Dispersion analysis for baseline reference mission 3A with 400,000 foot entry interface altitude

A dispersion analysis considering 3 beta uncertainties in platform, vehicle, and environmental parameters is described. Powered explicit guidance used to develop closed loop steering commands, the nominal profile, and entry interface conditions are discussed. The groundrules and assumptions for the analysis are reviewed. The results presented include dispersion data at specific time slices from liftoff to entry interface, covariance matrices, summary data, and exchange ratios

Dispersion analysis for baseline reference mission 2

A dispersion analysis considering uncertainties (or perturbations) in platform, vehicle, and environmental parameters was performed for baseline reference mission (BRM) 2. The dispersion analysis is based on the nominal trajectory for BRM 2. The analysis was performed to determine state vector and performance dispersions (or variations) which result from the indicated uncertainties. The dispersions are determined at major mission events and fixed times from liftoff (time slices). The dispersion results will be used to evaluate the capability of the vehicle to perform the mission within a specified level of confidence and to determine flight performance reserves

Space shuttle engineering and operations support: Dispersion analysis for the first orbital flight test (OFT-1) mission

A dispersion analysis considering 3-sigma uncertainties (or perturbations) in platform, vehicle, and environmental parameters was performed for the first orbital flight test (OFT-1) mission. The dispersion analysis is based on the nominal trajectory for the OFT-1 reference flight profile. The analysis was performed to determine state vector and performance dispersions (or variations) which result from the indicated 3-sigma uncertainties. The dispersions are determined at major mission events and fixed times from liftoff (time slices). The dispersion results are used to evaluate the capability of the vehicle to perform the mission within a 3-sigma level of confidence and to determine flight performance reserves

Ultraviolet properties of IRAS-selected Be stars

New IUE observations were obtained of 35 Be stars from a list of stars which show excess infrared fluxes in IRAS data. The IRAS-selected Be stars show larger C IV and Si IV equivalent widths than other Be stars. Excess C IV and Si IV absorption seems to be independent of spectral type for IRAS-selected Be stars later than spectral type B4. This is interpreted as evidence for a possible second mechanism acting in conjunction with radiation pressure for producing the winds in Be stars. No clear correlation of IR excess of v sin i with C IV or Si IV equivalent widths is seen, although a threshold for the occurrence of excess C IV and Si IV absorption appears at a v sin i of 150 km/sec

Dispersion analysis techniques within the space vehicle dynamics simulation program

The Space Vehicle Dynamics Simulation (SVDS) program was evaluated as a dispersion analysis tool. The Linear Error Analysis (LEA) post processor was examined in detail and simulation techniques relative to conducting a dispersion analysis using the SVDS were considered. The LEA processor is a tool for correlating trajectory dispersion data developed by simulating 3 sigma uncertainties as single error source cases. The processor combines trajectory and performance deviations by a root-sum-square (RSS process) and develops a covariance matrix for the deviations. Results are used in dispersion analyses for the baseline reference and orbiter flight test missions. As a part of this study, LEA results were verified as follows: (A) Hand calculating the RSS data and the elements of the covariance matrix for comparison with the LEA processor computed data. (B) Comparing results with previous error analyses. The LEA comparisons and verification are made at main engine cutoff (MECO)

New Insights on Interstellar Gas-Phase Iron

In this paper, we report on the gas-phase abundance of singly-ionized iron (Fe II) for 51 lines of sight, using data from the Far Ultraviolet Spectroscopic Explorer (FUSE). Fe II column densities are derived by measuring the equivalent widths of several ultraviolet absorption lines and subsequently fitting those to a curve of growth. Our derivation of Fe II column densities and abundances creates the largest sample of iron abundances in moderately- to highly-reddened lines of sight explored with FUSE, lines of sight that are on average more reddened than lines of sight in previous Copernicus studies. We present three major results. First, we observe the well-established correlation between iron depletion and and also find trends between iron depletion and other line of sight parameters (e.g. f(H_2), E_(B-V), and A_V), and examine the significance of these trends. Of note, a few of our lines of sight probe larger densities than previously explored and we do not see significantly enhanced depletion effects. Second, we present two detections of an extremely weak Fe II line at 1901.773 A in the archival STIS spectra of two lines of sight (HD 24534 and HD 93222). We compare these detections to the column densities derived through FUSE spectra and comment on the line's f-value and utility for future studies of Fe II. Lastly, we present strong anecdotal evidence that the Fe II f-values derived empirically through FUSE data are more accurate than previous values that have been theoretically calculated, with the probable exception of f_1112.Comment: Accepted for publication in ApJ, 669, 378; see ApJ version for small updates. 53 total pages (preprint format), 7 tables, 11 figure

A search for diffuse band profile variations in the rho Ophiuchi cloud

High signal-to-noise profiles of the broad diffuse interstellar band at 4430 A were obtained on the 2.2-m telescope at the Mauna Kea Observatory, using the newly-developed pulse-counting multi-anode microchannel array detector system in an effort to determine whether the band profile varies with mean grain size as expected if the band is produced by absorbers embedded in grain lattices. The lack of profile variability over several lines of sight where independent evidence indicates that the mean grain size varies shows that lambda 4430 is probably not formed by the same grains that are responsible for interstellar extinction at visible wavelengths. The possibility that this band is created by a population of very small ( approximately 100 A) grains is still viable, as is the hypothesis that it has a molecular origin

Making sense: talking data management with researchers

Incremental is one of eight projects in the JISC Managing Research Data programme funded to identify institutional requirements for digital research data management and pilot relevant infrastructure. Our findings concur with those of other Managing Research Data projects, as well as with several previous studies. We found that many researchers: (i) organise their data in an ad hoc fashion, posing difficulties with retrieval and re-use; (ii) store their data on all kinds of media without always considering security and back-up; (iii) are positive about data sharing in principle though reluctant in practice; (iv) believe back-up is equivalent to preservation. <br></br><br></br> The key difference between our approach and that of other Managing Research Data projects is the type of infrastructure we are piloting. While the majority of these projects focus on developing technical solutions, we are focusing on the need for ‘soft’ infrastructure, such as one-to-one tailored support, training, and easy-to-find, concise guidance that breaks down some of the barriers information professionals have unintentionally built with their use of specialist terminology. <br></br><br></br> We are employing a bottom-up approach as we feel that to support the step-by-step development of sound research data management practices, you must first understand researchers’ needs and perspectives. Over the life of the project, Incremental staff will act as mediators, assisting researchers and local support staff to understand the data management requirements within which they are expect to work, and will determine how these can be addressed within research workflows and the existing technical infrastructure. <br></br> <br></br> Our primary goal is to build data management capacity within the Universities of Cambridge and Glasgow by raising awareness of basic principles so everyone can manage their data to a certain extent. We will ensure our lessons can be picked up and used by other institutions. Our affiliation with the Digital Curation Centre and Digital Preservation Coalition will assist in this and all outputs will be released under a Creative Commons licence. The key difference between our approach and that of other MRD projects is the type of ‘infrastructure’ we are piloting. While the majority of these projects focus on developing technical solutions, we are focusing on the need for ‘soft’ infrastructure, such as one-to-one tailored support, training, and easy-to-find, concise guidance that breaks down some of the barriers information professionals have unintentionally built with their use of specialist terminology. We are employing a bottom-up approach as we feel that to support the step-by-step development of sound research data management practices, you must first understand researchers’ needs and perspectives. Over the life of the project, Incremental staff will act as mediators, assisting researchers and local support staff to understand the data management requirements within which they are expect to work, and will determine how these can be addressed within research workflows and the existing technical infrastructure. Our primary goal is to build data management capacity within the Universities of Cambridge and Glasgow by raising awareness of basic principles so everyone can manage their data to a certain extent. We’re achieving this by: - re-positioning existing guidance so researchers can locate the advice they need; - connecting researchers with one-to-one advice, support and partnering; - offering practical training and a seminar series to address key data management topics. We will ensure our lessons can be picked up and used by other institutions. Our affiliation with the Digital Curation Centre and Digital Preservation Coalition will assist in this and all outputs will be released under a Creative Commons licence