40 research outputs found
Quantitative chemical tagging, stellar ages and the chemo-dynamical evolution of the Galactic disc
The early science results from the new generation of high-resolution stellar
spectroscopic surveys, such as GALAH and the Gaia-ESO survey, will represent
major milestones in the quest to chemically tag the Galaxy. Yet this technique
to reconstruct dispersed coeval stellar groups has remained largely untested
until recently. We build on previous work that developed an empirical chemical
tagging probability function, which describes the likelihood that two field
stars are conatal, that is, they were formed in the same cluster environment.
In this work we perform the first ever blind chemical tagging experiment, i.e.,
tagging stars with no known or otherwise discernable associations, on a sample
of 714 disc field stars with a number of high quality high resolution
homogeneous metal abundance measurements. We present evidence that chemical
tagging of field stars does identify coeval groups of stars, yet these groups
may not represent distinct formation sites, e.g. as in dissolved open clusters,
as previously thought. Our results point to several important conclusions,
among them that group finding will be limited strictly to chemical abundance
space, e.g. stellar ages, kinematics, colors, temperature and surface gravity
do not enhance the detectability of groups. We also demonstrate that in
addition to its role in probing the chemical enrichment and kinematic history
of the Galactic disc, chemical tagging represents a powerful new stellar age
determination technique.Comment: 12 pages, 9 figures, accepted for publication in Monthly Notices of
the Royal Astronomical Society (MNRAS
Elemental abundances of intermediate age open cluster NGC 3680
We present a new abundance analysis of the intermediate age Galactic open
cluster NGC 3680, based on high resolution, high signal-to-noise VLT/UVES
spectroscopic data. Several element abundances are presented for this cluster
for the first time, but most notably we derive abundances for the light and
heavy s-process elements Y, Ba, La, and Nd. The serendipitous measurement of
the rare-earth r-process element Gd is also reported. This cluster exhibits a
significant enhancement of Na in giants as compared to dwarfs, which may be a
proxy for an O to Na anti-correlation as observed in Galactic globular clusters
but not open clusters. We also observe a step-like enhancement of heavy
s-process elements towards higher atomic number, contrary to expectations from
AGB nucleosynthesis models, suggesting that the r-process played a significant
role in the generation of both La and Nd in this clusterComment: 8 pages, 6 figures, accepted for publication in MNRA
The Chandra Source Catalog
The Chandra Source Catalog (CSC) is a general purpose virtual X-ray
astrophysics facility that provides access to a carefully selected set of
generally useful quantities for individual X-ray sources, and is designed to
satisfy the needs of a broad-based group of scientists, including those who may
be less familiar with astronomical data analysis in the X-ray regime. The first
release of the CSC includes information about 94,676 distinct X-ray sources
detected in a subset of public ACIS imaging observations from roughly the first
eight years of the Chandra mission. This release of the catalog includes point
and compact sources with observed spatial extents <~ 30''. The catalog (1)
provides access to the best estimates of the X-ray source properties for
detected sources, with good scientific fidelity, and directly supports
scientific analysis using the individual source data; (2) facilitates analysis
of a wide range of statistical properties for classes of X-ray sources; and (3)
provides efficient access to calibrated observational data and ancillary data
products for individual X-ray sources, so that users can perform detailed
further analysis using existing tools. The catalog includes real X-ray sources
detected with flux estimates that are at least 3 times their estimated 1 sigma
uncertainties in at least one energy band, while maintaining the number of
spurious sources at a level of <~ 1 false source per field for a 100 ks
observation. For each detected source, the CSC provides commonly tabulated
quantities, including source position, extent, multi-band fluxes, hardness
ratios, and variability statistics, derived from the observations in which the
source is detected. In addition to these traditional catalog elements, for each
X-ray source the CSC includes an extensive set of file-based data products that
can be manipulated interactively.Comment: To appear in The Astrophysical Journal Supplement Series, 53 pages,
27 figure
Statistical Characterization of the Chandra Source Catalog
The first release of the Chandra Source Catalog (CSC) contains ~95,000 X-ray
sources in a total area of ~0.75% of the entire sky, using data from ~3,900
separate ACIS observations of a multitude of different types of X-ray sources.
In order to maximize the scientific benefit of such a large, heterogeneous
data-set, careful characterization of the statistical properties of the
catalog, i.e., completeness, sensitivity, false source rate, and accuracy of
source properties, is required. Characterization efforts of other, large
Chandra catalogs, such as the ChaMP Point Source Catalog (Kim et al. 2007) or
the 2 Mega-second Deep Field Surveys (Alexander et al. 2003), while
informative, cannot serve this purpose, since the CSC analysis procedures are
significantly different and the range of allowable data is much less
restrictive. We describe here the characterization process for the CSC. This
process includes both a comparison of real CSC results with those of other,
deeper Chandra catalogs of the same targets and extensive simulations of
blank-sky and point source populations.Comment: To be published in the Astrophysical Journal Supplement Series (Fig.
52 replaced with a version which astro-ph can convert to PDF without issues.
A new design for friction stir spot joining of Al alloys and carbon fibre reinforced composites
Friction stir spot welding (FSSW) has been recently developed to join dissimilar materials. However, the traditional requirement for a rotating tool consists of a pin and shoulder in FSSW leads to a complex joining process and unpredictable defects. In this study, a new static-shoulder design in FSSW was proposed and developed to join Al alloys to carbon fiber-reinforced polymer (CFRP) composites. The main joining parameters, including pin rotational speed, pin feed rate and pin plunge depth, were varied to investigate their effects on the joining temperature, materials interaction and the strength of joints. The pin rotational speed had the largest influence on the joining temperature. Lap shear tensile testing was conducted to evaluate the performance of the joints. The joints exhibited the ultimate lap shear force from 230 to 260 N. A brittle fracture occurred with the displacement-at-fracture load of 0.35-0.41 mm. Cross-sectional images revealed the creation of undulations on the surface of Al alloys in the joining zone. The undulations created a macro-mechanical interlocking bonding between the materials, which determined the performance of the joints. For a flat pin, by increasing the plunge depth from 1.25 to 1.30 mm, the undulation size increased from 0.21 to 0.26 mm, which can enhance the macro-mechanical interlocking bonding between Al alloys and CFRP and accordingly increased the ultimate shear force of the joints from 230 to 241 N. Use of a fluted pin significantly influenced the flow of the plasticized Al alloy which created pronounced undulations and large Al alloy spikes of 0.46 mm. These features seemed to establish an efficient macro-mechanical interlocking bonding, which resulted in a noticeable improvement in the performance of the joint. For a plunge depth of 1.30 mm, the ultimate shear force increased to 261 N using the fluted pin
Quantifying chemical tagging : towards robust group finding in the Galaxy
The first generation of large-scale chemical tagging surveys, in particular the High Efficiency and Resolution Multi-Element Spectrograph (HERMES)/Galactic Archaeology with HERMES million star survey, promises to vastly expand our understanding of the chemical and dynamical evolution of the Galaxy. This, however, is contingent on our ability to confidently perform chemical tagging on such a large data set. Chemical homogeneity has been observed across a range of elements within several Galactic open clusters, yet the level to which this is the case globally, and particularly in comparison to the scatter across clusters themselves, is not well understood. The patterns of elements in coeval cluster members, occupying a complex chemical abundance space, are rooted in the evolution, ultimately the nature of the very late stages, of early generations of stars. The current astrophysical models of such stages are not yet sufficient to explain all observations, combining with our significant gaps in the understanding of star formation, makes this a difficult arena to tackle theoretically. Here, we describe a robust pair-wise metric used to gauge the chemical difference between two stellar components. This metric is then applied to a data base of high-resolution literature abundance sources to derive a function describing the probability that two stars are of common evolutionary origin. With this cluster probability function, it will be possible to report a confidence, grounded in empirical observational evidence, with which clusters are detected, independent of the group finding methods. This formulation is also used to probe the role of chemical dimensionality, and that of individual chemical species, on the ability of chemical tagging to differentiate coeval groups of stars.12 page(s
A framework for ontology-based temporal modelling of business intelligence
Ontologies provide the means for supporting business intelligence (BI) and information management through the interpretation of unstructured content. On the basis of the semantics of ontologies, information can be extracted from natural language texts, and on a further level of processing knowledge that facilitates BI can be discovered. However, in order to act this way, ontologies need to be properly modelled and evolved so that they are constantly aligned with changes that occur in the real world. This paper presents a framework for modelling the temporal aspects of a semantic knowledge base with direct impact on the BI process