A model to predict land susceptibility to wind erosion in western Queensland,Australia

This paper describes the development and validation of the Australian Land Erodibility Model (AUSLEM), designed to predict land susceptibility to wind erosion in western Queensland, Australia. The model operates at a 5 × 5 km spatial resolution on a daily time-step with inputs of grass and tree cover, soil moisture, soil texture and surficial stone cover. The system was implemented to predict land erodibility, i.e. susceptibility to wind erosion, for the period 1980–1990. Model performance was evaluated using cross-correlation analyses to compare trajectories of mean annual land erodibility at selected locations with trends in wind speed and observational records of dust events and a Dust Storm Index (DSI). The validation was conducted at four spatial length scales from 25 to 150 km using windows to represent potential dust source areas centered on and positioned around eight meteorological stations within the study area. The predicted land erodibility had strong correlations with dust-event frequencies at half of the stations. Poor correlations at the other stations were linked to the inability of the model to account for temporal changes in soil erodibility, and comparing trends in the land erodibility of regions with dust events whose source areas lie outside the regions of interest. The model agreement with dust-event frequency trends was found to vary across spatial scales and was highly dependent on land type characteristics around the stations and on the types of dust events used for validation.     

Topology-controlled volume rendering

Topology provides a foundation for the development of mathematically sound tools for processing and exploration of scalar fields. Existing topology-based methods can be used to identify interesting features in volumetric data sets, to find seed sets for accelerated isosurface extraction, or to treat individual connected components as distinct entities for isosurfacing or interval volume rendering. We describe a framework for direct volume rendering based on segmenting a volume into regions of equivalent contour topology and applying separate transfer functions to each region. Each region corresponds to a branch of a hierarchical contour tree decomposition, and a separate transfer function can be defined for it. The novel contributions of our work are: 1) a volume rendering framework and interface where a unique transfer function can be assigned to each subvolume corresponding to a branch of the contour tree, 2) a runtime method for adjusting data values to reflect contour tree simplifications, 3) an efficient way of mapping a spatial location into the contour tree to determine the applicable transfer function, and 4) an algorithm for hardware-accelerated direct volume rendering that visualizes the contour tree-based segmentation at interactive frame rates using graphics processing units (GPUs) that support loops and conditional branches in fragment programs     

Integrated Computational Materials Engineering (ICME) Approach to Design of Novel Microstructures for Ti-Alloys

In this overview, we present integrated CAPHAD and phase-field modeling with critical experiments to explore a newly discovered, nonconventional, solid–solid phase transformation pathway based on the so-called pseudo-spinodal mechanism. We show that this new transformation pathway offers a new design strategy for Ti alloys with extremely fine and uniform α + β microstructures that could potentially have highly attractive balances of mechanical properties. To broaden the processing window for such a mechanism to operate, we also explore a different nonconventional transformation pathway that involves precursory phase separation. In addition, the variant selection process during the β → α transformation leading to macrozones is investigated and the results could shed light on how to control processing conditions to avoid or reduce microtexture at both the individual β grain level and the overall polycrystalline sample level.     

Characterization of sulfate-reducing granular sludge in the SANI process

Hong Kong practices seawater toilet flushing covering 80% of the population. A sulfur cycle-based biological nitrogen removal process, the Sulfate reduction, Autotrophic denitrification and Nitrification Integrated (SANI^®) process, had been developed to close the loop between the hybrid water supply and saline sewage treatment. To enhance this novel process, granulation of a Sulfate-Reducing Up-flow Sludge Bed (SRUSB) reactor has recently been conducted for organic removal and provision of electron donors (sulfide) for subsequent autotrophic denitrification, with a view to minimizing footprint and maximizing operation resilience. This further study was focused on the biological and physicochemical characteristics of the granular sulfate-reducing sludge. A lab-scale SRUSB reactor seeded with anaerobic digester sludge was operated with synthetic saline sewage for 368 days. At 1 h nominal hydraulic retention time (HRT) and 6.4 kg COD/m³-d organic loading rate, the SRUSB reactor achieved 90% COD and 75% sulfate removal efficiencies. Granular sludge was observed within 30 days, and became stable after 4 months of operation with diameters of 400–500 μm, SVI₅ of 30 ml/g, and extracellular polymeric substances of 23 mg carbohydrate/g VSS. Fluorescence in situ hybridization (FISH) analysis revealed that the granules were enriched with abundant sulfate-reducing bacteria (SRB) as compared with the seeding sludge. Pyrosequencing analysis of the 16S rRNA gene in the sulfate-reducing granules on day 90 indicated that the microbial community consisted of a diverse SRB genera, namely Desulfobulbus (18.1%), Desulfobacter (13.6%), Desulfomicrobium (5.6%), Desulfosarcina (0.73%) and Desulfovibrio (0.6%), accounting for 38.6% of total operational taxonomic units at genera level, with no methanogens detected. The microbial population and physicochemical properties of the granules well explained the excellent performance of the granular SRUSB reactor.     

Laser-Deposited In Situ TiC-Reinforced Nickel Matrix Composites: 3D Microstructure and Tribological Properties

A new class of Ni-Ti-C-based metal-matrix composites has been developed using the laser-engineered net shaping? process. These composites consist of an in situ formed and homogeneously distributed titanium carbide (TiC) phase reinforcing the nickel matrix. Additionally, by tailoring the Ti/C ratio in these composites, an additional graphitic phase can also be engineered into the microstructure. Serial-sectioning, followed by three-dimensional reconstruction of the microstructure in these composites, reveals homogeneously distributed primary and eutectic titanium carbide precipitates as well as a graphitic phase encompassing the primary carbides within the nickel matrix. The morphology and spatial distribution of these phases in three dimensions reveals that the eutectic carbides form a network linked by primary carbides or graphitic nodules at the nodes, which suggests interesting insights into the sequence of phase evolution. These three-phase Ni-TiC-C composites exhibit excellent tribological properties, in terms of an extremely low coefficient of friction while maintaining a relatively high hardness.     

Treating test-item nonresponse

This study presents the results of an empirical investigation into the effects of nonresponse on the measurement of student ability in large scale educational achievement studies. The analyses explored the bias in student and national ability estimate distributions relating to particular psychometric treatments of nonresponse. A range of replicated analyses were undertaken using data collected from a crossnational study of reading achievement. The relative merits of these treatments are summarized in conclusion, and implications for normative and methodological research and practice are considered. It is suggested that environmental and psychological antecedents of nonresponse need to be determined and that related variables be included as essential components in item response modelling.     

Airline planning benchmark problems—Part I:: Characterising networks and demand using limited data

This paper is the first of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. While optimisation has made an enormous contribution to airline planning in general, the area suffers from a lack of standardised data and benchmark problems. Current research typically tackles problems unique to a given carrier, with associated specification and data unavailable to the broader research community. This limits direct comparison of alternative approaches, and creates barriers of entry for the research community. Furthermore, flight schedule design has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. This is Part I of two papers taking first steps to address these issues. It does so by providing a framework and methodology for generating realistic airline demand data, controlled by scalable parameters. First, a characterisation of flight network topologies and network capacity distributions is deduced, based on the analysis of airline data. Then a multi-objective optimisation model is proposed to solve the inverse problem of inferring OD-pair demands from passenger loads on arcs. These two elements are combined to yield a methodology for generating realistic flight network topologies and OD-pair demand data, according to specified parameters. This methodology is used to produce 33 benchmark instances exhibiting a range of characteristics. Part II extends this work by partitioning the demand in each market (OD pair) into market segments, each with its own utility function and set of preferences for alternative airline products. The resulting demand data will better reflect recent empirical research on passenger preference, and is expected to facilitate passenger choice modelling in flight schedule optimisation.     

Complementary techniques for the characterization of thin film Ti/Nb multilayers

An aberration corrector on the probe-forming lens of a scanning TEM (STEM) equipped with an electron energy-loss spectrometer (EELS) and X-ray energy-dispersive spectrometer (XEDS) has been employed to investigate the compositional variations as a function of length scale in nanoscale Ti/Nb metallic multilayers. The composition profiles of EELS and XEDS were compared with the profiles obtained from the complementary technique of 3D atom probe tomography. At large layer widths (h≥7 nm, where h is the layer width) of Ti and Nb, XEDS composition profiles of Ti/Nb metallic multilayers are in good agreement with the EELS results. However, at reduced layer widths (h≈2 nm), profiles of EELS and atom probe exhibited similar compositional variations, whereas XEDS results have shown a marked difference. This difference in the composition profiling of the layers has been addressed with reference to the effects of beam broadening and the origin of the signals collected in these techniques. The advantage of using EELS over XEDS for these nanoscaled multilayered materials is demonstrated.     

An improved method for calculating the no-fit polygon

The no-fit polygon (NFP) is the set of feasible locations that one polygon may take with respect to another polygon, such that the polygons do not overlap. Feasible locations are required for most of the solutions to two-dimensional packing problems, and also for other problems such as robot motion planning.