humidity, and carbon-dioxide. SIS provides the capability to monitor canopy transpiration and net assimilation of the plants growing in each vegetation unit (root zone) by enclosing the canopy in separate, retractable, ventilated leaf chambers. Six times during the seed-to-seed experiment, plant samples will be collected, leaf area measured, and plant parts fixed and/or dried for ground analysis. A second planting initiated 30 days before the arrival of a U.S. Shuttle [originally planned to be STS-71] is designed to provide green material at the vegetative development stage for ground analysis. [As this paper is being edited, the experiment has been delayed until after the arrival of STS-71.]     

Landsat satellite imagery of the Qattara Depression area,Egypt

The Qattara Depression lies in the northern part of the Western Desert of Egypt at a distance of some tens of kilometers to the south of the Mediterranean Sea Coast. The depression in question is the largest one in the great Sahara extending across North Africa. It covers an area of some 19,000 km² at ? 60 m level and the absolute level of its lowest point is about ? 134 m. The depression extends for about 300 km in a roughly ENE-WSW direction, while its width is variable reaching to a maximum of about 145 km. Feasibility studies are currently carried out for the Qattara solar-hydro-electric project which aims at generating hydro-electric power by the drop of the Mediterranean Sea water into the depression after passing through a canal/tunnel system. Peak load electric power may be also generated by raising the water to the small hollow of Deir Kirayim, situated at a higher level near the depression, and allowing it to drop to a low level.For the purpose of assessing the regional criteria involved in the implementation of the project and the environmental impact of such implementation, the Qattara Depression and the surrounding area has been studied on a regional scale by the utilization of LANDSAT satellite imagery. The maps produced by the interpretation of the images in question include those of the geological and environmental units, structural lineations, drainage and vegetation cover. Lineation density and drainage density maps are derived by the computation of the structural lineation and drainage maps respectively. A map of groundwater conditions is worked out on the basis of the image interpretation, and the observations previously carried out on the groundwater aquifers in the Qattara Depression and the surrounding area. LANDSAT satellite image interpretation and computation are supported by intensive observations carried out in the field as well as chemical, petrological and mineralogical analyses of the samples collected.The LANDSAT satellite images proved to be of great importance in mapping the Qattara Depression floor which is hardly accessible to classical mapping, and especially in view of the large area which could be covered by imagery mapping in a reasonably short time compatible with the duration of the feasibility study. The special characters of the spaceborne multispectral imagery have been paramount in deciphering the major regional features of the investigated area.The overall synoptic picture of the regional setting of the geological and environmental units, faults, fractures and folds, drainage lines and plant cover in the large area studied has been clarified for the first time. It has been demonstrated that the Qattara Depression is actually constituted of several small depressions. The environmental impact of the project implementation has been visualized especially regarding the possible influence of the saline water on the fresh groundwater sources. The thick salt accumulation in the depression has been found to be of such extension as to increase the salinity of the Mediterranean Sea water stored in the depression following the implementation of the project. The lineation density map has been particularly of great help in the localization of sites subjected to intense crustal deformation, greater slope instability and run off surface water flooding.     

Data fusion of decentralized local tracker outputs

An approach for fusing offboard track-level data at a central fusion node is presented. The case where the offboard tracker continues to update its local track estimate with measurement and system dynamics models that are not necessarily linear is considered. An algorithm is developed to perform this fusion at a central node without having access to the offboard measurements, their noise statistics, or the location of the local estimator. The algorithm is based on an extension of results that were originally established for linear offboard trackers. A second goal of this work is to develop an inequality constraint for selecting the proper sampling interval for the incoming state estimates to the fusion node. This interval is selected to allow use of conventional Kalman filter algorithms at the fusion node without suffering error performance degradation due to processing a correlated sequence of track state estimates     

Exploiting GNSS signal structure to enhance observability

There are a number of different error sources, such as multipath and thermal noise, which corrupt satellite navigation waveforms from their theoretical structure. However, even under ideal conditions the broadcast signals have some degree of deformation as a result of the practical individual hardware implementation. For the most demanding users of satellite navigation, such as aircraft navigation and landing systems, it is important to characterize the nominal signal structure in order to detect minimal variations resulting from hardware-based errors. Thus far such precorrelation Global Navigation Satellite System (GNSS) signal quality monitoring has been performed through high gain antennas, which allow for raising the GNSS spectrum above the thermal noise floor and observing the structure of the signal directly at the front end output. This paper describes a new approach to achieve such observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal. The paper presents how these techniques can drastically improve the signal-to-noise ratio (SNR) in postprocessing, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas. Results are predicted using the appropriate theory and validated using data collected from the Global Positioning System (GPS).     

Power management and distribution system for a more-electricaircraft (MADMEL)

A five-phase Power Management and Distribution System for a More-Electric Aircraft (MADMEL) program was awarded by the Air Force to Northrop/Grumman Military Aircraft Division in September 1991. The objective of the program is to design, develop, and demonstrate an advanced electrical power generation and distribution system for a More-Electric Aircraft (MEA). The MEA emphasizes the use of electrical power in place of hydraulics, pneumatic, and mechanical power to optimize the performance and life cycle cost of the aircraft. This paper presents an overview of the MADMEL program and a top-level summary of the program results, development and test of major components to date. In Phase I and Phase II studies, the electrical load requirements were established and the electrical power system architecture was defined for both near-term (NT-year 1996) and far-term (FT-year 2003) MEA application. The detailed design and specification for the Electrical Power System (EPS), its interface with the Vehicle Management System, and the test set-up were developed under Phase III. Phase IV, fabrication and testing of the subsystem level hardware, has been completed. Overall system level integration and testing, Phase V, is scheduled to be completed by September 1999